Karimi, Davood; Ward, Rabab K
2016-10-01
Image models are central to all image processing tasks. The great advancements in digital image processing would not have been made possible without powerful models which, themselves, have evolved over time. In the past decade, "patch-based" models have emerged as one of the most effective models for natural images. Patch-based methods have outperformed other competing methods in many image processing tasks. These developments have come at a time when greater availability of powerful computational resources and growing concerns over the health risks of the ionizing radiation encourage research on image processing algorithms for computed tomography (CT). The goal of this paper is to explain the principles of patch-based methods and to review some of their recent applications in CT. We first review the central concepts in patch-based image processing and explain some of the state-of-the-art algorithms, with a focus on aspects that are more relevant to CT. Then, we review some of the recent application of patch-based methods in CT. Patch-based methods have already transformed the field of image processing, leading to state-of-the-art results in many applications. More recently, several studies have proposed patch-based algorithms for various image processing tasks in CT, from denoising and restoration to iterative reconstruction. Although these studies have reported good results, the true potential of patch-based methods for CT has not been yet appreciated. Patch-based methods can play a central role in image reconstruction and processing for CT. They have the potential to lead to substantial improvements in the current state of the art.
Li, Haobo; Chen, Yanxi; Qiang, Minfei; Zhang, Kun; Jiang, Yuchen; Zhang, Yijie; Jia, Xiaoyang
2017-06-14
The objective of this study is to evaluate the value of computed tomography (CT) post-processing images in postoperative assessment of Lisfranc injuries compared with plain radiographs. A total of 79 cases with closed Lisfranc injuries that were treated with conventional open reduction and internal fixation from January 2010 to June 2016 were analyzed. Postoperative assessment was performed by two independent orthopedic surgeons with both plain radiographs and CT post-processing images. Inter- and intra-observer agreement were analyzed by kappa statistics while the differences between the two postoperative imaging assessments were assessed using the χ 2 test (McNemar's test). Significance was assumed when p < 0.05. Inter- and intra-observer agreement of CT post-processing images was much higher than that of plain radiographs. Non-anatomic reduction was more easily identified in patients with injuries of Myerson classifications A, B1, B2, and C1 using CT post-processing images with overall groups (p < 0.05), and poor internal fixation was also more easily detected in patients with injuries of Myerson classifications A, B1, B2, and C2 using CT post-processing images with overall groups (p < 0.05). CT post-processing images can be more reliable than plain radiographs in the postoperative assessment of reduction and implant placement for Lisfranc injuries.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Leng, Shuai; Yu, Lifeng; Wang, Jia
Purpose: Our purpose was to reduce image noise in spectral CT by exploiting data redundancies in the energy domain to allow flexible selection of the number, width, and location of the energy bins. Methods: Using a variety of spectral CT imaging methods, conventional filtered backprojection (FBP) reconstructions were performed and resulting images were compared to those processed using a Local HighlY constrained backPRojection Reconstruction (HYPR-LR) algorithm. The mean and standard deviation of CT numbers were measured within regions of interest (ROIs), and results were compared between FBP and HYPR-LR. For these comparisons, the following spectral CT imaging methods were used:(i)more » numerical simulations based on a photon-counting, detector-based CT system, (ii) a photon-counting, detector-based micro CT system using rubidium and potassium chloride solutions, (iii) a commercial CT system equipped with integrating detectors utilizing tube potentials of 80, 100, 120, and 140 kV, and (iv) a clinical dual-energy CT examination. The effects of tube energy and energy bin width were evaluated appropriate to each CT system. Results: The mean CT number in each ROI was unchanged between FBP and HYPR-LR images for each of the spectral CT imaging scenarios, irrespective of bin width or tube potential. However, image noise, as represented by the standard deviation of CT numbers in each ROI, was reduced by 36%-76%. In all scenarios, image noise after HYPR-LR algorithm was similar to that of composite images, which used all available photons. No difference in spatial resolution was observed between HYPR-LR processing and FBP. Dual energy patient data processed using HYPR-LR demonstrated reduced noise in the individual, low- and high-energy images, as well as in the material-specific basis images. Conclusions: Noise reduction can be accomplished for spectral CT by exploiting data redundancies in the energy domain. HYPR-LR is a robust method for reducing image noise in a variety of spectral CT imaging systems without losing spatial resolution or CT number accuracy. This method improves the flexibility to select energy bins in the manner that optimizes material identification and separation without paying the penalty of increased image noise or its corollary, increased patient dose.« less
Xia, Yong; Eberl, Stefan; Wen, Lingfeng; Fulham, Michael; Feng, David Dagan
2012-01-01
Dual medical imaging modalities, such as PET-CT, are now a routine component of clinical practice. Medical image segmentation methods, however, have generally only been applied to single modality images. In this paper, we propose the dual-modality image segmentation model to segment brain PET-CT images into gray matter, white matter and cerebrospinal fluid. This model converts PET-CT image segmentation into an optimization process controlled simultaneously by PET and CT voxel values and spatial constraints. It is innovative in the creation and application of the modality discriminatory power (MDP) coefficient as a weighting scheme to adaptively combine the functional (PET) and anatomical (CT) information on a voxel-by-voxel basis. Our approach relies upon allowing the modality with higher discriminatory power to play a more important role in the segmentation process. We compared the proposed approach to three other image segmentation strategies, including PET-only based segmentation, combination of the results of independent PET image segmentation and CT image segmentation, and simultaneous segmentation of joint PET and CT images without an adaptive weighting scheme. Our results in 21 clinical studies showed that our approach provides the most accurate and reliable segmentation for brain PET-CT images. Copyright © 2011 Elsevier Ltd. All rights reserved.
Leng, Shuai; Yu, Lifeng; Wang, Jia; Fletcher, Joel G; Mistretta, Charles A; McCollough, Cynthia H
2011-09-01
Our purpose was to reduce image noise in spectral CT by exploiting data redundancies in the energy domain to allow flexible selection of the number, width, and location of the energy bins. Using a variety of spectral CT imaging methods, conventional filtered backprojection (FBP) reconstructions were performed and resulting images were compared to those processed using a Local HighlY constrained backPRojection Reconstruction (HYPR-LR) algorithm. The mean and standard deviation of CT numbers were measured within regions of interest (ROIs), and results were compared between FBP and HYPR-LR. For these comparisons, the following spectral CT imaging methods were used:(i) numerical simulations based on a photon-counting, detector-based CT system, (ii) a photon-counting, detector-based micro CT system using rubidium and potassium chloride solutions, (iii) a commercial CT system equipped with integrating detectors utilizing tube potentials of 80, 100, 120, and 140 kV, and (iv) a clinical dual-energy CT examination. The effects of tube energy and energy bin width were evaluated appropriate to each CT system. The mean CT number in each ROI was unchanged between FBP and HYPR-LR images for each of the spectral CT imaging scenarios, irrespective of bin width or tube potential. However, image noise, as represented by the standard deviation of CT numbers in each ROI, was reduced by 36%-76%. In all scenarios, image noise after HYPR-LR algorithm was similar to that of composite images, which used all available photons. No difference in spatial resolution was observed between HYPR-LR processing and FBP. Dual energy patient data processed using HYPR-LR demonstrated reduced noise in the individual, low- and high-energy images, as well as in the material-specific basis images. Noise reduction can be accomplished for spectral CT by exploiting data redundancies in the energy domain. HYPR-LR is a robust method for reducing image noise in a variety of spectral CT imaging systems without losing spatial resolution or CT number accuracy. This method improves the flexibility to select energy bins in the manner that optimizes material identification and separation without paying the penalty of increased image noise or its corollary, increased patient dose.
Greenwood, Taylor J; Lopez-Costa, Rodrigo I; Rhoades, Patrick D; Ramírez-Giraldo, Juan C; Starr, Matthew; Street, Mandie; Duncan, James; McKinstry, Robert C
2015-01-01
The marked increase in radiation exposure from medical imaging, especially in children, has caused considerable alarm and spurred efforts to preserve the benefits but reduce the risks of imaging. Applying the principles of the Image Gently campaign, data-driven process and quality improvement techniques such as process mapping and flowcharting, cause-and-effect diagrams, Pareto analysis, statistical process control (control charts), failure mode and effects analysis, "lean" or Six Sigma methodology, and closed feedback loops led to a multiyear program that has reduced overall computed tomographic (CT) examination volume by more than fourfold and concurrently decreased radiation exposure per CT study without compromising diagnostic utility. This systematic approach involving education, streamlining access to magnetic resonance imaging and ultrasonography, auditing with comparison with benchmarks, applying modern CT technology, and revising CT protocols has led to a more than twofold reduction in CT radiation exposure between 2005 and 2012 for patients at the authors' institution while maintaining diagnostic utility. (©)RSNA, 2015.
SU-F-I-51: CT/MR Image Deformation: The Clinical Assessment QA in Target Delineation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, C; Chen, Y
Purpose: To study the deformation effects in CT/MR image registration of head and neck (HN) cancers. We present a clinical indication in guiding and simplifying registration procedures of this process while CT images possessed artifacts. Methods: CT/MR image fusion provides better soft tissue contrast in intracranial GTV definition with artifacts. However, whether the fusion process should include the deformation process is questionable and not recommended. We performed CT/MR image registration of a HN patient with tonsil GTV and nodes delineation on Varian Velocity™ system. Both rigid transformation and deformable registration of the same CT/MR imaging data were processed separately. Physician’smore » selection of target delineation was implemented to identify the variations. Transformation matrix was shown with visual identification, as well as the deformation QA numbers and figures were assessed. Results: The deformable CT/MR images were traced with the calculated matrix, both translation and rotational parameters were summarized. In deformable quality QA, the calculated Jacobian matrix was analyzed, which the min/mean/max of 0.73/0/99/1.37, respectively. Jacobian matrix of right neck node was 0.84/1.13/1.41, which present dis-similarity of the nodal area. If Jacobian = 1, the deformation is at the optimum situation. In this case, the deformation results have shown better target delineation for CT/MR deformation than rigid transformation. Though the root-mean-square vector difference is 1.48 mm, with similar rotational components, the cord and vertebrae position were aligned much better in the deformable MR images than the rigid transformation. Conclusion: CT/MR with/without image deformation presents similar image registration matrix; there were significant differentiate the anatomical structures in the region of interest by deformable process. Though vendor suggested only rigid transformation between CT/MR assuming the geometry remain similar, our findings indicated with patient positional variations, deformation registration is needed to generate proper GTV coverage, which will be irradiated more accurately in the following boost phase.« less
Using digital photo technology to improve visualization of gastric lumen CT images
NASA Astrophysics Data System (ADS)
Pyrgioti, M.; Kyriakidis, A.; Chrysostomou, S.; Panaritis, V.
2006-12-01
In order to evaluate the gastric lumen CT images better, a new method is being applied to images using an Image Processing software. During a 12-month period, 69 patients with various gastric symptoms and 20 normal (as far as it concerns the upper gastrointestinal system) volunteers underwent computed tomography of the upper gastrointestinal system. Just before the examination the patients and the normal volunteers underwent preparation with 40 ml soda water and 10 ml gastrografin. All the CT images were digitized with an Olympus 3.2 Mpixel digital camera and further processed with an Image Processing software. The administration per os of gastrografin and soda water resulted in the distension of the stomach and consequently better visualization of all the anatomic parts. By using an Image Processing software in a PC, all the pathological and normal images of the stomach were better diagnostically estimated. We believe that the photo digital technology improves the diagnostic capacity not only of the CT image but also in MRI and probably many other imaging methods.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kofler, J.
2016-06-15
Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This coursemore » will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.« less
Prostate seed implant quality assessment using MR and CT image fusion.
Amdur, R J; Gladstone, D; Leopold, K A; Harris, R D
1999-01-01
After a seed implant of the prostate, computerized tomography (CT) is ideal for determining seed distribution but soft tissue anatomy is frequently not well visualized. Magnetic resonance (MR) images soft tissue anatomy well but seed visualization is problematic. We describe a method of fusing CT and MR images to exploit the advantages of both of these modalities when assessing the quality of a prostate seed implant. Eleven consecutive prostate seed implant patients were imaged with axial MR and CT scans. MR and CT images were fused in three dimensions using the Pinnacle 3.0 version of the ADAC treatment planning system. The urethra and bladder base were used to "line up" MR and CT image sets during image fusion. Alignment was accomplished using translation and rotation in the three ortho-normal planes. Accuracy of image fusion was evaluated by calculating the maximum deviation in millimeters between the center of the urethra on axial MR versus CT images. Implant quality was determined by comparing dosimetric results to previously set parameters. Image fusion was performed with a high degree of accuracy. When lining up the urethra and base of bladder, the maximum difference in axial position of the urethra between MR and CT averaged 2.5 mm (range 1.3-4.0 mm, SD 0.9 mm). By projecting CT-derived dose distributions over MR images of soft tissue structures, qualitative and quantitative evaluation of implant quality is straightforward. The image-fusion process we describe provides a sophisticated way of assessing the quality of a prostate seed implant. Commercial software makes the process time-efficient and available to any clinical practice with a high-quality treatment planning system. While we use MR to image soft tissue structures, the process could be used with any imaging modality that is able to visualize the prostatic urethra (e.g., ultrasound).
Fischer, Michael A; Leidner, Bertil; Kartalis, Nikolaos; Svensson, Anders; Aspelin, Peter; Albiin, Nils; Brismar, Torkel B
2014-01-01
To assess feasibility and image quality (IQ) of a new post-processing algorithm for retrospective extraction of an optimised multi-phase CT (time-resolved CT) of the liver from volumetric perfusion imaging. Sixteen patients underwent clinically indicated perfusion CT using 4D spiral mode of dual-source 128-slice CT. Three image sets were reconstructed: motion-corrected and noise-reduced (MCNR) images derived from 4D raw data; maximum and average intensity projections (time MIP/AVG) of the arterial/portal/portal-venous phases and all phases (total MIP/ AVG) derived from retrospective fusion of dedicated MCNR split series. Two readers assessed the IQ, detection rate and evaluation time; one reader assessed image noise and lesion-to-liver contrast. Time-resolved CT was feasible in all patients. Each post-processing step yielded a significant reduction of image noise and evaluation time, maintaining lesion-to-liver contrast. Time MIPs/AVGs showed the highest overall IQ without relevant motion artefacts and best depiction of arterial and portal/portal-venous phases respectively. Time MIPs demonstrated a significantly higher detection rate for arterialised liver lesions than total MIPs/AVGs and the raw data series. Time-resolved CT allows data from volumetric perfusion imaging to be condensed into an optimised multi-phase liver CT, yielding a superior IQ and higher detection rate for arterialised liver lesions than the raw data series. • Four-dimensional computed tomography is limited by motion artefacts and poor image quality. • Time-resolved-CT facilitates 4D-CT data visualisation, segmentation and analysis by condensing raw data. • Time-resolved CT demonstrates better image quality than raw data images. • Time-resolved CT improves detection of arterialised liver lesions in cirrhotic patients.
İntepe, Yavuz Selim; Metin, Bayram; Şahin, Sevinç; Kaya, Buğra; Okur, Aylin
2016-08-01
The objective of this study was to compare the results of transthoracic biopsies performed through the use of FDG PET/CT imaging with the results of transthoracic needle biopsy performed without using the FDG PET/CT imaging. The medical files of a total of 58 patients with pulmonary and mediastinal masses. A total of 20 patients, who were suspected of malignancy with the SUVmax value of over 2.5 in FDG PET/CT, underwent a biopsy process. Twelve patients with no suspicion of malignancy in accordance with CT images and with the SUVmax value below 2.5 underwent no biopsy procedure, and hence, they were excluded from the study. On the other hand, 26 patients directly went through a biopsy process with the suspicion of malignancy according to CT imaging, regardless of performing any FDG PET/CT imaging. According to the biopsy results, the number of the patients diagnosed with cancer was 20 (43.5%), while the number of non-cancerous patients was 26 (56.5%). When these findings were considered, it was determined that the sensitivity of the whole TTNB (transthoracic needle biopsy) was 80.8%, and the specificity was found as 100%. The positive predictive value of the whole TTNB was 100%, while its negative predictive value was found to be 80%. The sensitivity in TTNB performed together with FDG PET/CT was 90.9%, whereas the specificity was 100%. The positive predictive value of TTNB with FDG PET/CT was 100%, while its negative predictive value was found to be 81.8%. The sensitivity in TTNB performed without the use of FDG PET/CT was 73.3%, whereas the specificity was determined as 100%. Performing FDG PET/CT imaging process prior to a transthoracic biopsy as well as preferring FDG PET/CT for the spot on which the biopsy will be performed during the transthoracic biopsy procedure increases the rate of receiving accurate diagnosis.
Neural network and its application to CT imaging
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nikravesh, M.; Kovscek, A.R.; Patzek, T.W.
We present an integrated approach to imaging the progress of air displacement by spontaneous imbibition of oil into sandstone. We combine Computerized Tomography (CT) scanning and neural network image processing. The main aspects of our approach are (I) visualization of the distribution of oil and air saturation by CT, (II) interpretation of CT scans using neural networks, and (III) reconstruction of 3-D images of oil saturation from the CT scans with a neural network model. Excellent agreement between the actual images and the neural network predictions is found.
Recent Advances in Cardiac Computed Tomography: Dual Energy, Spectral and Molecular CT Imaging
Danad, Ibrahim; Fayad, Zahi A.; Willemink, Martin J.; Min, James K.
2015-01-01
Computed tomography (CT) evolved into a powerful diagnostic tool and it is impossible to imagine current clinical practice without CT imaging. Due to its widespread availability, ease of clinical application, superb sensitivity for detection of CAD, and non-invasive nature, CT has become a valuable tool within the armamentarium of the cardiologist. In the last few years, numerous technological advances in CT have occurred—including dual energy CT (DECT), spectral CT and CT-based molecular imaging. By harnessing the advances in technology, cardiac CT has advanced beyond the mere evaluation of coronary stenosis to an imaging modality tool that permits accurate plaque characterization, assessment of myocardial perfusion and even probing of molecular processes that are involved in coronary atherosclerosis. Novel innovations in CT contrast agents and pre-clinical spectral CT devices have paved the way for CT-based molecular imaging. PMID:26068288
Kakakhel, M B; Jirasek, A; Johnston, H; Kairn, T; Trapp, J V
2017-03-01
This study evaluated the feasibility of combining the 'zero-scan' (ZS) X-ray computed tomography (CT) based polymer gel dosimeter (PGD) readout with adaptive mean (AM) filtering for improving the signal to noise ratio (SNR), and to compare these results with available average scan (AS) X-ray CT readout techniques. NIPAM PGD were manufactured, irradiated with 6 MV photons, CT imaged and processed in Matlab. AM filter for two iterations, with 3 × 3 and 5 × 5 pixels (kernel size), was used in two scenarios (a) the CT images were subjected to AM filtering (pre-processing) and these were further employed to generate AS and ZS gel images, and (b) the AS and ZS images were first reconstructed from the CT images and then AM filtering was carried out (post-processing). SNR was computed in an ROI of 30 × 30 for different pre and post processing cases. Results showed that the ZS technique combined with AM filtering resulted in improved SNR. Using the previously-recommended 25 images for reconstruction the ZS pre-processed protocol can give an increase of 44% and 80% in SNR for 3 × 3 and 5 × 5 kernel sizes respectively. However, post processing using both techniques and filter sizes introduced blur and a reduction in the spatial resolution. Based on this work, it is possible to recommend that the ZS method may be combined with pre-processed AM filtering using appropriate kernel size, to produce a large increase in the SNR of the reconstructed PGD images.
Sethi, A; Rusu, I; Surucu, M; Halama, J
2012-06-01
Evaluate accuracy of multi-modality image registration in radiotherapy planning process. A water-filled anthropomorphic head phantom containing eight 'donut-shaped' fiducial markers (3 internal + 5 external) was selected for this study. Seven image sets (3CTs, 3MRs and PET) of phantom were acquired and fused in a commercial treatment planning system. First, a narrow slice (0.75mm) baseline CT scan was acquired (CT1). Subsequently, the phantom was re-scanned with a coarse slice width = 1.5mm (CT2) and after subjecting phantom to rotation/displacement (CT3). Next, the phantom was scanned in a 1.5 Tesla MR scanner and three MR image sets (axial T1, axial T2, coronal T1) were acquired at 2mm slice width. Finally, the phantom and center of fiducials were doped with 18F and a PET scan was performed with 2mm cubic voxels. All image scans (CT/MR/PET) were fused to the baseline (CT1) data using automated mutual-information based fusion algorithm. Difference between centroids of fiducial markers in various image modalities was used to assess image registration accuracy. CT/CT image registration was superior to CT/MR and CT/PET: average CT/CT fusion error was found to be 0.64 ± 0.14 mm. Corresponding values for CT/MR and CT/PET fusion were 1.33 ± 0.71mm and 1.11 ± 0.37mm. Internal markers near the center of phantom fused better than external markers placed on the phantom surface. This was particularly true for the CT/MR and CT/PET. The inferior quality of external marker fusion indicates possible distortion effects toward the edges of MR image. Peripheral targets in the PET scan may be subject to parallax error caused by depth of interaction of photons in detectors. Current widespread use of multimodality imaging in radiotherapy planning calls for periodic quality assurance of image registration process. Such studies may help improve safety and accuracy in treatment planning. © 2012 American Association of Physicists in Medicine.
Discriminative feature representation: an effective postprocessing solution to low dose CT imaging
NASA Astrophysics Data System (ADS)
Chen, Yang; Liu, Jin; Hu, Yining; Yang, Jian; Shi, Luyao; Shu, Huazhong; Gui, Zhiguo; Coatrieux, Gouenou; Luo, Limin
2017-03-01
This paper proposes a concise and effective approach termed discriminative feature representation (DFR) for low dose computerized tomography (LDCT) image processing, which is currently a challenging problem in medical imaging field. This DFR method assumes LDCT images as the superposition of desirable high dose CT (HDCT) 3D features and undesirable noise-artifact 3D features (the combined term of noise and artifact features induced by low dose scan protocols), and the decomposed HDCT features are used to provide the processed LDCT images with higher quality. The target HDCT features are solved via the DFR algorithm using a featured dictionary composed by atoms representing HDCT features and noise-artifact features. In this study, the featured dictionary is efficiently built using physical phantom images collected from the same CT scanner as the target clinical LDCT images to process. The proposed DFR method also has good robustness in parameter setting for different CT scanner types. This DFR method can be directly applied to process DICOM formatted LDCT images, and has good applicability to current CT systems. Comparative experiments with abdomen LDCT data validate the good performance of the proposed approach. This research was supported by National Natural Science Foundation under grants (81370040, 81530060), the Fundamental Research Funds for the Central Universities, and the Qing Lan Project in Jiangsu Province.
NASA Astrophysics Data System (ADS)
Zhang, Lixin; Lin, Min; Wan, Baikun; Zhou, Yu; Wang, Yizhong
2005-01-01
In this paper, a new method of body fat and its distribution testing is proposed based on CT image processing. As it is more sensitive to slight differences in attenuation than standard radiography, CT depicts the soft tissues with better clarity. And body fat has a distinct grayness range compared with its neighboring tissues in a CT image. An effective multi-thresholds image segmentation method based on potential function clustering is used to deal with multiple peaks in the grayness histogram of a CT image. The CT images of abdomens of 14 volunteers with different fatness are processed with the proposed method. Not only can the result of total fat area be got, but also the differentiation of subcutaneous fat from intra-abdominal fat has been identified. The results show the adaptability and stability of the proposed method, which will be a useful tool for diagnosing obesity.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Castillo, S; Castillo, R; Castillo, E
2014-06-15
Purpose: Artifacts arising from the 4D CT acquisition and post-processing methods add systematic uncertainty to the treatment planning process. We propose an alternate cine 4D CT acquisition and post-processing method to consistently reduce artifacts, and explore patient parameters indicative of image quality. Methods: In an IRB-approved protocol, 18 patients with primary thoracic malignancies received a standard cine 4D CT acquisition followed by an oversampling 4D CT that doubled the number of images acquired. A second cohort of 10 patients received the clinical 4D CT plus 3 oversampling scans for intra-fraction reproducibility. The clinical acquisitions were processed by the standard phasemore » sorting method. The oversampling acquisitions were processed using Dijkstras algorithm to optimize an artifact metric over available image data. Image quality was evaluated with a one-way mixed ANOVA model using a correlation-based artifact metric calculated from the final 4D CT image sets. Spearman correlations and a linear mixed model tested the association between breathing parameters, patient characteristics, and image quality. Results: The oversampling 4D CT scans reduced artifact presence significantly by 27% and 28%, for the first cohort and second cohort respectively. From cohort 2, the inter-replicate deviation for the oversampling method was within approximately 13% of the cross scan average at the 0.05 significance level. Artifact presence for both clinical and oversampling methods was significantly correlated with breathing period (ρ=0.407, p-value<0.032 clinical, ρ=0.296, p-value<0.041 oversampling). Artifact presence in the oversampling method was significantly correlated with amount of data acquired, (ρ=-0.335, p-value<0.02) indicating decreased artifact presence with increased breathing cycles per scan location. Conclusion: The 4D CT oversampling acquisition with optimized sorting reduced artifact presence significantly and reproducibly compared to the phase-sorted clinical acquisition.« less
Rubin, Geoffrey D.; Leipsic, Jonathon; Schoepf, U. Joseph; Fleischmann, Dominik; Napel, Sandy
2015-01-01
Through a marriage of spiral computed tomography (CT) and graphical volumetric image processing, CT angiography was born 20 years ago. Fueled by a series of technical innovations in CT and image processing, over the next 5–15 years, CT angiography toppled conventional angiography, the undisputed diagnostic reference standard for vascular disease for the prior 70 years, as the preferred modality for the diagnosis and characterization of most cardiovascular abnormalities. This review recounts the evolution of CT angiography from its development and early challenges to a maturing modality that has provided unique insights into cardiovascular disease characterization and management. Selected clinical challenges, which include acute aortic syndromes, peripheral vascular disease, aortic stent-graft and transcatheter aortic valve assessment, and coronary artery disease, are presented as contrasting examples of how CT angiography is changing our approach to cardiovascular disease diagnosis and management. Finally, the recently introduced capabilities for multispectral imaging, tissue perfusion imaging, and radiation dose reduction through iterative reconstruction are explored with consideration toward the continued refinement and advancement of CT angiography. PMID:24848958
Jin, Shuo; Li, Dengwang; Wang, Hongjun; Yin, Yong
2013-01-07
Accurate registration of 18F-FDG PET (positron emission tomography) and CT (computed tomography) images has important clinical significance in radiation oncology. PET and CT images are acquired from (18)F-FDG PET/CT scanner, but the two acquisition processes are separate and take a long time. As a result, there are position errors in global and deformable errors in local caused by respiratory movement or organ peristalsis. The purpose of this work was to implement and validate a deformable CT to PET image registration method in esophageal cancer to eventually facilitate accurate positioning the tumor target on CT, and improve the accuracy of radiation therapy. Global registration was firstly utilized to preprocess position errors between PET and CT images, achieving the purpose of aligning these two images on the whole. Demons algorithm, based on optical flow field, has the features of fast process speed and high accuracy, and the gradient of mutual information-based demons (GMI demons) algorithm adds an additional external force based on the gradient of mutual information (GMI) between two images, which is suitable for multimodality images registration. In this paper, GMI demons algorithm was used to achieve local deformable registration of PET and CT images, which can effectively reduce errors between internal organs. In addition, to speed up the registration process, maintain its robustness, and avoid the local extremum, multiresolution image pyramid structure was used before deformable registration. By quantitatively and qualitatively analyzing cases with esophageal cancer, the registration scheme proposed in this paper can improve registration accuracy and speed, which is helpful for precisely positioning tumor target and developing the radiation treatment planning in clinical radiation therapy application.
Jin, Shuo; Li, Dengwang; Yin, Yong
2013-01-01
Accurate registration of 18F−FDG PET (positron emission tomography) and CT (computed tomography) images has important clinical significance in radiation oncology. PET and CT images are acquired from 18F−FDG PET/CT scanner, but the two acquisition processes are separate and take a long time. As a result, there are position errors in global and deformable errors in local caused by respiratory movement or organ peristalsis. The purpose of this work was to implement and validate a deformable CT to PET image registration method in esophageal cancer to eventually facilitate accurate positioning the tumor target on CT, and improve the accuracy of radiation therapy. Global registration was firstly utilized to preprocess position errors between PET and CT images, achieving the purpose of aligning these two images on the whole. Demons algorithm, based on optical flow field, has the features of fast process speed and high accuracy, and the gradient of mutual information‐based demons (GMI demons) algorithm adds an additional external force based on the gradient of mutual information (GMI) between two images, which is suitable for multimodality images registration. In this paper, GMI demons algorithm was used to achieve local deformable registration of PET and CT images, which can effectively reduce errors between internal organs. In addition, to speed up the registration process, maintain its robustness, and avoid the local extremum, multiresolution image pyramid structure was used before deformable registration. By quantitatively and qualitatively analyzing cases with esophageal cancer, the registration scheme proposed in this paper can improve registration accuracy and speed, which is helpful for precisely positioning tumor target and developing the radiation treatment planning in clinical radiation therapy application. PACS numbers: 87.57.nj, 87.57.Q‐, 87.57.uk PMID:23318381
Dong, J; Hayakawa, Y; Kober, C
2014-01-01
When metallic prosthetic appliances and dental fillings exist in the oral cavity, the appearance of metal-induced streak artefacts is not avoidable in CT images. The aim of this study was to develop a method for artefact reduction using the statistical reconstruction on multidetector row CT images. Adjacent CT images often depict similar anatomical structures. Therefore, reconstructed images with weak artefacts were attempted using projection data of an artefact-free image in a neighbouring thin slice. Images with moderate and strong artefacts were continuously processed in sequence by successive iterative restoration where the projection data was generated from the adjacent reconstructed slice. First, the basic maximum likelihood-expectation maximization algorithm was applied. Next, the ordered subset-expectation maximization algorithm was examined. Alternatively, a small region of interest setting was designated. Finally, the general purpose graphic processing unit machine was applied in both situations. The algorithms reduced the metal-induced streak artefacts on multidetector row CT images when the sequential processing method was applied. The ordered subset-expectation maximization and small region of interest reduced the processing duration without apparent detriments. A general-purpose graphic processing unit realized the high performance. A statistical reconstruction method was applied for the streak artefact reduction. The alternative algorithms applied were effective. Both software and hardware tools, such as ordered subset-expectation maximization, small region of interest and general-purpose graphic processing unit achieved fast artefact correction.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kemp, B.
2016-06-15
Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This coursemore » will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pooley, R.
2016-06-15
Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This coursemore » will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.« less
Siri, Sangeeta K; Latte, Mrityunjaya V
2017-11-01
Many different diseases can occur in the liver, including infections such as hepatitis, cirrhosis, cancer and over effect of medication or toxins. The foremost stage for computer-aided diagnosis of liver is the identification of liver region. Liver segmentation algorithms extract liver image from scan images which helps in virtual surgery simulation, speedup the diagnosis, accurate investigation and surgery planning. The existing liver segmentation algorithms try to extort exact liver image from abdominal Computed Tomography (CT) scan images. It is an open problem because of ambiguous boundaries, large variation in intensity distribution, variability of liver geometry from patient to patient and presence of noise. A novel approach is proposed to meet challenges in extracting the exact liver image from abdominal CT scan images. The proposed approach consists of three phases: (1) Pre-processing (2) CT scan image transformation to Neutrosophic Set (NS) and (3) Post-processing. In pre-processing, the noise is removed by median filter. The "new structure" is designed to transform a CT scan image into neutrosophic domain which is expressed using three membership subset: True subset (T), False subset (F) and Indeterminacy subset (I). This transform approximately extracts the liver image structure. In post processing phase, morphological operation is performed on indeterminacy subset (I) and apply Chan-Vese (C-V) model with detection of initial contour within liver without user intervention. This resulted in liver boundary identification with high accuracy. Experiments show that, the proposed method is effective, robust and comparable with existing algorithm for liver segmentation of CT scan images. Copyright © 2017 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Ishimori, Hiroyuki; Kawata, Yoshiki; Niki, Noboru; Nakaya, Yoshihiro; Ohmatsu, Hironobu; Matsui, Eisuke; Fujii, Masashi; Moriyama, Noriyuki
2007-03-01
We have developed a Micro CT system for understanding lung function at a high resolution of the micrometer order (up to 5µm in spatial resolution). Micro CT system enables the removal specimen of lungs to be observed at micro level, has expected a big contribution for micro internal organs morphology and the image diagnosis study. In this research, we develop system to visualize lung microstructures in three dimensions from micro CT images and analyze them. They characterize in that high CT value of the noise area is, and the difficulty of only using threshold processing to extract the alveolar wall of micro CT images. Thus, we are developing a method of extracting the alveolar wall with surface thinning algorithm. In this report, we propose the method which reduces the excessive degeneracy of figure which caused by surface thinning process. And, we apply this algorithm to the micro CT image of the actual pulmonary specimen. It is shown that the extraction of the alveolus wall becomes possible in the high precision.
NASA Astrophysics Data System (ADS)
Zhang, Hao; Gang, Grace J.; Lee, Junghoon; Wong, John; Stayman, J. Webster
2017-03-01
Purpose: There are many clinical situations where diagnostic CT is used for an initial diagnosis or treatment planning, followed by one or more CBCT scans that are part of an image-guided intervention. Because the high-quality diagnostic CT scan is a rich source of patient-specific anatomical knowledge, this provides an opportunity to incorporate the prior CT image into subsequent CBCT reconstruction for improved image quality. We propose a penalized-likelihood method called reconstruction of difference (RoD), to directly reconstruct differences between the CBCT scan and the CT prior. In this work, we demonstrate the efficacy of RoD with clinical patient datasets. Methods: We introduce a data processing workflow using the RoD framework to reconstruct anatomical changes between the prior CT and current CBCT. This workflow includes processing steps to account for non-anatomical differences between the two scans including 1) scatter correction for CBCT datasets due to increased scatter fractions in CBCT data; 2) histogram matching for attenuation variations between CT and CBCT; and 3) registration for different patient positioning. CBCT projection data and CT planning volumes for two radiotherapy patients - one abdominal study and one head-and-neck study - were investigated. Results: In comparisons between the proposed RoD framework and more traditional FDK and penalized-likelihood reconstructions, we find a significant improvement in image quality when prior CT information is incorporated into the reconstruction. RoD is able to provide additional low-contrast details while correctly incorporating actual physical changes in patient anatomy. Conclusions: The proposed framework provides an opportunity to either improve image quality or relax data fidelity constraints for CBCT imaging when prior CT studies of the same patient are available. Possible clinical targets include CBCT image-guided radiotherapy and CBCT image-guided surgeries.
3D visualization of Thoraco-Lumbar Spinal Lesions in German Shepherd Dog
DOE Office of Scientific and Technical Information (OSTI.GOV)
Azpiroz, J.; Krafft, J.; Cadena, M.
2006-09-08
Computed tomography (CT) has been found to be an excellent imaging modality due to its sensitivity to characterize the morphology of the spine in dogs. This technique is considered to be particularly helpful for diagnosing spinal cord atrophy and spinal stenosis. The three-dimensional visualization of organs and bones can significantly improve the diagnosis of certain diseases in dogs. CT images were acquired of a German shepherd's dog spinal cord to generate stacks and digitally process them to arrange them in a volume image. All imaging experiments were acquired using standard clinical protocols on a clinical CT scanner. The three-dimensional visualizationmore » allowed us to observe anatomical structures that otherwise are not possible to observe with two-dimensional images. The combination of an imaging modality like CT together with imaging processing techniques can be a powerful tool for the diagnosis of a number of animal diseases.« less
3D visualization of Thoraco-Lumbar Spinal Lesions in German Shepherd Dog
NASA Astrophysics Data System (ADS)
Azpiroz, J.; Krafft, J.; Cadena, M.; Rodríguez, A. O.
2006-09-01
Computed tomography (CT) has been found to be an excellent imaging modality due to its sensitivity to characterize the morphology of the spine in dogs. This technique is considered to be particularly helpful for diagnosing spinal cord atrophy and spinal stenosis. The three-dimensional visualization of organs and bones can significantly improve the diagnosis of certain diseases in dogs. CT images were acquired of a German shepherd's dog spinal cord to generate stacks and digitally process them to arrange them in a volume image. All imaging experiments were acquired using standard clinical protocols on a clinical CT scanner. The three-dimensional visualization allowed us to observe anatomical structures that otherwise are not possible to observe with two-dimensional images. The combination of an imaging modality like CT together with imaging processing techniques can be a powerful tool for the diagnosis of a number of animal diseases.
WE-G-209-00: Identifying Image Artifacts, Their Causes, and How to Fix Them
DOE Office of Scientific and Technical Information (OSTI.GOV)
NONE
Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This coursemore » will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.« less
NASA Astrophysics Data System (ADS)
Cruz, Francisco; Sevilla, Raquel; Zhu, Joe; Vanko, Amy; Lee, Jung Hoon; Dogdas, Belma; Zhang, Weisheng
2014-03-01
Bone mineral density (BMD) obtained from a CT image is an imaging biomarker used pre-clinically for characterizing the Rheumatoid arthritis (RA) phenotype. We use this biomarker in animal studies for evaluating disease progression and for testing various compounds. In the current setting, BMD measurements are obtained manually by selecting the regions of interest from three-dimensional (3-D) CT images of rat legs, which results in a laborious and low-throughput process. Combining image processing techniques, such as intensity thresholding and skeletonization, with mathematical techniques in curve fitting and curvature calculations, we developed an algorithm for quick, consistent, and automatic detection of joints in large CT data sets. The implemented algorithm has reduced analysis time for a study with 200 CT images from 10 days to 3 days and has improved the robust detection of the obtained regions of interest compared with manual segmentation. This algorithm has been used successfully in over 40 studies.
Deep learning methods to guide CT image reconstruction and reduce metal artifacts
NASA Astrophysics Data System (ADS)
Gjesteby, Lars; Yang, Qingsong; Xi, Yan; Zhou, Ye; Zhang, Junping; Wang, Ge
2017-03-01
The rapidly-rising field of machine learning, including deep learning, has inspired applications across many disciplines. In medical imaging, deep learning has been primarily used for image processing and analysis. In this paper, we integrate a convolutional neural network (CNN) into the computed tomography (CT) image reconstruction process. Our first task is to monitor the quality of CT images during iterative reconstruction and decide when to stop the process according to an intelligent numerical observer instead of using a traditional stopping rule, such as a fixed error threshold or a maximum number of iterations. After training on ground truth images, the CNN was successful in guiding an iterative reconstruction process to yield high-quality images. Our second task is to improve a sinogram to correct for artifacts caused by metal objects. A large number of interpolation and normalization-based schemes were introduced for metal artifact reduction (MAR) over the past four decades. The NMAR algorithm is considered a state-of-the-art method, although residual errors often remain in the reconstructed images, especially in cases of multiple metal objects. Here we merge NMAR with deep learning in the projection domain to achieve additional correction in critical image regions. Our results indicate that deep learning can be a viable tool to address CT reconstruction challenges.
NASA Astrophysics Data System (ADS)
Nishimaru, Eiji; Ichikawa, Katsuhiro; Okita, Izumi; Ninomiya, Yuuji; Tomoshige, Yukihiro; Kurokawa, Takehiro; Ono, Yutaka; Nakamura, Yuko; Suzuki, Masayuki
2008-03-01
Recently, several kinds of post-processing image filters which reduce the noise of computed tomography (CT) images have been proposed. However, these image filters are mostly for adults. Because these are not very effective in small (< 20 cm) display fields of view (FOV), we cannot use them for pediatric body images (e.g., premature babies and infant children). We have developed a new noise reduction filter algorithm for pediatric body CT images. This algorithm is based on a 3D post-processing in which the output pixel values are calculated by nonlinear interpolation in z-directions on original volumetric-data-sets. This algorithm does not need the in-plane (axial plane) processing, so the spatial resolution does not change. From the phantom studies, our algorithm could reduce SD up to 40% without affecting the spatial resolution of x-y plane and z-axis, and improved the CNR up to 30%. This newly developed filter algorithm will be useful for the diagnosis and radiation dose reduction of the pediatric body CT images.
Classification of stroke disease using convolutional neural network
NASA Astrophysics Data System (ADS)
Marbun, J. T.; Seniman; Andayani, U.
2018-03-01
Stroke is a condition that occurs when the blood supply stop flowing to the brain because of a blockage or a broken blood vessel. A symptoms that happen when experiencing stroke, some of them is a dropped consciousness, disrupted vision and paralyzed body. The general examination is being done to get a picture of the brain part that have stroke using Computerized Tomography (CT) Scan. The image produced from CT will be manually checked and need a proper lighting by doctor to get a type of stroke. That is why it needs a method to classify stroke from CT image automatically. A method proposed in this research is Convolutional Neural Network. CT image of the brain is used as the input for image processing. The stage before classification are image processing (Grayscaling, Scaling, Contrast Limited Adaptive Histogram Equalization, then the image being classified with Convolutional Neural Network. The result then showed that the method significantly conducted was able to be used as a tool to classify stroke disease in order to distinguish the type of stroke from CT image.
WE-G-209-01: Digital Radiography
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schueler, B.
Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This coursemore » will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.« less
NASA Astrophysics Data System (ADS)
Reilly, B. T.; Stoner, J. S.; Wiest, J.
2017-08-01
Computed tomography (CT) of sediment cores allows for high-resolution images, three-dimensional volumes, and down core profiles. These quantitative data are generated through the attenuation of X-rays, which are sensitive to sediment density and atomic number, and are stored in pixels as relative gray scale values or Hounsfield units (HU). We present a suite of MATLAB™ tools specifically designed for routine sediment core analysis as a means to standardize and better quantify the products of CT data collected on medical CT scanners. SedCT uses a graphical interface to process Digital Imaging and Communications in Medicine (DICOM) files, stitch overlapping scanned intervals, and create down core HU profiles in a manner robust to normal coring imperfections. Utilizing a random sampling technique, SedCT reduces data size and allows for quick processing on typical laptop computers. SedCTimage uses a graphical interface to create quality tiff files of CT slices that are scaled to a user-defined HU range, preserving the quantitative nature of CT images and easily allowing for comparison between sediment cores with different HU means and variance. These tools are presented along with examples from lacustrine and marine sediment cores to highlight the robustness and quantitative nature of this method.
Automated extraction of radiation dose information from CT dose report images.
Li, Xinhua; Zhang, Da; Liu, Bob
2011-06-01
The purpose of this article is to describe the development of an automated tool for retrieving texts from CT dose report images. Optical character recognition was adopted to perform text recognitions of CT dose report images. The developed tool is able to automate the process of analyzing multiple CT examinations, including text recognition, parsing, error correction, and exporting data to spreadsheets. The results were precise for total dose-length product (DLP) and were about 95% accurate for CT dose index and DLP of scanned series.
An approach for quantitative image quality analysis for CT
NASA Astrophysics Data System (ADS)
Rahimi, Amir; Cochran, Joe; Mooney, Doug; Regensburger, Joe
2016-03-01
An objective and standardized approach to assess image quality of Compute Tomography (CT) systems is required in a wide variety of imaging processes to identify CT systems appropriate for a given application. We present an overview of the framework we have developed to help standardize and to objectively assess CT image quality for different models of CT scanners used for security applications. Within this framework, we have developed methods to quantitatively measure metrics that should correlate with feature identification, detection accuracy and precision, and image registration capabilities of CT machines and to identify strengths and weaknesses in different CT imaging technologies in transportation security. To that end we have designed, developed and constructed phantoms that allow for systematic and repeatable measurements of roughly 88 image quality metrics, representing modulation transfer function, noise equivalent quanta, noise power spectra, slice sensitivity profiles, streak artifacts, CT number uniformity, CT number consistency, object length accuracy, CT number path length consistency, and object registration. Furthermore, we have developed a sophisticated MATLAB based image analysis tool kit to analyze CT generated images of phantoms and report these metrics in a format that is standardized across the considered models of CT scanners, allowing for comparative image quality analysis within a CT model or between different CT models. In addition, we have developed a modified sparse principal component analysis (SPCA) method to generate a modified set of PCA components as compared to the standard principal component analysis (PCA) with sparse loadings in conjunction with Hotelling T2 statistical analysis method to compare, qualify, and detect faults in the tested systems.
Dual-Energy CT: New Horizon in Medical Imaging
Goo, Jin Mo
2017-01-01
Dual-energy CT has remained underutilized over the past decade probably due to a cumbersome workflow issue and current technical limitations. Clinical radiologists should be made aware of the potential clinical benefits of dual-energy CT over single-energy CT. To accomplish this aim, the basic principle, current acquisition methods with advantages and disadvantages, and various material-specific imaging methods as clinical applications of dual-energy CT should be addressed in detail. Current dual-energy CT acquisition methods include dual tubes with or without beam filtration, rapid voltage switching, dual-layer detector, split filter technique, and sequential scanning. Dual-energy material-specific imaging methods include virtual monoenergetic or monochromatic imaging, effective atomic number map, virtual non-contrast or unenhanced imaging, virtual non-calcium imaging, iodine map, inhaled xenon map, uric acid imaging, automatic bone removal, and lung vessels analysis. In this review, we focus on dual-energy CT imaging including related issues of radiation exposure to patients, scanning and post-processing options, and potential clinical benefits mainly to improve the understanding of clinical radiologists and thus, expand the clinical use of dual-energy CT; in addition, we briefly describe the current technical limitations of dual-energy CT and the current developments of photon-counting detector. PMID:28670151
Kashiwagi, Toru; Yutani, Kenji; Fukuchi, Minoru; Naruse, Hitoshi; Iwasaki, Tadaaki; Yokozuka, Koichi; Inoue, Shinichi; Kondo, Shoji
2002-06-01
Improvements in image quality and quantitation measurement, and the addition of detailed anatomical structures are important topics for single-photon emission tomography (SPECT). The goal of this study was to develop a practical system enabling both nonuniform attenuation correction and image fusion of SPECT images by means of high-performance X-ray computed tomography (CT). A SPECT system and a helical X-ray CT system were placed next to each other and linked with Ethernet. To avoid positional differences between the SPECT and X-ray CT studies, identical flat patient tables were used for both scans; body distortion was minimized with laser beams from the upper and lateral directions to detect the position of the skin surface. For the raw projection data of SPECT, a scatter correction was performed with the triple energy window method. Image fusion of the X-ray CT and SPECT images was performed automatically by auto-registration of fiducial markers attached to the skin surface. After registration of the X-ray CT and SPECT images, an X-ray CT-derived attenuation map was created with the calibration curve for 99mTc. The SPECT images were then reconstructed with scatter and attenuation correction by means of a maximum likelihood expectation maximization algorithm. This system was evaluated in torso and cylindlical phantoms and in 4 patients referred for myocardial SPECT imaging with Tc-99m tetrofosmin. In the torso phantom study, the SPECT and X-ray CT images overlapped exactly on the computer display. After scatter and attenuation correction, the artifactual activity reduction in the inferior wall of the myocardium improved. Conversely, the incresed activity around the torso surface and the lungs was reduced. In the abdomen, the liver activity, which was originally uniform, had recovered after scatter and attenuation correction processing. The clinical study also showed good overlapping of cardiac and skin surface outlines on the fused SPECT and X-ray CT images. The effectiveness of the scatter and attenuation correction process was similar to that observed in the phantom study. Because the total time required for computer processing was less than 10 minutes, this method of attenuation correction and image fusion for SPECT images is expected to become popular in clinical practice.
Computer system for definition of the quantitative geometry of musculature from CT images.
Daniel, Matej; Iglic, Ales; Kralj-Iglic, Veronika; Konvicková, Svatava
2005-02-01
The computer system for quantitative determination of musculoskeletal geometry from computer tomography (CT) images has been developed. The computer system processes series of CT images to obtain three-dimensional (3D) model of bony structures where the effective muscle fibres can be interactively defined. Presented computer system has flexible modular structure and is suitable also for educational purposes.
Prior image constrained image reconstruction in emerging computed tomography applications
NASA Astrophysics Data System (ADS)
Brunner, Stephen T.
Advances have been made in computed tomography (CT), especially in the past five years, by incorporating prior images into the image reconstruction process. In this dissertation, we investigate prior image constrained image reconstruction in three emerging CT applications: dual-energy CT, multi-energy photon-counting CT, and cone-beam CT in image-guided radiation therapy. First, we investigate the application of Prior Image Constrained Compressed Sensing (PICCS) in dual-energy CT, which has been called "one of the hottest research areas in CT." Phantom and animal studies are conducted using a state-of-the-art 64-slice GE Discovery 750 HD CT scanner to investigate the extent to which PICCS can enable radiation dose reduction in material density and virtual monochromatic imaging. Second, we extend the application of PICCS from dual-energy CT to multi-energy photon-counting CT, which has been called "one of the 12 topics in CT to be critical in the next decade." Numerical simulations are conducted to generate multiple energy bin images for a photon-counting CT acquisition and to investigate the extent to which PICCS can enable radiation dose efficiency improvement. Third, we investigate the performance of a newly proposed prior image constrained scatter correction technique to correct scatter-induced shading artifacts in cone-beam CT, which, when used in image-guided radiation therapy procedures, can assist in patient localization, and potentially, dose verification and adaptive radiation therapy. Phantom studies are conducted using a Varian 2100 EX system with an on-board imager to investigate the extent to which the prior image constrained scatter correction technique can mitigate scatter-induced shading artifacts in cone-beam CT. Results show that these prior image constrained image reconstruction techniques can reduce radiation dose in dual-energy CT by 50% in phantom and animal studies in material density and virtual monochromatic imaging, can lead to radiation dose efficiency improvement in multi-energy photon-counting CT, and can mitigate scatter-induced shading artifacts in cone-beam CT in full-fan and half-fan modes.
SU-E-T-04: 3D Dose Based Patient Compensator QA Procedure for Proton Radiotherapy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zou, W; Reyhan, M; Zhang, M
2015-06-15
Purpose: In proton double-scattering radiotherapy, compensators are the essential patient specific devices to contour the distal dose distribution to the tumor target. Traditional compensator QA is limited to checking the drilled surface profiles against the plan. In our work, a compensator QA process was established that assess the entire compensator including its internal structure for patient 3D dose verification. Methods: The fabricated patient compensators were CT scanned. Through mathematical image processing and geometric transformations, the CT images of the proton compensator were combined with the patient simulation CT images into a new series of CT images, in which the imagedmore » compensator is placed at the planned location along the corresponding beam line. The new CT images were input into the Eclipse treatment planning system. The original plan was calculated to the combined CT image series without the plan compensator. The newly computed patient 3D dose from the combined patientcompensator images was verified against the original plan dose. Test plans include the compensators with defects intentionally created inside the fabricated compensators. Results: The calculated 3D dose with the combined compensator and patient CT images reflects the impact of the fabricated compensator to the patient. For the test cases in which no defects were created, the dose distributions were in agreement between our method and the corresponding original plans. For the compensator with the defects, the purposely changed material and a purposely created internal defect were successfully detected while not possible with just the traditional compensator profiles detection methods. Conclusion: We present here a 3D dose verification process to qualify the fabricated proton double-scattering compensator. Such compensator detection process assesses the patient 3D impact of the fabricated compensator surface profile as well as the compensator internal material and structure changes. This research receives funding support from CURA Medical Technologies.« less
A minimum spanning forest based classification method for dedicated breast CT images
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pike, Robert; Sechopoulos, Ioannis; Fei, Baowei, E-mail: bfei@emory.edu
Purpose: To develop and test an automated algorithm to classify different types of tissue in dedicated breast CT images. Methods: Images of a single breast of five different patients were acquired with a dedicated breast CT clinical prototype. The breast CT images were processed by a multiscale bilateral filter to reduce noise while keeping edge information and were corrected to overcome cupping artifacts. As skin and glandular tissue have similar CT values on breast CT images, morphologic processing is used to identify the skin based on its position information. A support vector machine (SVM) is trained and the resulting modelmore » used to create a pixelwise classification map of fat and glandular tissue. By combining the results of the skin mask with the SVM results, the breast tissue is classified as skin, fat, and glandular tissue. This map is then used to identify markers for a minimum spanning forest that is grown to segment the image using spatial and intensity information. To evaluate the authors’ classification method, they use DICE overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on five patient images. Results: Comparison between the automatic and the manual segmentation shows that the minimum spanning forest based classification method was able to successfully classify dedicated breast CT image with average DICE ratios of 96.9%, 89.8%, and 89.5% for fat, glandular, and skin tissue, respectively. Conclusions: A 2D minimum spanning forest based classification method was proposed and evaluated for classifying the fat, skin, and glandular tissue in dedicated breast CT images. The classification method can be used for dense breast tissue quantification, radiation dose assessment, and other applications in breast imaging.« less
Pandey, Anil Kumar; Saroha, Kartik; Sharma, Param Dev; Patel, Chetan; Bal, Chandrashekhar; Kumar, Rakesh
2017-01-01
In this study, we have developed a simple image processing application in MATLAB that uses suprathreshold stochastic resonance (SSR) and helps the user to visualize abdominopelvic tumor on the exported prediuretic positron emission tomography/computed tomography (PET/CT) images. A brainstorming session was conducted for requirement analysis for the program. It was decided that program should load the screen captured PET/CT images and then produces output images in a window with a slider control that should enable the user to view the best image that visualizes the tumor, if present. The program was implemented on personal computer using Microsoft Windows and MATLAB R2013b. The program has option for the user to select the input image. For the selected image, it displays output images generated using SSR in a separate window having a slider control. The slider control enables the user to view images and select one which seems to provide the best visualization of the area(s) of interest. The developed application enables the user to select, process, and view output images in the process of utilizing SSR to detect the presence of abdominopelvic tumor on prediuretic PET/CT image.
A combined learning algorithm for prostate segmentation on 3D CT images.
Ma, Ling; Guo, Rongrong; Zhang, Guoyi; Schuster, David M; Fei, Baowei
2017-11-01
Segmentation of the prostate on CT images has many applications in the diagnosis and treatment of prostate cancer. Because of the low soft-tissue contrast on CT images, prostate segmentation is a challenging task. A learning-based segmentation method is proposed for the prostate on three-dimensional (3D) CT images. We combine population-based and patient-based learning methods for segmenting the prostate on CT images. Population data can provide useful information to guide the segmentation processing. Because of inter-patient variations, patient-specific information is particularly useful to improve the segmentation accuracy for an individual patient. In this study, we combine a population learning method and a patient-specific learning method to improve the robustness of prostate segmentation on CT images. We train a population model based on the data from a group of prostate patients. We also train a patient-specific model based on the data of the individual patient and incorporate the information as marked by the user interaction into the segmentation processing. We calculate the similarity between the two models to obtain applicable population and patient-specific knowledge to compute the likelihood of a pixel belonging to the prostate tissue. A new adaptive threshold method is developed to convert the likelihood image into a binary image of the prostate, and thus complete the segmentation of the gland on CT images. The proposed learning-based segmentation algorithm was validated using 3D CT volumes of 92 patients. All of the CT image volumes were manually segmented independently three times by two, clinically experienced radiologists and the manual segmentation results served as the gold standard for evaluation. The experimental results show that the segmentation method achieved a Dice similarity coefficient of 87.18 ± 2.99%, compared to the manual segmentation. By combining the population learning and patient-specific learning methods, the proposed method is effective for segmenting the prostate on 3D CT images. The prostate CT segmentation method can be used in various applications including volume measurement and treatment planning of the prostate. © 2017 American Association of Physicists in Medicine.
Iterative CT shading correction with no prior information
NASA Astrophysics Data System (ADS)
Wu, Pengwei; Sun, Xiaonan; Hu, Hongjie; Mao, Tingyu; Zhao, Wei; Sheng, Ke; Cheung, Alice A.; Niu, Tianye
2015-11-01
Shading artifacts in CT images are caused by scatter contamination, beam-hardening effect and other non-ideal imaging conditions. The purpose of this study is to propose a novel and general correction framework to eliminate low-frequency shading artifacts in CT images (e.g. cone-beam CT, low-kVp CT) without relying on prior information. The method is based on the general knowledge of the relatively uniform CT number distribution in one tissue component. The CT image is first segmented to construct a template image where each structure is filled with the same CT number of a specific tissue type. Then, by subtracting the ideal template from the CT image, the residual image from various error sources are generated. Since forward projection is an integration process, non-continuous shading artifacts in the image become continuous signals in a line integral. Thus, the residual image is forward projected and its line integral is low-pass filtered in order to estimate the error that causes shading artifacts. A compensation map is reconstructed from the filtered line integral error using a standard FDK algorithm and added back to the original image for shading correction. As the segmented image does not accurately depict a shaded CT image, the proposed scheme is iterated until the variation of the residual image is minimized. The proposed method is evaluated using cone-beam CT images of a Catphan©600 phantom and a pelvis patient, and low-kVp CT angiography images for carotid artery assessment. Compared with the CT image without correction, the proposed method reduces the overall CT number error from over 200 HU to be less than 30 HU and increases the spatial uniformity by a factor of 1.5. Low-contrast object is faithfully retained after the proposed correction. An effective iterative algorithm for shading correction in CT imaging is proposed that is only assisted by general anatomical information without relying on prior knowledge. The proposed method is thus practical and attractive as a general solution to CT shading correction.
Umehara, Kensuke; Ota, Junko; Ishida, Takayuki
2017-10-18
In this study, the super-resolution convolutional neural network (SRCNN) scheme, which is the emerging deep-learning-based super-resolution method for enhancing image resolution in chest CT images, was applied and evaluated using the post-processing approach. For evaluation, 89 chest CT cases were sampled from The Cancer Imaging Archive. The 89 CT cases were divided randomly into 45 training cases and 44 external test cases. The SRCNN was trained using the training dataset. With the trained SRCNN, a high-resolution image was reconstructed from a low-resolution image, which was down-sampled from an original test image. For quantitative evaluation, two image quality metrics were measured and compared to those of the conventional linear interpolation methods. The image restoration quality of the SRCNN scheme was significantly higher than that of the linear interpolation methods (p < 0.001 or p < 0.05). The high-resolution image reconstructed by the SRCNN scheme was highly restored and comparable to the original reference image, in particular, for a ×2 magnification. These results indicate that the SRCNN scheme significantly outperforms the linear interpolation methods for enhancing image resolution in chest CT images. The results also suggest that SRCNN may become a potential solution for generating high-resolution CT images from standard CT images.
[Application of computed tomography (CT) examination for forensic medicine].
Urbanik, Andrzej; Chrzan, Robert
2013-01-01
The aim of the study is to present a own experiences in usage of post mortem CT examination for forensic medicine. With the help of 16-slice CT scanner 181 corpses were examined. Obtained during acquisition imaging data are later developed with dedicated programmes. Analyzed images were extracted from axial sections, multiplanar reconstructions as well as 3D reconstructions. Gained information helped greatly when classical autopsy was performed by making it more accurate. A CT scan images recorded digitally enable to evaluate corpses at any time, despite processes of putrefaction or cremation. If possible CT examination should precede classical autopsy.
Automatic anatomy recognition in whole-body PET/CT images
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Huiqian; Udupa, Jayaram K., E-mail: jay@mail.med.upenn.edu; Odhner, Dewey
Purpose: Whole-body positron emission tomography/computed tomography (PET/CT) has become a standard method of imaging patients with various disease conditions, especially cancer. Body-wide accurate quantification of disease burden in PET/CT images is important for characterizing lesions, staging disease, prognosticating patient outcome, planning treatment, and evaluating disease response to therapeutic interventions. However, body-wide anatomy recognition in PET/CT is a critical first step for accurately and automatically quantifying disease body-wide, body-region-wise, and organwise. This latter process, however, has remained a challenge due to the lower quality of the anatomic information portrayed in the CT component of this imaging modality and the paucity ofmore » anatomic details in the PET component. In this paper, the authors demonstrate the adaptation of a recently developed automatic anatomy recognition (AAR) methodology [Udupa et al., “Body-wide hierarchical fuzzy modeling, recognition, and delineation of anatomy in medical images,” Med. Image Anal. 18, 752–771 (2014)] to PET/CT images. Their goal was to test what level of object localization accuracy can be achieved on PET/CT compared to that achieved on diagnostic CT images. Methods: The authors advance the AAR approach in this work in three fronts: (i) from body-region-wise treatment in the work of Udupa et al. to whole body; (ii) from the use of image intensity in optimal object recognition in the work of Udupa et al. to intensity plus object-specific texture properties, and (iii) from the intramodality model-building-recognition strategy to the intermodality approach. The whole-body approach allows consideration of relationships among objects in different body regions, which was previously not possible. Consideration of object texture allows generalizing the previous optimal threshold-based fuzzy model recognition method from intensity images to any derived fuzzy membership image, and in the process, to bring performance to the level achieved on diagnostic CT and MR images in body-region-wise approaches. The intermodality approach fosters the use of already existing fuzzy models, previously created from diagnostic CT images, on PET/CT and other derived images, thus truly separating the modality-independent object assembly anatomy from modality-specific tissue property portrayal in the image. Results: Key ways of combining the above three basic ideas lead them to 15 different strategies for recognizing objects in PET/CT images. Utilizing 50 diagnostic CT image data sets from the thoracic and abdominal body regions and 16 whole-body PET/CT image data sets, the authors compare the recognition performance among these 15 strategies on 18 objects from the thorax, abdomen, and pelvis in object localization error and size estimation error. Particularly on texture membership images, object localization is within three voxels on whole-body low-dose CT images and 2 voxels on body-region-wise low-dose images of known true locations. Surprisingly, even on direct body-region-wise PET images, localization error within 3 voxels seems possible. Conclusions: The previous body-region-wise approach can be extended to whole-body torso with similar object localization performance. Combined use of image texture and intensity property yields the best object localization accuracy. In both body-region-wise and whole-body approaches, recognition performance on low-dose CT images reaches levels previously achieved on diagnostic CT images. The best object recognition strategy varies among objects; the proposed framework however allows employing a strategy that is optimal for each object.« less
Image processing based detection of lung cancer on CT scan images
NASA Astrophysics Data System (ADS)
Abdillah, Bariqi; Bustamam, Alhadi; Sarwinda, Devvi
2017-10-01
In this paper, we implement and analyze the image processing method for detection of lung cancer. Image processing techniques are widely used in several medical problems for picture enhancement in the detection phase to support the early medical treatment. In this research we proposed a detection method of lung cancer based on image segmentation. Image segmentation is one of intermediate level in image processing. Marker control watershed and region growing approach are used to segment of CT scan image. Detection phases are followed by image enhancement using Gabor filter, image segmentation, and features extraction. From the experimental results, we found the effectiveness of our approach. The results show that the best approach for main features detection is watershed with masking method which has high accuracy and robust.
Optimization of oncological {sup 18}F-FDG PET/CT imaging based on a multiparameter analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Menezes, Vinicius O., E-mail: vinicius@radtec.com.br; Machado, Marcos A. D.; Queiroz, Cleiton C.
2016-02-15
Purpose: This paper describes a method to achieve consistent clinical image quality in {sup 18}F-FDG scans accounting for patient habitus, dose regimen, image acquisition, and processing techniques. Methods: Oncological PET/CT scan data for 58 subjects were evaluated retrospectively to derive analytical curves that predict image quality. Patient noise equivalent count rate and coefficient of variation (CV) were used as metrics in their analysis. Optimized acquisition protocols were identified and prospectively applied to 179 subjects. Results: The adoption of different schemes for three body mass ranges (<60 kg, 60–90 kg, >90 kg) allows improved image quality with both point spread functionmore » and ordered-subsets expectation maximization-3D reconstruction methods. The application of this methodology showed that CV improved significantly (p < 0.0001) in clinical practice. Conclusions: Consistent oncological PET/CT image quality on a high-performance scanner was achieved from an analysis of the relations existing between dose regimen, patient habitus, acquisition, and processing techniques. The proposed methodology may be used by PET/CT centers to develop protocols to standardize PET/CT imaging procedures and achieve better patient management and cost-effective operations.« less
Histogram-driven cupping correction (HDCC) in CT
NASA Astrophysics Data System (ADS)
Kyriakou, Y.; Meyer, M.; Lapp, R.; Kalender, W. A.
2010-04-01
Typical cupping correction methods are pre-processing methods which require either pre-calibration measurements or simulations of standard objects to approximate and correct for beam hardening and scatter. Some of them require the knowledge of spectra, detector characteristics, etc. The aim of this work was to develop a practical histogram-driven cupping correction (HDCC) method to post-process the reconstructed images. We use a polynomial representation of the raw-data generated by forward projection of the reconstructed images; forward and backprojection are performed on graphics processing units (GPU). The coefficients of the polynomial are optimized using a simplex minimization of the joint entropy of the CT image and its gradient. The algorithm was evaluated using simulations and measurements of homogeneous and inhomogeneous phantoms. For the measurements a C-arm flat-detector CT (FD-CT) system with a 30×40 cm2 detector, a kilovoltage on board imager (radiation therapy simulator) and a micro-CT system were used. The algorithm reduced cupping artifacts both in simulations and measurements using a fourth-order polynomial and was in good agreement to the reference. The minimization algorithm required less than 70 iterations to adjust the coefficients only performing a linear combination of basis images, thus executing without time consuming operations. HDCC reduced cupping artifacts without the necessity of pre-calibration or other scan information enabling a retrospective improvement of CT image homogeneity. However, the method can work with other cupping correction algorithms or in a calibration manner, as well.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cline, K; Narayanasamy, G; Obediat, M
Purpose: Deformable image registration (DIR) is used routinely in the clinic without a formalized quality assurance (QA) process. Using simulated deformations to digitally deform images in a known way and comparing to DIR algorithm predictions is a powerful technique for DIR QA. This technique must also simulate realistic image noise and artifacts, especially between modalities. This study developed an algorithm to create simulated daily kV cone-beam computed-tomography (CBCT) images from CT images for DIR QA between these modalities. Methods: A Catphan and physical head-and-neck phantom, with known deformations, were used. CT and kV-CBCT images of the Catphan were utilized tomore » characterize the changes in Hounsfield units, noise, and image cupping that occur between these imaging modalities. The algorithm then imprinted these changes onto a CT image of the deformed head-and-neck phantom, thereby creating a simulated-CBCT image. CT and kV-CBCT images of the undeformed and deformed head-and-neck phantom were also acquired. The Velocity and MIM DIR algorithms were applied between the undeformed CT image and each of the deformed CT, CBCT, and simulated-CBCT images to obtain predicted deformations. The error between the known and predicted deformations was used as a metric to evaluate the quality of the simulated-CBCT image. Ideally, the simulated-CBCT image registration would produce the same accuracy as the deformed CBCT image registration. Results: For Velocity, the mean error was 1.4 mm for the CT-CT registration, 1.7 mm for the CT-CBCT registration, and 1.4 mm for the CT-simulated-CBCT registration. These same numbers were 1.5, 4.5, and 5.9 mm, respectively, for MIM. Conclusion: All cases produced similar accuracy for Velocity. MIM produced similar values of accuracy for CT-CT registration, but was not as accurate for CT-CBCT registrations. The MIM simulated-CBCT registration followed this same trend, but overestimated MIM DIR errors relative to the CT-CBCT registration.« less
Dos Santos, Denise Takehana; Costa e Silva, Adriana Paula Andrade; Vannier, Michael Walter; Cavalcanti, Marcelo Gusmão Paraiso
2004-12-01
The purpose of this study was to demonstrate the sensitivity and specificity of multislice computerized tomography (CT) for diagnosis of maxillofacial fractures following specific protocols using an independent workstation. The study population consisted of 56 patients with maxillofacial fractures who were submitted to a multislice CT. The original data were transferred to an independent workstation using volumetric imaging software to generate axial images and simultaneous multiplanar (MPR) and 3-dimensional (3D-CT) volume rendering reconstructed images. The images were then processed and interpreted by 2 examiners using the following protocols independently of each other: axial, MPR/axial, 3D-CT images, and the association of axial/MPR/3D images. The clinical/surgical findings were considered the gold standard corroborating the diagnosis of the fractures and their anatomic localization. The statistical analysis was carried out using validity and chi-squared tests. The association of axial/MPR/3D images indicated a higher sensitivity (range 95.8%) and specificity (range 99%) than the other methods regarding the analysis of all regions. CT imaging demonstrated high specificity and sensitivity for maxillofacial fractures. The association of axial/MPR/3D-CT images added important information in relationship to other CT protocols.
CT radiation profile width measurement using CR imaging plate raw data
Yang, Chang‐Ying Joseph
2015-01-01
This technical note demonstrates computed tomography (CT) radiation profile measurement using computed radiography (CR) imaging plate raw data showing it is possible to perform the CT collimation width measurement using a single scan without saturating the imaging plate. Previously described methods require careful adjustments to the CR reader settings in order to avoid signal clipping in the CR processed image. CT radiation profile measurements were taken as part of routine quality control on 14 CT scanners from four vendors. CR cassettes were placed on the CT scanner bed, raised to isocenter, and leveled. Axial scans were taken at all available collimations, advancing the cassette for each scan. The CR plates were processed and raw CR data were analyzed using MATLAB scripts to measure collimation widths. The raw data approach was compared with previously established methodology. The quality control analysis scripts are released as open source using creative commons licensing. A log‐linear relationship was found between raw pixel value and air kerma, and raw data collimation width measurements were in agreement with CR‐processed, bit‐reduced data, using previously described methodology. The raw data approach, with intrinsically wider dynamic range, allows improved measurement flexibility and precision. As a result, we demonstrate a methodology for CT collimation width measurements using a single CT scan and without the need for CR scanning parameter adjustments which is more convenient for routine quality control work. PACS numbers: 87.57.Q‐, 87.59.bd, 87.57.uq PMID:26699559
PET/CT (and CT) instrumentation, image reconstruction and data transfer for radiotherapy planning.
Sattler, Bernhard; Lee, John A; Lonsdale, Markus; Coche, Emmanuel
2010-09-01
The positron emission tomography in combination with CT in hybrid, cross-modality imaging systems (PET/CT) gains more and more importance as a part of the treatment-planning procedure in radiotherapy. Positron emission tomography (PET), as a integral part of nuclear medicine imaging and non-invasive imaging technique, offers the visualization and quantification of pre-selected tracer metabolism. In combination with the structural information from CT, this molecular imaging technique has great potential to support and improve the outcome of the treatment-planning procedure prior to radiotherapy. By the choice of the PET-Tracer, a variety of different metabolic processes can be visualized. First and foremost, this is the glucose metabolism of a tissue as well as for instance hypoxia or cell proliferation. This paper comprises the system characteristics of hybrid PET/CT systems. Acquisition and processing protocols are described in general and modifications to cope with the special needs in radiooncology. This starts with the different position of the patient on a special table top, continues with the use of the same fixation material as used for positioning of the patient in radiooncology while simulation and irradiation and leads to special processing protocols that include the delineation of the volumes that are subject to treatment planning and irradiation (PTV, GTV, CTV, etc.). General CT acquisition and processing parameters as well as the use of contrast enhancement of the CT are described. The possible risks and pitfalls the investigator could face during the hybrid-imaging procedure are explained and listed. The interdisciplinary use of different imaging modalities implies a increase of the volume of data created. These data need to be stored and communicated fast, safe and correct. Therefore, the DICOM-Standard provides objects and classes for this purpose (DICOM RT). Furthermore, the standard DICOM objects and classes for nuclear medicine (NM, PT) and computed tomography (CT) are used to communicate the actual image data created by the modalities. Care must be taken for data security, especially when transferring data across the (network-) borders of different hospitals. Overall, the most important precondition for successful integration of functional imaging in RT treatment planning is the goal orientated as well as close and thorough communication between nuclear medicine and radiotherapy departments on all levels of interaction (personnel, imaging protocols, GTV delineation, and selection of the data transfer method). Copyright 2010 European Society for Therapeutic Radiology and Oncology and European Association of Nuclear Medicine. Published by Elsevier Ireland Ltd.. All rights reserved.
Image Processing and Computer Aided Diagnosis in Computed Tomography of the Breast
2007-03-01
TERMS breast imaging, breast CT, scatter compensation, denoising, CAD , Cone-beam CT 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF...clinical projection images. The CAD tool based on signal known exactly (SKE) scenario is under development. Task 6: Test and compare the...performances of the CAD developed in Task 5 applied to processed projection data from Task 1 with the CAD performance on the projection data without Bayesian
Larson, David B; Malarik, Remo J; Hall, Seth M; Podberesky, Daniel J
2013-10-01
To evaluate the effect of an automated computed tomography (CT) radiation dose optimization and process control system on the consistency of estimated image noise and size-specific dose estimates (SSDEs) of radiation in CT examinations of the chest, abdomen, and pelvis. This quality improvement project was determined not to constitute human subject research. An automated system was developed to analyze each examination immediately after completion, and to report individual axial-image-level and study-level summary data for patient size, image noise, and SSDE. The system acquired data for 4 months beginning October 1, 2011. Protocol changes were made by using parameters recommended by the prediction application, and 3 months of additional data were acquired. Preimplementation and postimplementation mean image noise and SSDE were compared by using unpaired t tests and F tests. Common-cause variation was differentiated from special-cause variation by using a statistical process control individual chart. A total of 817 CT examinations, 490 acquired before and 327 acquired after the initial protocol changes, were included in the study. Mean patient age and water-equivalent diameter were 12.0 years and 23.0 cm, respectively. The difference between actual and target noise increased from -1.4 to 0.3 HU (P < .01) and the standard deviation decreased from 3.9 to 1.6 HU (P < .01). Mean SSDE decreased from 11.9 to 7.5 mGy, a 37% reduction (P < .01). The process control chart identified several special causes of variation. Implementation of an automated CT radiation dose optimization system led to verifiable simultaneous decrease in image noise variation and SSDE. The automated nature of the system provides the opportunity for consistent CT radiation dose optimization on a broad scale. © RSNA, 2013.
Non-rigid CT/CBCT to CBCT registration for online external beam radiotherapy guidance
NASA Astrophysics Data System (ADS)
Zachiu, Cornel; de Senneville, Baudouin Denis; Tijssen, Rob H. N.; Kotte, Alexis N. T. J.; Houweling, Antonetta C.; Kerkmeijer, Linda G. W.; Lagendijk, Jan J. W.; Moonen, Chrit T. W.; Ries, Mario
2018-01-01
Image-guided external beam radiotherapy (EBRT) allows radiation dose deposition with a high degree of accuracy and precision. Guidance is usually achieved by estimating the displacements, via image registration, between cone beam computed tomography (CBCT) and computed tomography (CT) images acquired at different stages of the therapy. The resulting displacements are then used to reposition the patient such that the location of the tumor at the time of treatment matches its position during planning. Moreover, ongoing research aims to use CBCT-CT image registration for online plan adaptation. However, CBCT images are usually acquired using a small number of x-ray projections and/or low beam intensities. This often leads to the images being subject to low contrast, low signal-to-noise ratio and artifacts, which ends-up hampering the image registration process. Previous studies addressed this by integrating additional image processing steps into the registration procedure. However, these steps are usually designed for particular image acquisition schemes, therefore limiting their use on a case-by-case basis. In the current study we address CT to CBCT and CBCT to CBCT registration by the means of the recently proposed EVolution registration algorithm. Contrary to previous approaches, EVolution does not require the integration of additional image processing steps in the registration scheme. Moreover, the algorithm requires a low number of input parameters, is easily parallelizable and provides an elastic deformation on a point-by-point basis. Results have shown that relative to a pure CT-based registration, the intrinsic artifacts present in typical CBCT images only have a sub-millimeter impact on the accuracy and precision of the estimated deformation. In addition, the algorithm has low computational requirements, which are compatible with online image-based guidance of EBRT treatments.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Riegel, Adam C. B.A.; Chang, Joe Y.; Vedam, Sastry S.
2009-02-01
Purpose: To determine whether cine computed tomography (CT) can serve as an alternative to four-dimensional (4D)-CT by providing tumor motion information and producing equivalent target volumes when used to contour in radiotherapy planning without a respiratory surrogate. Methods and Materials: Cine CT images from a commercial CT scanner were used to form maximum intensity projection and respiratory-averaged CT image sets. These image sets then were used together to define the targets for radiotherapy. Phantoms oscillating under irregular motion were used to assess the differences between contouring using cine CT and 4D-CT. We also retrospectively reviewed the image sets for 26more » patients (27 lesions) at our institution who had undergone stereotactic radiotherapy for Stage I non-small-cell lung cancer. The patients were included if the tumor motion was >1 cm. The lesions were first contoured using maximum intensity projection and respiratory-averaged CT image sets processed from cine CT and then with 4D-CT maximum intensity projection and 10-phase image sets. The mean ratios of the volume magnitude were compared with intraobserver variation, the mean centroid shifts were calculated, and the volume overlap was assessed with the normalized Dice similarity coefficient index. Results: The phantom studies demonstrated that cine CT captured a greater extent of irregular tumor motion than did 4D-CT, producing a larger tumor volume. The patient studies demonstrated that the gross tumor defined using cine CT imaging was similar to, or slightly larger than, that defined using 4D-CT. Conclusion: The results of our study have shown that cine CT is a promising alternative to 4D-CT for stereotactic radiotherapy planning.« less
Development of a semi-automated combined PET and CT lung lesion segmentation framework
NASA Astrophysics Data System (ADS)
Rossi, Farli; Mokri, Siti Salasiah; Rahni, Ashrani Aizzuddin Abd.
2017-03-01
Segmentation is one of the most important steps in automated medical diagnosis applications, which affects the accuracy of the overall system. In this paper, we propose a semi-automated segmentation method for extracting lung lesions from thoracic PET/CT images by combining low level processing and active contour techniques. The lesions are first segmented in PET images which are first converted to standardised uptake values (SUVs). The segmented PET images then serve as an initial contour for subsequent active contour segmentation of corresponding CT images. To evaluate its accuracy, the Jaccard Index (JI) was used as a measure of the accuracy of the segmented lesion compared to alternative segmentations from the QIN lung CT segmentation challenge, which is possible by registering the whole body PET/CT images to the corresponding thoracic CT images. The results show that our proposed technique has acceptable accuracy in lung lesion segmentation with JI values of around 0.8, especially when considering the variability of the alternative segmentations.
Perz, Rafał; Toczyski, Jacek; Subit, Damien
2015-01-01
Computational models of the human body are commonly used for injury prediction in automobile safety research. To create these models, the geometry of the human body is typically obtained from segmentation of medical images such as computed tomography (CT) images that have a resolution between 0.2 and 1mm/pixel. While the accuracy of the geometrical and structural information obtained from these images depend greatly on their resolution, the effect of image resolution on the estimation of the ribs geometrical properties has yet to be established. To do so, each of the thirty-four sections of ribs obtained from a Post Mortem Human Surrogate (PMHS) was imaged using three different CT modalities: standard clinical CT (clinCT), high resolution clinical CT (HRclinCT), and microCT. The images were processed to estimate the rib cross-section geometry and mechanical properties, and the results were compared to those obtained from the microCT images by computing the 'deviation factor', a metric that quantifies the relative difference between results obtained from clinCT and HRclinCT to those obtained from microCT. Overall, clinCT images gave a deviation greater than 100%, and were therefore deemed inadequate for the purpose of this study. HRclinCT overestimated the rib cross-sectional area by 7.6%, the moments of inertia by about 50%, and the cortical shell area by 40.2%, while underestimating the trabecular area by 14.7%. Next, a parametric analysis was performed to quantify how the variations in the estimate of the geometrical properties affected the rib predicted mechanical response under antero-posterior loading. A variation of up to 45% for the predicted peak force and up to 50% for the predicted stiffness was observed. These results provide a quantitative estimate of the sensitivity of the response of the FE model to the resolution of the images used to generate it. They also suggest that a correction factor could be derived from the comparison between microCT and HRclinCT images to improve the response of the model developed based on HRclinCT images. Copyright © 2014 Elsevier Ltd. All rights reserved.
Deformable image registration for multimodal lung-cancer staging
NASA Astrophysics Data System (ADS)
Cheirsilp, Ronnarit; Zang, Xiaonan; Bascom, Rebecca; Allen, Thomas W.; Mahraj, Rickhesvar P. M.; Higgins, William E.
2016-03-01
Positron emission tomography (PET) and X-ray computed tomography (CT) serve as major diagnostic imaging modalities in the lung-cancer staging process. Modern scanners provide co-registered whole-body PET/CT studies, collected while the patient breathes freely, and high-resolution chest CT scans, collected under a brief patient breath hold. Unfortunately, no method exists for registering a PET/CT study into the space of a high-resolution chest CT scan. If this could be done, vital diagnostic information offered by the PET/CT study could be brought seamlessly into the procedure plan used during live cancer-staging bronchoscopy. We propose a method for the deformable registration of whole-body PET/CT data into the space of a high-resolution chest CT study. We then demonstrate its potential for procedure planning and subsequent use in multimodal image-guided bronchoscopy.
An evaluation on CT image acquisition method for medical VR applications
NASA Astrophysics Data System (ADS)
Jang, Seong-wook; Ko, Junho; Yoo, Yon-sik; Kim, Yoonsang
2017-02-01
Recent medical virtual reality (VR) applications to minimize re-operations are being studied for improvements in surgical efficiency and reduction of operation error. The CT image acquisition method considering three-dimensional (3D) modeling for medical VR applications is important, because the realistic model is required for the actual human organ. However, the research for medical VR applications has focused on 3D modeling techniques and utilized 3D models. In addition, research on a CT image acquisition method considering 3D modeling has never been reported. The conventional CT image acquisition method involves scanning a limited area of the lesion for the diagnosis of doctors once or twice. However, the medical VR application is required to acquire the CT image considering patients' various postures and a wider area than the lesion. A wider area than the lesion is required because of the necessary process of comparing bilateral sides for dyskinesia diagnosis of the shoulder, pelvis, and leg. Moreover, patients' various postures are required due to the different effects on the musculoskeletal system. Therefore, in this paper, we perform a comparative experiment on the acquired CT images considering image area (unilateral/bilateral) and patients' postures (neutral/abducted). CT images are acquired from 10 patients for the experiments, and the acquired CT images are evaluated based on the length per pixel and the morphological deviation. Finally, by comparing the experiment results, we evaluate the CT image acquisition method for medical VR applications.
CT Imaging, Data Reduction, and Visualization of Hardwood Logs
Daniel L. Schmoldt
1996-01-01
Computer tomography (CT) is a mathematical technique that, combined with noninvasive scanning such as x-ray imaging, has become a powerful tool to nondestructively test materials prior to use or to evaluate materials prior to processing. In the current context, hardwood lumber processing can benefit greatly by knowing what a log looks like prior to initial breakdown....
NASA Astrophysics Data System (ADS)
Hayashi, Tatsuro; Zhou, Xiangrong; Chen, Huayue; Hara, Takeshi; Miyamoto, Kei; Kobayashi, Tatsunori; Yokoyama, Ryujiro; Kanematsu, Masayuki; Hoshi, Hiroaki; Fujita, Hiroshi
2010-03-01
X-ray CT images have been widely used in clinical routine in recent years. CT images scanned by a modern CT scanner can show the details of various organs and tissues. This means various organs and tissues can be simultaneously interpreted on CT images. However, CT image interpretation requires a lot of time and energy. Therefore, support for interpreting CT images based on image-processing techniques is expected. The interpretation of the spinal curvature is important for clinicians because spinal curvature is associated with various spinal disorders. We propose a quantification scheme of the spinal curvature based on the center line of spinal canal on CT images. The proposed scheme consists of four steps: (1) Automated extraction of the skeletal region based on CT number thresholding. (2) Automated extraction of the center line of spinal canal. (3) Generation of the median plane image of spine, which is reformatted based on the spinal canal. (4) Quantification of the spinal curvature. The proposed scheme was applied to 10 cases, and compared with the Cobb angle that is commonly used by clinicians. We found that a high-correlation (for the 95% confidence interval, lumbar lordosis: 0.81-0.99) between values obtained by the proposed (vector) method and Cobb angle. Also, the proposed method can provide the reproducible result (inter- and intra-observer variability: within 2°). These experimental results suggested a possibility that the proposed method was efficient for quantifying the spinal curvature on CT images.
SU-C-9A-06: The Impact of CT Image Used for Attenuation Correction in 4D-PET
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cui, Y; Bowsher, J; Yan, S
2014-06-01
Purpose: To evaluate the appropriateness of using 3D non-gated CT image for attenuation correction (AC) in a 4D-PET (gated PET) imaging protocol used in radiotherapy treatment planning simulation. Methods: The 4D-PET imaging protocol in a Siemens PET/CT simulator (Biograph mCT, Siemens Medical Solutions, Hoffman Estates, IL) was evaluated. CIRS Dynamic Thorax Phantom (CIRS Inc., Norfolk, VA) with a moving glass sphere (8 mL) in the middle of its thorax portion was used in the experiments. The glass was filled with {sup 18}F-FDG and was in a longitudinal motion derived from a real patient breathing pattern. Varian RPM system (Varian Medicalmore » Systems, Palo Alto, CA) was used for respiratory gating. Both phase-gating and amplitude-gating methods were tested. The clinical imaging protocol was modified to use three different CT images for AC in 4D-PET reconstruction: first is to use a single-phase CT image to mimic actual clinical protocol (single-CT-PET); second is to use the average intensity projection CT (AveIP-CT) derived from 4D-CT scanning (AveIP-CT-PET); third is to use 4D-CT image to do the phase-matched AC (phase-matching- PET). Maximum SUV (SUVmax) and volume of the moving target (glass sphere) with threshold of 40% SUVmax were calculated for comparison between 4D-PET images derived with different AC methods. Results: The SUVmax varied 7.3%±6.9% over the breathing cycle in single-CT-PET, compared to 2.5%±2.8% in AveIP-CT-PET and 1.3%±1.2% in phasematching PET. The SUVmax in single-CT-PET differed by up to 15% from those in phase-matching-PET. The target volumes measured from single- CT-PET images also presented variations up to 10% among different phases of 4D PET in both phase-gating and amplitude-gating experiments. Conclusion: Attenuation correction using non-gated CT in 4D-PET imaging is not optimal process for quantitative analysis. Clinical 4D-PET imaging protocols should consider phase-matched 4D-CT image if available to achieve better accuracy.« less
Investigation of Carbon Fiber Architecture in Braided Composites Using X-Ray CT Inspection
NASA Technical Reports Server (NTRS)
Rhoads, Daniel J.; Miller, Sandi G.; Roberts, Gary D.; Rauser, Richard W.; Golovaty, Dmitry; Wilber, J. Patrick; Espanol, Malena I.
2017-01-01
During the fabrication of braided carbon fiber composite materials, process variations occur which affect the fiber architecture. Quantitative measurements of local and global fiber architecture variations are needed to determine the potential effect of process variations on mechanical properties of the cured composite. Although non-destructive inspection via X-ray CT imaging is a promising approach, difficulties in quantitative analysis of the data arise due to the similar densities of the material constituents. In an effort to gain more quantitative information about features related to fiber architecture, methods have been explored to improve the details that can be captured by X-ray CT imaging. Metal-coated fibers and thin veils are used as inserts to extract detailed information about fiber orientations and inter-ply behavior from X-ray CT images.
Acquiring 4D Thoracic CT Scans Using Ciné CT Acquisition
NASA Astrophysics Data System (ADS)
Low, Daniel
One method for acquiring 4D thoracic CT scans is to use ciné acquisition. Ciné acquisition is conducted by rotating the gantry and acquiring x-ray projections while keeping the couch stationary. After a complete rotation, a single set of CT slices, the number corresponding to the number of CT detector rows, is produced. The rotation period is typically sub second so each image set corresponds to a single point in time. The ciné image acquisition is repeated for at least one breathing cycle to acquire images throughout the breathing cycle. Once the images are acquired at a single couch position, the couch is moved to the abutting position and the acquisition is repeated. Post-processing of the images sets typically resorts the sets into breathing phases, stacking images from a specific phase to produce a thoracic CT scan at that phase. Benefits of the ciné acquisition protocol include, the ability to precisely identify the phase with respect to the acquired image, the ability to resort images after reconstruction, and the ability to acquire images over arbitrarily long times and for arbitrarily many images (within dose constraints).
Calibration free beam hardening correction for cardiac CT perfusion imaging
NASA Astrophysics Data System (ADS)
Levi, Jacob; Fahmi, Rachid; Eck, Brendan L.; Fares, Anas; Wu, Hao; Vembar, Mani; Dhanantwari, Amar; Bezerra, Hiram G.; Wilson, David L.
2016-03-01
Myocardial perfusion imaging using CT (MPI-CT) and coronary CTA have the potential to make CT an ideal noninvasive gate-keeper for invasive coronary angiography. However, beam hardening artifacts (BHA) prevent accurate blood flow calculation in MPI-CT. BH Correction (BHC) methods require either energy-sensitive CT, not widely available, or typically a calibration-based method. We developed a calibration-free, automatic BHC (ABHC) method suitable for MPI-CT. The algorithm works with any BHC method and iteratively determines model parameters using proposed BHA-specific cost function. In this work, we use the polynomial BHC extended to three materials. The image is segmented into soft tissue, bone, and iodine images, based on mean HU and temporal enhancement. Forward projections of bone and iodine images are obtained, and in each iteration polynomial correction is applied. Corrections are then back projected and combined to obtain the current iteration's BHC image. This process is iterated until cost is minimized. We evaluate the algorithm on simulated and physical phantom images and on preclinical MPI-CT data. The scans were obtained on a prototype spectral detector CT (SDCT) scanner (Philips Healthcare). Mono-energetic reconstructed images were used as the reference. In the simulated phantom, BH streak artifacts were reduced from 12+/-2HU to 1+/-1HU and cupping was reduced by 81%. Similarly, in physical phantom, BH streak artifacts were reduced from 48+/-6HU to 1+/-5HU and cupping was reduced by 86%. In preclinical MPI-CT images, BHA was reduced from 28+/-6 HU to less than 4+/-4HU at peak enhancement. Results suggest that the algorithm can be used to reduce BHA in conventional CT and improve MPI-CT accuracy.
A novel data processing technique for image reconstruction of penumbral imaging
NASA Astrophysics Data System (ADS)
Xie, Hongwei; Li, Hongyun; Xu, Zeping; Song, Guzhou; Zhang, Faqiang; Zhou, Lin
2011-06-01
CT image reconstruction technique was applied to the data processing of the penumbral imaging. Compared with other traditional processing techniques for penumbral coded pinhole image such as Wiener, Lucy-Richardson and blind technique, this approach is brand new. In this method, the coded aperture processing method was used for the first time independent to the point spread function of the image diagnostic system. In this way, the technical obstacles was overcome in the traditional coded pinhole image processing caused by the uncertainty of point spread function of the image diagnostic system. Then based on the theoretical study, the simulation of penumbral imaging and image reconstruction was carried out to provide fairly good results. While in the visible light experiment, the point source of light was used to irradiate a 5mm×5mm object after diffuse scattering and volume scattering. The penumbral imaging was made with aperture size of ~20mm. Finally, the CT image reconstruction technique was used for image reconstruction to provide a fairly good reconstruction result.
Combination of CT scanning and fluoroscopy imaging on a flat-panel CT scanner
NASA Astrophysics Data System (ADS)
Grasruck, M.; Gupta, R.; Reichardt, B.; Suess, Ch.; Schmidt, B.; Stierstorfer, K.; Popescu, S.; Brady, T.; Flohr, T.
2006-03-01
We developed and evaluated a prototype flat-panel detector based Volume CT (fpVCT) scanner. The fpVCT scanner consists of a Varian 4030CB a-Si flat-panel detector mounted in a multi slice CT-gantry (Siemens Medical Solutions). It provides a 25 cm field of view with 18 cm z-coverage at the isocenter. In addition to the standard tomographic scanning, fpVCT allows two new scan modes: (1) fluoroscopic imaging from any arbitrary rotation angle, and (2) continuous, time-resolved tomographic scanning of a dynamically changing viewing volume. Fluoroscopic imaging is feasible by modifying the standard CT gantry so that the imaging chain can be oriented along any user-selected rotation angle. Scanning with a stationary gantry, after it has been oriented, is equivalent to a conventional fluoroscopic examination. This scan mode enables combined use of high-resolution tomography and real-time fluoroscopy with a clinically usable field of view in the z direction. The second scan mode allows continuous observation of a timeevolving process such as perfusion. The gantry can be continuously rotated for up to 80 sec, with the rotation time ranging from 3 to 20 sec, to gather projection images of a dynamic process. The projection data, that provides a temporal log of the viewing volume, is then converted into multiple image stacks that capture the temporal evolution of a dynamic process. Studies using phantoms, ex vivo specimens, and live animals have confirmed that these new scanning modes are clinically usable and offer a unique view of the anatomy and physiology that heretofore has not been feasible using static CT scanning. At the current level of image quality and temporal resolution, several clinical applications such a dynamic angiography, tumor enhancement pattern and vascularity studies, organ perfusion, and interventional applications are in reach.
Automated measurements of metabolic tumor volume and metabolic parameters in lung PET/CT imaging
NASA Astrophysics Data System (ADS)
Orologas, F.; Saitis, P.; Kallergi, M.
2017-11-01
Patients with lung tumors or inflammatory lung disease could greatly benefit in terms of treatment and follow-up by PET/CT quantitative imaging, namely measurements of metabolic tumor volume (MTV), standardized uptake values (SUVs) and total lesion glycolysis (TLG). The purpose of this study was the development of an unsupervised or partially supervised algorithm using standard image processing tools for measuring MTV, SUV, and TLG from lung PET/CT scans. Automated metabolic lesion volume and metabolic parameter measurements were achieved through a 5 step algorithm: (i) The segmentation of the lung areas on the CT slices, (ii) the registration of the CT segmented lung regions on the PET images to define the anatomical boundaries of the lungs on the functional data, (iii) the segmentation of the regions of interest (ROIs) on the PET images based on adaptive thresholding and clinical criteria, (iv) the estimation of the number of pixels and pixel intensities in the PET slices of the segmented ROIs, (v) the estimation of MTV, SUVs, and TLG from the previous step and DICOM header data. Whole body PET/CT scans of patients with sarcoidosis were used for training and testing the algorithm. Lung area segmentation on the CT slices was better achieved with semi-supervised techniques that reduced false positive detections significantly. Lung segmentation results agreed with the lung volumes published in the literature while the agreement between experts and algorithm in the segmentation of the lesions was around 88%. Segmentation results depended on the image resolution selected for processing. The clinical parameters, SUV (either mean or max or peak) and TLG estimated by the segmented ROIs and DICOM header data provided a way to correlate imaging data to clinical and demographic data. In conclusion, automated MTV, SUV, and TLG measurements offer powerful analysis tools in PET/CT imaging of the lungs. Custom-made algorithms are often a better approach than the manufacturer’s general analysis software at much lower cost. Relatively simple processing techniques could lead to customized, unsupervised or partially supervised methods that can successfully perform the desirable analysis and adapt to the specific disease requirements.
NASA Astrophysics Data System (ADS)
Slot Thing, Rune; Bernchou, Uffe; Mainegra-Hing, Ernesto; Hansen, Olfred; Brink, Carsten
2016-08-01
A comprehensive artefact correction method for clinical cone beam CT (CBCT) images acquired for image guided radiation therapy (IGRT) on a commercial system is presented. The method is demonstrated to reduce artefacts and recover CT-like Hounsfield units (HU) in reconstructed CBCT images of five lung cancer patients. Projection image based artefact corrections of image lag, detector scatter, body scatter and beam hardening are described and applied to CBCT images of five lung cancer patients. Image quality is evaluated through visual appearance of the reconstructed images, HU-correspondence with the planning CT images, and total volume HU error. Artefacts are reduced and CT-like HUs are recovered in the artefact corrected CBCT images. Visual inspection confirms that artefacts are indeed suppressed by the proposed method, and the HU root mean square difference between reconstructed CBCTs and the reference CT images are reduced by 31% when using the artefact corrections compared to the standard clinical CBCT reconstruction. A versatile artefact correction method for clinical CBCT images acquired for IGRT has been developed. HU values are recovered in the corrected CBCT images. The proposed method relies on post processing of clinical projection images, and does not require patient specific optimisation. It is thus a powerful tool for image quality improvement of large numbers of CBCT images.
Shelmerdine, Susan C; Simcock, Ian C; Hutchinson, John Ciaran; Aughwane, Rosalind; Melbourne, Andrew; Nikitichev, Daniil I; Ong, Ju-Ling; Borghi, Alessandro; Cole, Garrard; Kingham, Emilia; Calder, Alistair D; Capelli, Claudio; Akhtar, Aadam; Cook, Andrew C; Schievano, Silvia; David, Anna; Ourselin, Sebastian; Sebire, Neil J; Arthurs, Owen J
2018-06-14
Microfocus CT (micro-CT) is an imaging method that provides three-dimensional digital data sets with comparable resolution to light microscopy. Although it has traditionally been used for non-destructive testing in engineering, aerospace industries and in preclinical animal studies, new applications are rapidly becoming available in the clinical setting including post-mortem fetal imaging and pathological specimen analysis. Printing three-dimensional models from imaging data sets for educational purposes is well established in the medical literature, but typically using low resolution (0.7 mm voxel size) data acquired from CT or MR examinations. With higher resolution imaging (voxel sizes below 1 micron, <0.001 mm) at micro-CT, smaller structures can be better characterised, and data sets post-processed to create accurate anatomical models for review and handling. In this review, we provide examples of how three-dimensional printing of micro-CT imaged specimens can provide insight into craniofacial surgical applications, developmental cardiac anatomy, placental imaging, archaeological remains and high-resolution bone imaging. We conclude with other potential future usages of this emerging technique.
Performance of hybrid system for fluorescence and micro-computed tomography in synchronous mode
NASA Astrophysics Data System (ADS)
Liu, Xin; Zhang, Yi; Liu, Fei; Guo, Xiaolian; Wang, Xin; Bai, Jing
2010-11-01
Fluorescence diffuse optical tomography (FDOT) plays an important role in studying physiological and pathological processes of small animals in vivo. The low spatial resolution, however, limits the ability of FDOT in resolving the biodistributions of fluorescent markers. The anatomical information provided by X-ray computed tomography (CT) can be used to improve the image quality of FDOT. However, in most hybrid FDOT/CT systems, the projection data sets of optics and X-ray are acquired sequentially, which increases the acquisition time and bring in the unwanted soft tissue displacement. In this paper, we evaluate the performance of a synchronous FDOT/CT system, which allows for faster and concurrent imaging. Compared with previous FDOT/CT systems, the two subsystems (FDOT and CT) acquire projection images in synchronous mode, so the body position can keep consistent in the same projection data acquired by both subsystems. The experimental results of phantom and in vivo experiments suggest that the reconstruction quality of FDOT can be significantly improved when structural a priori information is utilized to constrain the reconstruction process. On the other hand, the synchronous FDOT/CT system decreases the imaging time.
Automated Analysis of CT Images for the Inspection of Hardwood Logs
Harbin Li; A. Lynn Abbott; Daniel L. Schmoldt
1996-01-01
This paper investigates several classifiers for labeling internal features of hardwood logs using computed tomography (CT) images. A primary motivation is to locate and classify internal defects so that an optimal cutting strategy can be chosen. Previous work has relied on combinations of low-level processing, image segmentation, autoregressive texture modeling, and...
NASA Astrophysics Data System (ADS)
Zhou, X.; Hayashi, T.; Han, M.; Chen, H.; Hara, T.; Fujita, H.; Yokoyama, R.; Kanematsu, M.; Hoshi, H.
2009-02-01
X-ray CT images have been widely used in clinical diagnosis in recent years. A modern CT scanner can generate about 1000 CT slices to show the details of all the human organs within 30 seconds. However, CT image interpretations (viewing 500-1000 slices of CT images manually in front of a screen or films for each patient) require a lot of time and energy. Therefore, computer-aided diagnosis (CAD) systems that can support CT image interpretations are strongly anticipated. Automated recognition of the anatomical structures in CT images is a basic pre-processing of the CAD system. The bone structure is a part of anatomical structures and very useful to act as the landmarks for predictions of the other different organ positions. However, the automated recognition of the bone structure is still a challenging issue. This research proposes an automated scheme for segmenting the bone regions and recognizing the bone structure in noncontrast torso CT images. The proposed scheme was applied to 48 torso CT cases and a subjective evaluation for the experimental results was carried out by an anatomical expert following the anatomical definition. The experimental results showed that the bone structure in 90% CT cases have been recognized correctly. For quantitative evaluation, automated recognition results were compared to manual inputs of bones of lower limb created by an anatomical expert on 10 randomly selected CT cases. The error (maximum distance in 3D) between the recognition results and manual inputs distributed from 3-8 mm in different parts of the bone regions.
Tokuda, Junichi; Plishker, William; Torabi, Meysam; Olubiyi, Olutayo I; Zaki, George; Tatli, Servet; Silverman, Stuart G; Shekher, Raj; Hata, Nobuhiko
2015-06-01
Accuracy and speed are essential for the intraprocedural nonrigid magnetic resonance (MR) to computed tomography (CT) image registration in the assessment of tumor margins during CT-guided liver tumor ablations. Although both accuracy and speed can be improved by limiting the registration to a region of interest (ROI), manual contouring of the ROI prolongs the registration process substantially. To achieve accurate and fast registration without the use of an ROI, we combined a nonrigid registration technique on the basis of volume subdivision with hardware acceleration using a graphics processing unit (GPU). We compared the registration accuracy and processing time of GPU-accelerated volume subdivision-based nonrigid registration technique to the conventional nonrigid B-spline registration technique. Fourteen image data sets of preprocedural MR and intraprocedural CT images for percutaneous CT-guided liver tumor ablations were obtained. Each set of images was registered using the GPU-accelerated volume subdivision technique and the B-spline technique. Manual contouring of ROI was used only for the B-spline technique. Registration accuracies (Dice similarity coefficient [DSC] and 95% Hausdorff distance [HD]) and total processing time including contouring of ROIs and computation were compared using a paired Student t test. Accuracies of the GPU-accelerated registrations and B-spline registrations, respectively, were 88.3 ± 3.7% versus 89.3 ± 4.9% (P = .41) for DSC and 13.1 ± 5.2 versus 11.4 ± 6.3 mm (P = .15) for HD. Total processing time of the GPU-accelerated registration and B-spline registration techniques was 88 ± 14 versus 557 ± 116 seconds (P < .000000002), respectively; there was no significant difference in computation time despite the difference in the complexity of the algorithms (P = .71). The GPU-accelerated volume subdivision technique was as accurate as the B-spline technique and required significantly less processing time. The GPU-accelerated volume subdivision technique may enable the implementation of nonrigid registration into routine clinical practice. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li Hua; Noel, Camille; Chen, Haijian
Purpose: Severe artifacts in kilovoltage-CT simulation images caused by large metallic implants can significantly degrade the conspicuity and apparent CT Hounsfield number of targets and anatomic structures, jeopardize the confidence of anatomical segmentation, and introduce inaccuracies into the radiation therapy treatment planning process. This study evaluated the performance of the first commercial orthopedic metal artifact reduction function (O-MAR) for radiation therapy, and investigated its clinical applications in treatment planning. Methods: Both phantom and clinical data were used for the evaluation. The CIRS electron density phantom with known physical (and electron) density plugs and removable titanium implants was scanned on amore » Philips Brilliance Big Bore 16-slice CT simulator. The CT Hounsfield numbers of density plugs on both uncorrected and O-MAR corrected images were compared. Treatment planning accuracy was evaluated by comparing simulated dose distributions computed using the true density images, uncorrected images, and O-MAR corrected images. Ten CT image sets of patients with large hip implants were processed with the O-MAR function and evaluated by two radiation oncologists using a five-point score for overall image quality, anatomical conspicuity, and CT Hounsfield number accuracy. By utilizing the same structure contours delineated from the O-MAR corrected images, clinical IMRT treatment plans for five patients were computed on the uncorrected and O-MAR corrected images, respectively, and compared. Results: Results of the phantom study indicated that CT Hounsfield number accuracy and noise were improved on the O-MAR corrected images, especially for images with bilateral metal implants. The {gamma} pass rates of the simulated dose distributions computed on the uncorrected and O-MAR corrected images referenced to those of the true densities were higher than 99.9% (even when using 1% and 3 mm distance-to-agreement criterion), suggesting that dose distributions were clinically identical. In all patient cases, radiation oncologists rated O-MAR corrected images as higher quality. Formerly obscured critical structures were able to be visualized. The overall image quality and the conspicuity in critical organs were significantly improved compared with the uncorrected images: overall quality score (1.35 vs 3.25, P= 0.0022); bladder (2.15 vs 3.7, P= 0.0023); prostate and seminal vesicles/vagina (1.3 vs 3.275, P= 0.0020); rectum (2.8 vs 3.9, P= 0.0021). The noise levels of the selected ROIs were reduced from 93.7 to 38.2 HU. On most cases (8/10), the average CT Hounsfield numbers of the prostate/vagina on the O-MAR corrected images were closer to the referenced value (41.2 HU, an average measured from patients without metal implants) than those on the uncorrected images. High {gamma} pass rates of the five IMRT dose distribution pairs indicated that the dose distributions were not significantly affected by the CT image improvements. Conclusions: Overall, this study indicated that the O-MAR function can remarkably reduce metal artifacts and improve both CT Hounsfield number accuracy and target and critical structure visualization. Although there was no significant impact of the O-MAR algorithm on the calculated dose distributions, we suggest that O-MAR corrected images are more suitable for the entire treatment planning process by offering better anatomical structure visualization, improving radiation oncologists' confidence in target delineation, and by avoiding subjective density overrides of artifact regions on uncorrected images.« less
Li, Hua; Noel, Camille; Chen, Haijian; Harold Li, H.; Low, Daniel; Moore, Kevin; Klahr, Paul; Michalski, Jeff; Gay, Hiram A.; Thorstad, Wade; Mutic, Sasa
2012-01-01
Purpose: Severe artifacts in kilovoltage-CT simulation images caused by large metallic implants can significantly degrade the conspicuity and apparent CT Hounsfield number of targets and anatomic structures, jeopardize the confidence of anatomical segmentation, and introduce inaccuracies into the radiation therapy treatment planning process. This study evaluated the performance of the first commercial orthopedic metal artifact reduction function (O-MAR) for radiation therapy, and investigated its clinical applications in treatment planning. Methods: Both phantom and clinical data were used for the evaluation. The CIRS electron density phantom with known physical (and electron) density plugs and removable titanium implants was scanned on a Philips Brilliance Big Bore 16-slice CT simulator. The CT Hounsfield numbers of density plugs on both uncorrected and O-MAR corrected images were compared. Treatment planning accuracy was evaluated by comparing simulated dose distributions computed using the true density images, uncorrected images, and O-MAR corrected images. Ten CT image sets of patients with large hip implants were processed with the O-MAR function and evaluated by two radiation oncologists using a five-point score for overall image quality, anatomical conspicuity, and CT Hounsfield number accuracy. By utilizing the same structure contours delineated from the O-MAR corrected images, clinical IMRT treatment plans for five patients were computed on the uncorrected and O-MAR corrected images, respectively, and compared. Results: Results of the phantom study indicated that CT Hounsfield number accuracy and noise were improved on the O-MAR corrected images, especially for images with bilateral metal implants. The γ pass rates of the simulated dose distributions computed on the uncorrected and O-MAR corrected images referenced to those of the true densities were higher than 99.9% (even when using 1% and 3 mm distance-to-agreement criterion), suggesting that dose distributions were clinically identical. In all patient cases, radiation oncologists rated O-MAR corrected images as higher quality. Formerly obscured critical structures were able to be visualized. The overall image quality and the conspicuity in critical organs were significantly improved compared with the uncorrected images: overall quality score (1.35 vs 3.25, P = 0.0022); bladder (2.15 vs 3.7, P = 0.0023); prostate and seminal vesicles/vagina (1.3 vs 3.275, P = 0.0020); rectum (2.8 vs 3.9, P = 0.0021). The noise levels of the selected ROIs were reduced from 93.7 to 38.2 HU. On most cases (8/10), the average CT Hounsfield numbers of the prostate/vagina on the O-MAR corrected images were closer to the referenced value (41.2 HU, an average measured from patients without metal implants) than those on the uncorrected images. High γ pass rates of the five IMRT dose distribution pairs indicated that the dose distributions were not significantly affected by the CT image improvements. Conclusions: Overall, this study indicated that the O-MAR function can remarkably reduce metal artifacts and improve both CT Hounsfield number accuracy and target and critical structure visualization. Although there was no significant impact of the O-MAR algorithm on the calculated dose distributions, we suggest that O-MAR corrected images are more suitable for the entire treatment planning process by offering better anatomical structure visualization, improving radiation oncologists’ confidence in target delineation, and by avoiding subjective density overrides of artifact regions on uncorrected images. PMID:23231300
New prospective 4D-CT for mitigating the effects of irregular respiratory motion
NASA Astrophysics Data System (ADS)
Pan, Tinsu; Martin, Rachael M.; Luo, Dershan
2017-08-01
Artifact caused by irregular respiration is a major source of error in 4D-CT imaging. We propose a new prospective 4D-CT to mitigate this source of error without new hardware, software or off-line data-processing on the GE CT scanner. We utilize the cine CT scan in the design of the new prospective 4D-CT. The cine CT scan at each position can be stopped by the operator when an irregular respiration occurs, and resumed when the respiration becomes regular. This process can be repeated at one or multiple scan positions. After the scan, a retrospective reconstruction is initiated on the CT console to reconstruct only the images corresponding to the regular respiratory cycles. The end result is a 4D-CT free of irregular respiration. To prove feasibility, we conducted a phantom and six patient studies. The artifacts associated with the irregular respiratory cycles could be removed from both the phantom and patient studies. A new prospective 4D-CT scanning and processing technique to mitigate the impact of irregular respiration in 4D-CT has been demonstrated. This technique can save radiation dose because the repeat scans are only at the scan positions where an irregular respiration occurs. Current practice is to repeat the scans at all positions. There is no cost to apply this technique because it is applicable on the GE CT scanner without new hardware, software or off-line data-processing.
Kamogawa, Junji; Kato, Osamu; Morizane, Tatsunori; Hato, Taizo
2015-01-01
There have been several imaging studies of cervical radiculopathy, but no three-dimensional (3D) images have shown the path, position, and pathological changes of the cervical nerve roots and spinal root ganglion relative to the cervical bony structure. The objective of this study was to introduce a technique that enables the virtual pathology of the nerve root to be assessed using 3D magnetic resonance (MR)/computed tomography (CT) fusion images that show the compression of the proximal portion of the cervical nerve root by both the herniated disc and the preforaminal or foraminal bony spur in patients with cervical radiculopathy. MR and CT images were obtained from three patients with cervical radiculopathy. 3D MR images were placed onto 3D CT images using a computer workstation. The entire nerve root could be visualized in 3D with or without the vertebrae. The most important characteristic evident on the images was flattening of the nerve root by a bony spur. The affected root was constricted at a pre-ganglion site. In cases of severe deformity, the flattened portion of the root seemed to change the angle of its path, resulting in twisted condition. The 3D MR/CT fusion imaging technique enhances visualization of pathoanatomy in cervical hidden area that is composed of the root and intervertebral foramen. This technique provides two distinct advantages for diagnosis of cervical radiculopathy. First, the isolation of individual vertebra clarifies the deformities of the whole root groove, including both the uncinate process and superior articular process in the cervical spine. Second, the tortuous or twisted condition of a compressed root can be visualized. The surgeon can identify the narrowest face of the root if they view the MR/CT fusion image from the posterolateral-inferior direction. Surgeons use MR/CT fusion images as a pre-operative map and for intraoperative navigation. The MR/CT fusion images can also be used as educational materials for all hospital staff and for patients and patients' families who provide informed consent for treatments.
CT fluoroscopy-guided robotically-assisted lung biopsy
NASA Astrophysics Data System (ADS)
Xu, Sheng; Fichtinger, Gabor; Taylor, Russell H.; Banovac, Filip; Cleary, Kevin
2006-03-01
Lung biopsy is a common interventional radiology procedure. One of the difficulties in performing the lung biopsy is that lesions move with respiration. This paper presents a new robotically assisted lung biopsy system for CT fluoroscopy that can automatically compensate for the respiratory motion during the intervention. The system consists of a needle placement robot to hold the needle on the CT scan plane, a radiolucent Z-frame for registration of the CT and robot coordinate systems, and a frame grabber to obtain the CT fluoroscopy image in real-time. The CT fluoroscopy images are used to noninvasively track the motion of a pulmonary lesion in real-time. The position of the lesion in the images is automatically determined by the image processing software and the motion of the robot is controlled to compensate for the lesion motion. The system was validated under CT fluoroscopy using a respiratory motion simulator. A swine study was also done to show the feasibility of the technique in a respiring animal.
NASA Astrophysics Data System (ADS)
Burk, Laurel M.; Lee, Yueh Z.; Heathcote, Samuel; Wang, Ko-han; Kim, William Y.; Lu, Jianping; Zhou, Otto
2011-03-01
Current optical imaging techniques can successfully measure tumor load in murine models of lung carcinoma but lack structural detail. We demonstrate that respiratory gated micro-CT imaging of such models gives information about structure and correlates with tumor load measurements by optical methods. Four mice with multifocal, Kras-induced tumors expressing firefly luciferase were imaged against four controls using both optical imaging and respiratory gated micro-CT. CT images of anesthetized animals were acquired with a custom CNT-based system using 30 ms x-ray pulses during peak inspiration; respiration motion was tracked with a pressure sensor beneath each animal's abdomen. Optical imaging based on the Luc+ signal correlating with tumor load was performed on a Xenogen IVIS Kinetix. Micro-CT images were post-processed using Osirix, measuring lung volume with region growing. Diameters of the largest three tumors were measured. Relationships between tumor size, lung volumes, and optical signal were compared. CT images and optical signals were obtained for all animals at two time points. In all lobes of the Kras+ mice in all images, tumors were visible; the smallest to be readily identified measured approximately 300 microns diameter. CT-derived tumor volumes and optical signals related linearly, with r=0.94 for all animals. When derived for only tumor bearing animals, r=0.3. The trend of each individual animal's optical signal tracked correctly based on the CT volumes. Interestingly, lung volumes also correlated positively with optical imaging data and tumor volume burden, suggesting active remodeling.
Zhang, Dongxia; Gan, Yangzhou; Xiong, Jing; Xia, Zeyang
2017-02-01
Complete three-dimensional(3D) tooth model provides essential information to assist orthodontists for diagnosis and treatment planning. Currently, 3D tooth model is mainly obtained by segmentation and reconstruction from dental computed tomography(CT) images. However, the accuracy of 3D tooth model reconstructed from dental CT images is low and not applicable for invisalign design. And another serious problem also occurs, i.e. frequentative dental CT scan during different intervals of orthodontic treatment often leads to radiation to the patients. Hence, this paper proposed a method to reconstruct tooth model based on fusion of dental CT images and laser-scanned images. A complete3 D tooth model was reconstructed with the registration and fusion between the root reconstructed from dental CT images and the crown reconstructed from laser-scanned images. The crown of the complete 3D tooth model reconstructed with the proposed method has higher accuracy. Moreover, in order to reconstruct complete 3D tooth model of each orthodontic treatment interval, only one pre-treatment CT scan is needed and in the orthodontic treatment process only the laser-scan is required. Therefore, radiation to the patients can be reduced significantly.
NASA Astrophysics Data System (ADS)
Jechel, Christopher Alexander
In radiotherapy planning, computed tomography (CT) images are used to quantify the electron density of tissues and provide spatial anatomical information. Treatment planning systems use these data to calculate the expected spatial distribution of absorbed dose in a patient. CT imaging is complicated by the presence of metal implants which cause increased image noise, produce artifacts throughout the image and can exceed the available range of CT number values within the implant, perturbing electron density estimates in the image. Furthermore, current dose calculation algorithms do not accurately model radiation transport at metal-tissue interfaces. Combined, these issues adversely affect the accuracy of dose calculations in the vicinity of metal implants. As the number of patients with orthopedic and dental implants grows, so does the need to deliver safe and effective radiotherapy treatments in the presence of implants. The Medical Physics group at the Cancer Centre of Southeastern Ontario and Queen's University has developed a Cobalt-60 CT system that is relatively insensitive to metal artifacts due to the high energy, nearly monoenergetic Cobalt-60 photon beam. Kilovoltage CT (kVCT) images, including images corrected using a commercial metal artifact reduction tool, were compared to Cobalt-60 CT images throughout the treatment planning process, from initial imaging through to dose calculation. An effective metal artifact reduction algorithm was also implemented for the Cobalt-60 CT system. Electron density maps derived from the same kVCT and Cobalt-60 CT images indicated the impact of image artifacts on estimates of photon attenuation for treatment planning applications. Measurements showed that truncation of CT number data in kVCT images produced significant mischaracterization of the electron density of metals. Dose measurements downstream of metal inserts in a water phantom were compared to dose data calculated using CT images from kVCT and Cobalt-60 systems with and without artifact correction. The superior accuracy of electron density data derived from Cobalt-60 images compared to kVCT images produced calculated dose with far better agreement with measured results. These results indicated that dose calculation errors from metal image artifacts are primarily due to misrepresentation of electron density within metals rather than artifacts surrounding the implants.
Parametric boundary reconstruction algorithm for industrial CT metrology application.
Yin, Zhye; Khare, Kedar; De Man, Bruno
2009-01-01
High-energy X-ray computed tomography (CT) systems have been recently used to produce high-resolution images in various nondestructive testing and evaluation (NDT/NDE) applications. The accuracy of the dimensional information extracted from CT images is rapidly approaching the accuracy achieved with a coordinate measuring machine (CMM), the conventional approach to acquire the metrology information directly. On the other hand, CT systems generate the sinogram which is transformed mathematically to the pixel-based images. The dimensional information of the scanned object is extracted later by performing edge detection on reconstructed CT images. The dimensional accuracy of this approach is limited by the grid size of the pixel-based representation of CT images since the edge detection is performed on the pixel grid. Moreover, reconstructed CT images usually display various artifacts due to the underlying physical process and resulting object boundaries from the edge detection fail to represent the true boundaries of the scanned object. In this paper, a novel algorithm to reconstruct the boundaries of an object with uniform material composition and uniform density is presented. There are three major benefits in the proposed approach. First, since the boundary parameters are reconstructed instead of image pixels, the complexity of the reconstruction algorithm is significantly reduced. The iterative approach, which can be computationally intensive, will be practical with the parametric boundary reconstruction. Second, the object of interest in metrology can be represented more directly and accurately by the boundary parameters instead of the image pixels. By eliminating the extra edge detection step, the overall dimensional accuracy and process time can be improved. Third, since the parametric reconstruction approach shares the boundary representation with other conventional metrology modalities such as CMM, boundary information from other modalities can be directly incorporated as prior knowledge to improve the convergence of an iterative approach. In this paper, the feasibility of parametric boundary reconstruction algorithm is demonstrated with both simple and complex simulated objects. Finally, the proposed algorithm is applied to the experimental industrial CT system data.
Han, Guanghui; Liu, Xiabi; Zheng, Guangyuan; Wang, Murong; Huang, Shan
2018-06-06
Ground-glass opacity (GGO) is a common CT imaging sign on high-resolution CT, which means the lesion is more likely to be malignant compared to common solid lung nodules. The automatic recognition of GGO CT imaging signs is of great importance for early diagnosis and possible cure of lung cancers. The present GGO recognition methods employ traditional low-level features and system performance improves slowly. Considering the high-performance of CNN model in computer vision field, we proposed an automatic recognition method of 3D GGO CT imaging signs through the fusion of hybrid resampling and layer-wise fine-tuning CNN models in this paper. Our hybrid resampling is performed on multi-views and multi-receptive fields, which reduces the risk of missing small or large GGOs by adopting representative sampling panels and processing GGOs with multiple scales simultaneously. The layer-wise fine-tuning strategy has the ability to obtain the optimal fine-tuning model. Multi-CNN models fusion strategy obtains better performance than any single trained model. We evaluated our method on the GGO nodule samples in publicly available LIDC-IDRI dataset of chest CT scans. The experimental results show that our method yields excellent results with 96.64% sensitivity, 71.43% specificity, and 0.83 F1 score. Our method is a promising approach to apply deep learning method to computer-aided analysis of specific CT imaging signs with insufficient labeled images. Graphical abstract We proposed an automatic recognition method of 3D GGO CT imaging signs through the fusion of hybrid resampling and layer-wise fine-tuning CNN models in this paper. Our hybrid resampling reduces the risk of missing small or large GGOs by adopting representative sampling panels and processing GGOs with multiple scales simultaneously. The layer-wise fine-tuning strategy has ability to obtain the optimal fine-tuning model. Our method is a promising approach to apply deep learning method to computer-aided analysis of specific CT imaging signs with insufficient labeled images.
Statistical distributions of ultra-low dose CT sinograms and their fundamental limits
NASA Astrophysics Data System (ADS)
Lee, Tzu-Cheng; Zhang, Ruoqiao; Alessio, Adam M.; Fu, Lin; De Man, Bruno; Kinahan, Paul E.
2017-03-01
Low dose CT imaging is typically constrained to be diagnostic. However, there are applications for even lowerdose CT imaging, including image registration across multi-frame CT images and attenuation correction for PET/CT imaging. We define this as the ultra-low-dose (ULD) CT regime where the exposure level is a factor of 10 lower than current low-dose CT technique levels. In the ULD regime it is possible to use statistically-principled image reconstruction methods that make full use of the raw data information. Since most statistical based iterative reconstruction methods are based on the assumption of that post-log noise distribution is close to Poisson or Gaussian, our goal is to understand the statistical distribution of ULD CT data with different non-positivity correction methods, and to understand when iterative reconstruction methods may be effective in producing images that are useful for image registration or attenuation correction in PET/CT imaging. We first used phantom measurement and calibrated simulation to reveal how the noise distribution deviate from normal assumption under the ULD CT flux environment. In summary, our results indicate that there are three general regimes: (1) Diagnostic CT, where post-log data are well modeled by normal distribution. (2) Lowdose CT, where normal distribution remains a reasonable approximation and statistically-principled (post-log) methods that assume a normal distribution have an advantage. (3) An ULD regime that is photon-starved and the quadratic approximation is no longer effective. For instance, a total integral density of 4.8 (ideal pi for 24 cm of water) for 120kVp, 0.5mAs of radiation source is the maximum pi value where a definitive maximum likelihood value could be found. This leads to fundamental limits in the estimation of ULD CT data when using a standard data processing stream
System Matrix Analysis for Computed Tomography Imaging
Flores, Liubov; Vidal, Vicent; Verdú, Gumersindo
2015-01-01
In practical applications of computed tomography imaging (CT), it is often the case that the set of projection data is incomplete owing to the physical conditions of the data acquisition process. On the other hand, the high radiation dose imposed on patients is also undesired. These issues demand that high quality CT images can be reconstructed from limited projection data. For this reason, iterative methods of image reconstruction have become a topic of increased research interest. Several algorithms have been proposed for few-view CT. We consider that the accurate solution of the reconstruction problem also depends on the system matrix that simulates the scanning process. In this work, we analyze the application of the Siddon method to generate elements of the matrix and we present results based on real projection data. PMID:26575482
WE-G-207-07: Iterative CT Shading Correction Method with No Prior Information
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wu, P; Mao, T; Niu, T
2015-06-15
Purpose: Shading artifacts are caused by scatter contamination, beam hardening effects and other non-ideal imaging condition. Our Purpose is to propose a novel and general correction framework to eliminate low-frequency shading artifacts in CT imaging (e.g., cone-beam CT, low-kVp CT) without relying on prior information. Methods: Our method applies general knowledge of the relatively uniform CT number distribution in one tissue component. Image segmentation is applied to construct template image where each structure is filled with the same CT number of that specific tissue. By subtracting the ideal template from CT image, the residual from various error sources are generated.more » Since the forward projection is an integration process, the non-continuous low-frequency shading artifacts in the image become continuous and low-frequency signals in the line integral. Residual image is thus forward projected and its line integral is filtered using Savitzky-Golay filter to estimate the error. A compensation map is reconstructed on the error using standard FDK algorithm and added to the original image to obtain the shading corrected one. Since the segmentation is not accurate on shaded CT image, the proposed scheme is iterated until the variation of residual image is minimized. Results: The proposed method is evaluated on a Catphan600 phantom, a pelvic patient and a CT angiography scan for carotid artery assessment. Compared to the one without correction, our method reduces the overall CT number error from >200 HU to be <35 HU and increases the spatial uniformity by a factor of 1.4. Conclusion: We propose an effective iterative algorithm for shading correction in CT imaging. Being different from existing algorithms, our method is only assisted by general anatomical and physical information in CT imaging without relying on prior knowledge. Our method is thus practical and attractive as a general solution to CT shading correction. This work is supported by the National Science Foundation of China (NSFC Grant No. 81201091), National High Technology Research and Development Program of China (863 program, Grant No. 2015AA020917), and Fund Project for Excellent Abroad Scholar Personnel in Science and Technology.« less
MDCT imaging of the stomach: advances and applications
Prakash, Anjali; Pradhan, Gaurav; Vidholia, Aditi; Nagpal, Nishant; Saboo, Sachin S; Kuehn, David M; Khandelwal, Ashish
2017-01-01
The stomach may be involved by a myriad of pathologies ranging from benign aetiologies like inflammation to malignant aetiologies like carcinoma or lymphoma. Multidetector CT (MDCT) of the stomach is the first-line imaging for patients with suspected gastric pathologies. Conventionally, CT imaging had the advantage of simultaneous detection of the mural and extramural disease extent, but advances in MDCT have allowed mucosal assessment by virtual endoscopy (VE). Also, better three-dimensional (3D) post-processing techniques have enabled more robust and accurate pre-operative planning in patients undergoing gastrectomy and even predict the response to surgery for patients undergoing laparoscopic sleeve gastrectomy for weight loss. The ability of CT to obtain stomach volume (for bariatric surgery patients) and 3D VE images depends on various patient and protocol factors that are important for a radiologist to understand. We review the appropriate CT imaging protocol in the patients with suspected gastric pathologies and highlight the imaging pearls of various gastric pathologies on CT and VE. PMID:27785936
MDCT imaging of the stomach: advances and applications.
Nagpal, Prashant; Prakash, Anjali; Pradhan, Gaurav; Vidholia, Aditi; Nagpal, Nishant; Saboo, Sachin S; Kuehn, David M; Khandelwal, Ashish
2017-01-01
The stomach may be involved by a myriad of pathologies ranging from benign aetiologies like inflammation to malignant aetiologies like carcinoma or lymphoma. Multidetector CT (MDCT) of the stomach is the first-line imaging for patients with suspected gastric pathologies. Conventionally, CT imaging had the advantage of simultaneous detection of the mural and extramural disease extent, but advances in MDCT have allowed mucosal assessment by virtual endoscopy (VE). Also, better three-dimensional (3D) post-processing techniques have enabled more robust and accurate pre-operative planning in patients undergoing gastrectomy and even predict the response to surgery for patients undergoing laparoscopic sleeve gastrectomy for weight loss. The ability of CT to obtain stomach volume (for bariatric surgery patients) and 3D VE images depends on various patient and protocol factors that are important for a radiologist to understand. We review the appropriate CT imaging protocol in the patients with suspected gastric pathologies and highlight the imaging pearls of various gastric pathologies on CT and VE.
Caballero Perea, Begoña; Villegas, Antonio Cabrera; Rodríguez, José Miguel Delgado; Velloso, María José García; Vicente, Ana María García; Cabrerizo, Carlos Huerga; López, Rosa Morera; Romasanta, Luis Alberto Pérez; Beltrán, Moisés Sáez
2012-01-01
Positron emission tomography (PET) with (18)F-fluorodeoxyglucose (FDG) is a valuable tool for diagnosing and staging malignant lesions. The fusion of PET and computed tomography (CT) yields images that contain both metabolic and morphological information, which, taken together, have improved the diagnostic precision of PET in oncology. The main imaging modality for planning radiotherapy treatment is CT. However, PET-CT is an emerging modality for use in planning treatments because it allows for more accurate treatment volume definition. The use of PET-CT for treatment planning is highly complex, and protocols and standards for its use are still being developed. It seems probable that PET-CT will eventually replace current CT-based planning methods, but this will require a full understanding of the relevant technical aspects of PET-CT planning. The aim of the present document is to review these technical aspects and to provide recommendations for clinical use of this imaging modality in the radiotherapy planning process.
Caballero Perea, Begoña; Villegas, Antonio Cabrera; Rodríguez, José Miguel Delgado; Velloso, María José García; Vicente, Ana María García; Cabrerizo, Carlos Huerga; López, Rosa Morera; Romasanta, Luis Alberto Pérez; Beltrán, Moisés Sáez
2012-01-01
Positron emission tomography (PET) with 18F-fluorodeoxyglucose (FDG) is a valuable tool for diagnosing and staging malignant lesions. The fusion of PET and computed tomography (CT) yields images that contain both metabolic and morphological information, which, taken together, have improved the diagnostic precision of PET in oncology. The main imaging modality for planning radiotherapy treatment is CT. However, PET-CT is an emerging modality for use in planning treatments because it allows for more accurate treatment volume definition. The use of PET-CT for treatment planning is highly complex, and protocols and standards for its use are still being developed. It seems probable that PET-CT will eventually replace current CT-based planning methods, but this will require a full understanding of the relevant technical aspects of PET-CT planning. The aim of the present document is to review these technical aspects and to provide recommendations for clinical use of this imaging modality in the radiotherapy planning process. PMID:24377032
Unified Digital Image Display And Processing System
NASA Astrophysics Data System (ADS)
Horii, Steven C.; Maguire, Gerald Q.; Noz, Marilyn E.; Schimpf, James H.
1981-11-01
Our institution like many others, is faced with a proliferation of medical imaging techniques. Many of these methods give rise to digital images (e.g. digital radiography, computerized tomography (CT) , nuclear medicine and ultrasound). We feel that a unified, digital system approach to image management (storage, transmission and retrieval), image processing and image display will help in integrating these new modalities into the present diagnostic radiology operations. Future techniques are likely to employ digital images, so such a system could readily be expanded to include other image sources. We presently have the core of such a system. We can both view and process digital nuclear medicine (conventional gamma camera) images, positron emission tomography (PET) and CT images on a single system. Images from our recently installed digital radiographic unit can be added. Our paper describes our present system, explains the rationale for its configuration, and describes the directions in which it will expand.
Automated segmentation of hepatic vessel trees in non-contrast x-ray CT images
NASA Astrophysics Data System (ADS)
Kawajiri, Suguru; Zhou, Xiangrong; Zhang, Xuejin; Hara, Takeshi; Fujita, Hiroshi; Yokoyama, Ryujiro; Kondo, Hiroshi; Kanematsu, Masayuki; Hoshi, Hiroaki
2007-03-01
Hepatic vessel trees are the key structures in the liver. Knowledge of the hepatic vessel trees is important for liver surgery planning and hepatic disease diagnosis such as portal hypertension. However, hepatic vessels cannot be easily distinguished from other liver tissues in non-contrast CT images. Automated segmentation of hepatic vessels in non-contrast CT images is a challenging issue. In this paper, an approach for automated segmentation of hepatic vessels trees in non-contrast X-ray CT images is proposed. Enhancement of hepatic vessels is performed using two techniques: (1) histogram transformation based on a Gaussian window function; (2) multi-scale line filtering based on eigenvalues of Hessian matrix. After the enhancement of hepatic vessels, candidate of hepatic vessels are extracted by thresholding. Small connected regions of size less than 100 voxels are considered as false-positives and are removed from the process. This approach is applied to 20 cases of non-contrast CT images. Hepatic vessel trees segmented from the contrast-enhanced CT images of the same patient are used as the ground truth in evaluating the performance of the proposed segmentation method. Results show that the proposed method can enhance and segment the hepatic vessel regions in non-contrast CT images correctly.
A limited-angle CT reconstruction method based on anisotropic TV minimization.
Chen, Zhiqiang; Jin, Xin; Li, Liang; Wang, Ge
2013-04-07
This paper presents a compressed sensing (CS)-inspired reconstruction method for limited-angle computed tomography (CT). Currently, CS-inspired CT reconstructions are often performed by minimizing the total variation (TV) of a CT image subject to data consistency. A key to obtaining high image quality is to optimize the balance between TV-based smoothing and data fidelity. In the case of the limited-angle CT problem, the strength of data consistency is angularly varying. For example, given a parallel beam of x-rays, information extracted in the Fourier domain is mostly orthogonal to the direction of x-rays, while little is probed otherwise. However, the TV minimization process is isotropic, suggesting that it is unfit for limited-angle CT. Here we introduce an anisotropic TV minimization method to address this challenge. The advantage of our approach is demonstrated in numerical simulation with both phantom and real CT images, relative to the TV-based reconstruction.
NASA Astrophysics Data System (ADS)
Latief, F. D. E.; Sari, D. S.; Fitri, L. A.
2017-08-01
High-resolution tomographic imaging by means of x-ray micro-computed tomography (μCT) has been widely utilized for morphological evaluations in dentistry and medicine. The use of μCT follows a standard procedure: image acquisition, reconstruction, processing, evaluation using image analysis, and reporting of results. This paper discusses methods of μCT using a specific scanning device, the Bruker SkyScan 1173 High Energy Micro-CT. We present a description of the general workflow, information on terminology for the measured parameters and corresponding units, and further analyses that can potentially be conducted with this technology. Brief qualitative and quantitative analyses, including basic image processing (VOI selection and thresholding) and measurement of several morphometrical variables (total VOI volume, object volume, percentage of total volume, total VOI surface, object surface, object surface/volume ratio, object surface density, structure thickness, structure separation, total porosity) were conducted on two samples, the mandible of a wistar rat and a urinary tract stone, to illustrate the abilities of this device and its accompanying software package. The results of these analyses for both samples are reported, along with a discussion of the types of analyses that are possible using digital images obtained with a μCT scanning device, paying particular attention to non-diagnostic ex vivo research applications.
Investigation of ultra low-dose scans in the context of quantum-counting clinical CT
NASA Astrophysics Data System (ADS)
Weidinger, T.; Buzug, T. M.; Flohr, T.; Fung, G. S. K.; Kappler, S.; Stierstorfer, K.; Tsui, B. M. W.
2012-03-01
In clinical computed tomography (CT), images from patient examinations taken with conventional scanners exhibit noise characteristics governed by electronics noise, when scanning strongly attenuating obese patients or with an ultra-low X-ray dose. Unlike CT systems based on energy integrating detectors, a system with a quantum counting detector does not suffer from this drawback. Instead, the noise from the electronics mainly affects the spectral resolution of these detectors. Therefore, it does not contribute to the image noise in spectrally non-resolved CT images. This promises improved image quality due to image noise reduction in scans obtained from clinical CT examinations with lowest X-ray tube currents or obese patients. To quantify the benefits of quantum counting detectors in clinical CT we have carried out an extensive simulation study of the complete scanning and reconstruction process for both kinds of detectors. The simulation chain encompasses modeling of the X-ray source, beam attenuation in the patient, and calculation of the detector response. Moreover, in each case the subsequent image preprocessing and reconstruction is modeled as well. The simulation-based, theoretical evaluation is validated by experiments with a novel prototype quantum counting system and a Siemens Definition Flash scanner with a conventional energy integrating CT detector. We demonstrate and quantify the improvement from image noise reduction achievable with quantum counting techniques in CT examinations with ultra-low X-ray dose and strong attenuation.
Watanabe, Yoshiyuki; Tsukabe, Akio; Kunitomi, Yuki; Nishizawa, Mitsuo; Arisawa, Atsuko; Tanaka, Hisashi; Yoshiya, Kazuhisa; Shimazu, Takeshi; Tomiyama, Noriyuki
2014-04-01
Our study aimed to elucidate the diagnostic performance of dual-energy CT (DECT) in the detection of contrast enhancement in intracranial haematomas (ICrH) with early phase dual-energy computed tomography angiography (CTA) and compare the results with those obtained by delayed CT enhancement. Thirty-six patients with ICrH were retrospectively included in this study. All patients had undergone single-energy non-contrast CT and contrast-enhanced dual-source DECT. DECT images were post-processed with commercial software, followed by obtaining iodine images and virtual non-contrast images and generating combined images that created the impression of 120-kVp images. Two neuroradiologists, blinded to the patients' data, reviewed two reading sessions: session A (non-contrast CT and combined CT) and session B (non-contrast CT, combined CT, and iodine images) for detection of contrast enhancement in the haematomas. Contrast leakage or enhancement was detected in 23 (57.5 %) out of 40 haemorrhagic lesions in 36 patients on delayed CT. Three enhanced lesions were depicted only in the DECT iodine images. The sensitivity, specificity, positive predictive value, and negative predictive value of session A were 82.6, 94.1, 95.0, and 80.0 %, respectively, and those of session B were 95.7, 94.1, 95.7, and 94.1 %, respectively. DECT emphasised the iodine enhancement and facilitated the detection of contrast enhancement or leakage.
Zhang, Hao; Zeng, Dong; Zhang, Hua; Wang, Jing; Liang, Zhengrong
2017-01-01
Low-dose X-ray computed tomography (LDCT) imaging is highly recommended for use in the clinic because of growing concerns over excessive radiation exposure. However, the CT images reconstructed by the conventional filtered back-projection (FBP) method from low-dose acquisitions may be severely degraded with noise and streak artifacts due to excessive X-ray quantum noise, or with view-aliasing artifacts due to insufficient angular sampling. In 2005, the nonlocal means (NLM) algorithm was introduced as a non-iterative edge-preserving filter to denoise natural images corrupted by additive Gaussian noise, and showed superior performance. It has since been adapted and applied to many other image types and various inverse problems. This paper specifically reviews the applications of the NLM algorithm in LDCT image processing and reconstruction, and explicitly demonstrates its improving effects on the reconstructed CT image quality from low-dose acquisitions. The effectiveness of these applications on LDCT and their relative performance are described in detail. PMID:28303644
Comparison of an adaptive local thresholding method on CBCT and µCT endodontic images
NASA Astrophysics Data System (ADS)
Michetti, Jérôme; Basarab, Adrian; Diemer, Franck; Kouame, Denis
2018-01-01
Root canal segmentation on cone beam computed tomography (CBCT) images is difficult because of the noise level, resolution limitations, beam hardening and dental morphological variations. An image processing framework, based on an adaptive local threshold method, was evaluated on CBCT images acquired on extracted teeth. A comparison with high quality segmented endodontic images on micro computed tomography (µCT) images acquired from the same teeth was carried out using a dedicated registration process. Each segmented tooth was evaluated according to volume and root canal sections through the area and the Feret’s diameter. The proposed method is shown to overcome the limitations of CBCT and to provide an automated and adaptive complete endodontic segmentation. Despite a slight underestimation (-4, 08%), the local threshold segmentation method based on edge-detection was shown to be fast and accurate. Strong correlations between CBCT and µCT segmentations were found both for the root canal area and diameter (respectively 0.98 and 0.88). Our findings suggest that combining CBCT imaging with this image processing framework may benefit experimental endodontology, teaching and could represent a first development step towards the clinical use of endodontic CBCT segmentation during pulp cavity treatment.
Mori, Shinichiro; Inaniwa, Taku; Kumagai, Motoki; Kuwae, Tsunekazu; Matsuzaki, Yuka; Furukawa, Takuji; Shirai, Toshiyuki; Noda, Koji
2012-06-01
To increase the accuracy of carbon ion beam scanning therapy, we have developed a graphical user interface-based digitally-reconstructed radiograph (DRR) software system for use in routine clinical practice at our center. The DRR software is used in particular scenarios in the new treatment facility to achieve the same level of geometrical accuracy at the treatment as at the imaging session. DRR calculation is implemented simply as the summation of CT image voxel values along the X-ray projection ray. Since we implemented graphics processing unit-based computation, the DRR images are calculated with a speed sufficient for the particular clinical practice requirements. Since high spatial resolution flat panel detector (FPD) images should be registered to the reference DRR images in patient setup process in any scenarios, the DRR images also needs higher spatial resolution close to that of FPD images. To overcome the limitation of the CT spatial resolution imposed by the CT voxel size, we applied image processing to improve the calculated DRR spatial resolution. The DRR software introduced here enabled patient positioning with sufficient accuracy for the implementation of carbon-ion beam scanning therapy at our center.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Xu, M; Foster, R; Parks, H
Purpose: The objective was to utilize and evaluate diagnostic CT-MAR technique for radiation therapy treatment planning. Methods: A Toshiba-diagnostic-CT acquisition with SEMAR(Single-energy-MAR)-algorism was performed to make the metal-artifact-reduction (MAR) for patient treatment planning. CT-imaging datasets with and without SEMAR were taken on a Catphan-phantom. Two sets of CT-numbers were calibrated with the relative electron densities (RED). A tissue characterization phantom with Gammex various simulating material rods was used to establish the relationship between known REDs and corresponding CT-numbers. A GE-CT-sim acquisition was taken on the Catphan for comparison. A patient with bilateral hip arthroplasty was scanned in the radiotherapy CT-simmore » and the diagnostic SEMAR-CT on a flat panel. The derived SEMAR images were used as a primary CT dataset to create contours for the target, critical-structures, and for planning. A deformable registration was performed with VelocityAI to track voxel changes between SEMAR and CT-sim images. The SEMAR-CT images with minimal artifacts and high quality of geometrical and spatial integrity were employed for a treatment plan. Treatment-plans were evaluated based on deformable registration of SEMAR-CT and CT-sim dataset with assigned CT-numbers in the metal artifact regions in Eclipse v11 TPS. Results: The RED and CT-number relationships were consistent for the datasets in CT-sim and CT’s with and without SEMAR. SEMAR datasets with high image quality were used for PTV and organ delineation in the treatment planning process. For dose distribution to the PTV through the DVH analysis, the plan using CT-sim with the assigned CT-number showed a good agreement to those on deformable CT-SEMAR. Conclusion: A diagnostic-CT with MAR-algorithm can be utilized for radiotherapy treatment planning with CT-number calibrated to the RED. Treatment planning comparison and DVH shows a good agreement in the PTV and critical organs between the plans on CT-sim with assigned CT-number and the deformable SEMAR CT datasets.« less
SU-E-I-09: The Impact of X-Ray Scattering On Image Noise for Dedicated Breast CT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, K; Gazi, P; Boone, J
2015-06-15
Purpose: To quantify the impact of detected x-ray scatter on image noise in flat panel based dedicated breast CT systems and to determine the optimal scanning geometry given practical trade-offs between radiation dose and scatter reduction. Methods: Four different uniform polyethylene cylinders (104, 131, 156, and 184 mm in diameter) were scanned as the phantoms on a dedicated breast CT scanner developed in our laboratory. Both stationary projection imaging and rotational cone-beam CT imaging was performed. For each acquisition type, three different x-ray beam collimations were used (12, 24, and 109 mm measured at isocenter). The aim was to quantifymore » image noise properties (pixel variance, SNR, and image NPS) under different levels of x-ray scatter, in order to optimize the scanning geometry. For both projection images and reconstructed CT images, individual pixel variance and NPS were determined and compared. Noise measurement from the CT images were also performed with different detector binning modes and reconstruction matrix sizes. Noise propagation was also tracked throughout the intermediate steps of cone-beam CT reconstruction, including the inverse-logarithmic process, Fourier-filtering before backprojection. Results: Image noise was lower in the presence of higher scatter levels. For the 184 mm polyethylene phantom, the image noise (measured in pixel variance) was ∼30% lower with full cone-beam acquisition compared to a narrow (12 mm) fan-beam acquisition. This trend is consistent across all phantom sizes and throughout all steps of CT image reconstruction. Conclusion: From purely a noise perspective, the cone-beam geometry (i.e. the full cone-angle acquisition) produces lower image noise compared to the lower-scatter fan-beam acquisition for breast CT. While these results are relevant in homogeneous phantoms, the full impact of scatter on noise in bCT should involve contrast-to-noise-ratio measurements in heterogeneous phantoms if the goal is to optimize the scanning geometry for dedicated breast CT. This work was supported by a grant from the National Institute for Biomedical Imaging and Bioengineering (R01 EB002138)« less
WHOLE BODY NONRIGID CT-PET REGISTRATION USING WEIGHTED DEMONS.
Suh, J W; Kwon, Oh-K; Scheinost, D; Sinusas, A J; Cline, Gary W; Papademetris, X
2011-03-30
We present a new registration method for whole-body rat computed tomography (CT) image and positron emission tomography (PET) images using a weighted demons algorithm. The CT and PET images are acquired in separate scanners at different times and the inherent differences in the imaging protocols produced significant nonrigid changes between the two acquisitions in addition to heterogeneous image characteristics. In this situation, we utilized both the transmission-PET and the emission-PET images in the deformable registration process emphasizing particular regions of the moving transmission-PET image using the emission-PET image. We validated our results with nine rat image sets using M-Hausdorff distance similarity measure. We demonstrate improved performance compared to standard methods such as Demons and normalized mutual information-based non-rigid FFD registration.
Emerging Techniques for Dose Optimization in Abdominal CT
Platt, Joel F.; Goodsitt, Mitchell M.; Al-Hawary, Mahmoud M.; Maturen, Katherine E.; Wasnik, Ashish P.; Pandya, Amit
2014-01-01
Recent advances in computed tomographic (CT) scanning technique such as automated tube current modulation (ATCM), optimized x-ray tube voltage, and better use of iterative image reconstruction have allowed maintenance of good CT image quality with reduced radiation dose. ATCM varies the tube current during scanning to account for differences in patient attenuation, ensuring a more homogeneous image quality, although selection of the appropriate image quality parameter is essential for achieving optimal dose reduction. Reducing the x-ray tube voltage is best suited for evaluating iodinated structures, since the effective energy of the x-ray beam will be closer to the k-edge of iodine, resulting in a higher attenuation for the iodine. The optimal kilovoltage for a CT study should be chosen on the basis of imaging task and patient habitus. The aim of iterative image reconstruction is to identify factors that contribute to noise on CT images with use of statistical models of noise (statistical iterative reconstruction) and selective removal of noise to improve image quality. The degree of noise suppression achieved with statistical iterative reconstruction can be customized to minimize the effect of altered image quality on CT images. Unlike with statistical iterative reconstruction, model-based iterative reconstruction algorithms model both the statistical noise and the physical acquisition process, allowing CT to be performed with further reduction in radiation dose without an increase in image noise or loss of spatial resolution. Understanding these recently developed scanning techniques is essential for optimization of imaging protocols designed to achieve the desired image quality with a reduced dose. © RSNA, 2014 PMID:24428277
Yang, Xiaofeng; Wu, Shengyong; Sechopoulos, Ioannis; Fei, Baowei
2012-10-01
To develop and test an automated algorithm to classify the different tissues present in dedicated breast CT images. The original CT images are first corrected to overcome cupping artifacts, and then a multiscale bilateral filter is used to reduce noise while keeping edge information on the images. As skin and glandular tissues have similar CT values on breast CT images, morphologic processing is used to identify the skin mask based on its position information. A modified fuzzy C-means (FCM) classification method is then used to classify breast tissue as fat and glandular tissue. By combining the results of the skin mask with the FCM, the breast tissue is classified as skin, fat, and glandular tissue. To evaluate the authors' classification method, the authors use Dice overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on eight patient images. The correction method was able to correct the cupping artifacts and improve the quality of the breast CT images. For glandular tissue, the overlap ratios between the authors' automatic classification and manual segmentation were 91.6% ± 2.0%. A cupping artifact correction method and an automatic classification method were applied and evaluated for high-resolution dedicated breast CT images. Breast tissue classification can provide quantitative measurements regarding breast composition, density, and tissue distribution.
Yang, Xiaofeng; Wu, Shengyong; Sechopoulos, Ioannis; Fei, Baowei
2012-01-01
Purpose: To develop and test an automated algorithm to classify the different tissues present in dedicated breast CT images. Methods: The original CT images are first corrected to overcome cupping artifacts, and then a multiscale bilateral filter is used to reduce noise while keeping edge information on the images. As skin and glandular tissues have similar CT values on breast CT images, morphologic processing is used to identify the skin mask based on its position information. A modified fuzzy C-means (FCM) classification method is then used to classify breast tissue as fat and glandular tissue. By combining the results of the skin mask with the FCM, the breast tissue is classified as skin, fat, and glandular tissue. To evaluate the authors’ classification method, the authors use Dice overlap ratios to compare the results of the automated classification to those obtained by manual segmentation on eight patient images. Results: The correction method was able to correct the cupping artifacts and improve the quality of the breast CT images. For glandular tissue, the overlap ratios between the authors’ automatic classification and manual segmentation were 91.6% ± 2.0%. Conclusions: A cupping artifact correction method and an automatic classification method were applied and evaluated for high-resolution dedicated breast CT images. Breast tissue classification can provide quantitative measurements regarding breast composition, density, and tissue distribution. PMID:23039675
Multimodality image integration for radiotherapy treatment: an easy approach
NASA Astrophysics Data System (ADS)
Santos, Andres; Pascau, Javier; Desco, Manuel; Santos, Juan A.; Calvo, Felipe A.; Benito, Carlos; Garcia-Barreno, Rafael
2001-05-01
The interest of using combined MR and CT information for radiotherapy planning is well documented. However, many planning workstations do not allow to use MR images, nor import predefined contours. This paper presents a new simple approach for transferring segmentation results from MRI to a CT image that will be used for radiotherapy planning, using the same original CT format. CT and MRI images of the same anatomical area are registered using mutual information (MI) algorithm. Targets and organs at risk are segmented by the physician on the MR image, where their contours are easy to track. A locally developed software running on PC is used for this step, with several facilities for the segmentation process. The result is transferred onto the CT by slightly modifying up and down the original Hounsfield values of some points of the contour. This is enough to visualize the contour on the CT, but does not affect dose calculations. The CT is then stored using the original file format of the radiotherapy planning workstation, where the technician uses the segmented contour to design the correct beam positioning. The described method has been tested in five patients. Simulations and patient results show that the dose distribution is not affected by the small modification of pixels of the CT image, while the segmented structures can be tracked in the radiotherapy planning workstation-using adequate window/level settings. The presence of the physician is not requires at the planning workstation, and he/she can perform the segmentation process using his/her own PC. This new approach makes it possible to take advantage from the anatomical information present on the MRI and to transfer the segmentation to the CT used for planning, even when the planning workstation does not allow to import external contours. The physician can draw the limits of the target and areas at risk off-line, thus separating in time the segmentation and planning tasks and increasing the efficiency.
MRI-based treatment planning with pseudo CT generated through atlas registration.
Uh, Jinsoo; Merchant, Thomas E; Li, Yimei; Li, Xingyu; Hua, Chiaho
2014-05-01
To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes of synthesizing a pseudo CT from single or multiple deformed atlas images: use of a single arbitrarily selected atlas, arithmetic mean process using 6 atlases, and pattern recognition with Gaussian process (PRGP) using 6 or 12 atlases. The required deformation for atlas CT images was derived from a nonlinear registration of conjugated atlas MR images to that of the patient of interest. The contrasts of atlas MR images were adjusted by histogram matching to reduce the effect of different sets of acquisition parameters. For comparison, the authors also tested a simple scheme assigning the Hounsfield unit of water to the entire patient volume. All pseudo CT generating schemes were applied to 14 patients with common pediatric brain tumors. The image similarity of real patient-specific CT and pseudo CTs constructed by different schemes was compared. Differences in computation times were also calculated. The real CT in the treatment planning system was replaced with the pseudo CT, and the dose distribution was recalculated to determine the difference. The atlas approach generally performed better than assigning a bulk CT number to the entire patient volume. Comparing atlas-based schemes, those using multiple atlases outperformed the single atlas scheme. For multiple atlas schemes, the pseudo CTs were similar to the real CTs (correlation coefficient, 0.787-0.819). The calculated dose distribution was in close agreement with the original dose. Nearly the entire patient volume (98.3%-98.7%) satisfied the criteria of chi-evaluation (<2% maximum dose and 2 mm range). The dose to 95% of the volume and the percentage of volume receiving at least 95% of the prescription dose in the planning target volume differed from the original values by less than 2% of the prescription dose (root-mean-square, RMS < 1%). The PRGP scheme did not perform better than the arithmetic mean process with the same number of atlases. Increasing the number of atlases from 6 to 12 often resulted in improvements, but statistical significance was not always found. MRI-based treatment planning with pseudo CTs generated through atlas registration is feasible for pediatric brain tumor patients. The doses calculated from pseudo CTs agreed well with those from real CTs, showing dosimetric accuracy within 2% for the PTV when multiple atlases were used. The arithmetic mean process may be a reasonable choice over PRGP for the synthesis scheme considering performance and computational costs.
MRI-based treatment planning with pseudo CT generated through atlas registration
DOE Office of Scientific and Technical Information (OSTI.GOV)
Uh, Jinsoo, E-mail: jinsoo.uh@stjude.org; Merchant, Thomas E.; Hua, Chiaho
2014-05-15
Purpose: To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. Methods: A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes of synthesizing a pseudo CT from single or multiple deformed atlas images: use of a single arbitrarily selected atlas, arithmetic mean process using 6 atlases, and pattern recognition with Gaussian process (PRGP) using 6 or 12 atlases. The required deformation for atlas CT images was derived from a nonlinear registration ofmore » conjugated atlas MR images to that of the patient of interest. The contrasts of atlas MR images were adjusted by histogram matching to reduce the effect of different sets of acquisition parameters. For comparison, the authors also tested a simple scheme assigning the Hounsfield unit of water to the entire patient volume. All pseudo CT generating schemes were applied to 14 patients with common pediatric brain tumors. The image similarity of real patient-specific CT and pseudo CTs constructed by different schemes was compared. Differences in computation times were also calculated. The real CT in the treatment planning system was replaced with the pseudo CT, and the dose distribution was recalculated to determine the difference. Results: The atlas approach generally performed better than assigning a bulk CT number to the entire patient volume. Comparing atlas-based schemes, those using multiple atlases outperformed the single atlas scheme. For multiple atlas schemes, the pseudo CTs were similar to the real CTs (correlation coefficient, 0.787–0.819). The calculated dose distribution was in close agreement with the original dose. Nearly the entire patient volume (98.3%–98.7%) satisfied the criteria of chi-evaluation (<2% maximum dose and 2 mm range). The dose to 95% of the volume and the percentage of volume receiving at least 95% of the prescription dose in the planning target volume differed from the original values by less than 2% of the prescription dose (root-mean-square, RMS < 1%). The PRGP scheme did not perform better than the arithmetic mean process with the same number of atlases. Increasing the number of atlases from 6 to 12 often resulted in improvements, but statistical significance was not always found. Conclusions: MRI-based treatment planning with pseudo CTs generated through atlas registration is feasible for pediatric brain tumor patients. The doses calculated from pseudo CTs agreed well with those from real CTs, showing dosimetric accuracy within 2% for the PTV when multiple atlases were used. The arithmetic mean process may be a reasonable choice over PRGP for the synthesis scheme considering performance and computational costs.« less
MRI-based treatment planning with pseudo CT generated through atlas registration
Uh, Jinsoo; Merchant, Thomas E.; Li, Yimei; Li, Xingyu; Hua, Chiaho
2014-01-01
Purpose: To evaluate the feasibility and accuracy of magnetic resonance imaging (MRI)-based treatment planning using pseudo CTs generated through atlas registration. Methods: A pseudo CT, providing electron density information for dose calculation, was generated by deforming atlas CT images previously acquired on other patients. The authors tested 4 schemes of synthesizing a pseudo CT from single or multiple deformed atlas images: use of a single arbitrarily selected atlas, arithmetic mean process using 6 atlases, and pattern recognition with Gaussian process (PRGP) using 6 or 12 atlases. The required deformation for atlas CT images was derived from a nonlinear registration of conjugated atlas MR images to that of the patient of interest. The contrasts of atlas MR images were adjusted by histogram matching to reduce the effect of different sets of acquisition parameters. For comparison, the authors also tested a simple scheme assigning the Hounsfield unit of water to the entire patient volume. All pseudo CT generating schemes were applied to 14 patients with common pediatric brain tumors. The image similarity of real patient-specific CT and pseudo CTs constructed by different schemes was compared. Differences in computation times were also calculated. The real CT in the treatment planning system was replaced with the pseudo CT, and the dose distribution was recalculated to determine the difference. Results: The atlas approach generally performed better than assigning a bulk CT number to the entire patient volume. Comparing atlas-based schemes, those using multiple atlases outperformed the single atlas scheme. For multiple atlas schemes, the pseudo CTs were similar to the real CTs (correlation coefficient, 0.787–0.819). The calculated dose distribution was in close agreement with the original dose. Nearly the entire patient volume (98.3%–98.7%) satisfied the criteria of chi-evaluation (<2% maximum dose and 2 mm range). The dose to 95% of the volume and the percentage of volume receiving at least 95% of the prescription dose in the planning target volume differed from the original values by less than 2% of the prescription dose (root-mean-square, RMS < 1%). The PRGP scheme did not perform better than the arithmetic mean process with the same number of atlases. Increasing the number of atlases from 6 to 12 often resulted in improvements, but statistical significance was not always found. Conclusions: MRI-based treatment planning with pseudo CTs generated through atlas registration is feasible for pediatric brain tumor patients. The doses calculated from pseudo CTs agreed well with those from real CTs, showing dosimetric accuracy within 2% for the PTV when multiple atlases were used. The arithmetic mean process may be a reasonable choice over PRGP for the synthesis scheme considering performance and computational costs. PMID:24784377
Classification algorithm of lung lobe for lung disease cases based on multislice CT images
NASA Astrophysics Data System (ADS)
Matsuhiro, M.; Kawata, Y.; Niki, N.; Nakano, Y.; Mishima, M.; Ohmatsu, H.; Tsuchida, T.; Eguchi, K.; Kaneko, M.; Moriyama, N.
2011-03-01
With the development of multi-slice CT technology, to obtain an accurate 3D image of lung field in a short time is possible. To support that, a lot of image processing methods need to be developed. In clinical setting for diagnosis of lung cancer, it is important to study and analyse lung structure. Therefore, classification of lung lobe provides useful information for lung cancer analysis. In this report, we describe algorithm which classify lungs into lung lobes for lung disease cases from multi-slice CT images. The classification algorithm of lung lobes is efficiently carried out using information of lung blood vessel, bronchus, and interlobar fissure. Applying the classification algorithms to multi-slice CT images of 20 normal cases and 5 lung disease cases, we demonstrate the usefulness of the proposed algorithms.
Mandell, Jacob C; Khurana, Bharti; Folio, Les R; Hyun, Hyewon; Smith, Stacy E; Dunne, Ruth M; Andriole, Katherine P
2017-06-01
A methodology is described using Adobe Photoshop and Adobe Extendscript to process DICOM images with a Relative Attenuation-Dependent Image Overlay (RADIO) algorithm to visualize the full dynamic range of CT in one view, without requiring a change in window and level settings. The potential clinical uses for such an algorithm are described in a pictorial overview, including applications in emergency radiology, oncologic imaging, and nuclear medicine and molecular imaging.
Image deblurring using a joint entropy prior in x-ray luminescence computed tomography
NASA Astrophysics Data System (ADS)
Su, Chang; Dutta, Joyita; Zhang, Hui; El Fakhri, Georges; Li, Quanzheng
2017-03-01
X-ray luminescence computed tomography (XLCT) is an emerging hybrid imaging modality that can provide functional and anatomical images at the same time. Traditional narrow beam XLCT can achieve high spatial resolution as well as high sensitivity. However, by treating the CCD camera as a single pixel detector, this kind of scheme resembles the first generation of CT scanner which results in a long scanning time and a high radiation dose. Although cone beam or fan beam XLCT has the ability to mitigate this problem with an optical propagation model introduced, image quality is affected because the inverse problem is ill-conditioned. Much effort has been done to improve the image quality through hardware improvements or by developing new reconstruction techniques for XLCT. The objective of this work is to further enhance the already reconstructed image by introducing anatomical information through retrospective processing. The deblurring process used a spatially variant point spread function (PSF) model and a joint entropy based anatomical prior derived from a CT image acquired using the same XLCT system. A numerical experiment was conducted with a real mouse CT image from the Digimouse phantom used as the anatomical prior. The resultant images of bone and lung regions showed sharp edges and good consistency with the CT image. Activity error was reduced by 52.3% even for nanophosphor lesion size as small as 0.8mm.
Automatic detection of the inner ears in head CT images using deep convolutional neural networks
NASA Astrophysics Data System (ADS)
Zhang, Dongqing; Noble, Jack H.; Dawant, Benoit M.
2018-03-01
Cochlear implants (CIs) use electrode arrays that are surgically inserted into the cochlea to stimulate nerve endings to replace the natural electro-mechanical transduction mechanism and restore hearing for patients with profound hearing loss. Post-operatively, the CI needs to be programmed. Traditionally, this is done by an audiologist who is blind to the positions of the electrodes relative to the cochlea and relies on the patient's subjective response to stimuli. This is a trial-and-error process that can be frustratingly long (dozens of programming sessions are not unusual). To assist audiologists, we have proposed what we call IGCIP for image-guided cochlear implant programming. In IGCIP, we use image processing algorithms to segment the intra-cochlear anatomy in pre-operative CT images and to localize the electrode arrays in post-operative CTs. We have shown that programming strategies informed by image-derived information significantly improve hearing outcomes for both adults and pediatric populations. We are now aiming at deploying these techniques clinically, which requires full automation. One challenge we face is the lack of standard image acquisition protocols. The content of the image volumes we need to process thus varies greatly and visual inspection and labelling is currently required to initialize processing pipelines. In this work we propose a deep learning-based approach to automatically detect if a head CT volume contains two ears, one ear, or no ear. Our approach has been tested on a data set that contains over 2,000 CT volumes from 153 patients and we achieve an overall 95.97% classification accuracy.
Comparison of ring artifact removal methods using flat panel detector based CT images
2011-01-01
Background Ring artifacts are the concentric rings superimposed on the tomographic images often caused by the defective and insufficient calibrated detector elements as well as by the damaged scintillator crystals of the flat panel detector. It may be also generated by objects attenuating X-rays very differently in different projection direction. Ring artifact reduction techniques so far reported in the literature can be broadly classified into two groups. One category of the approaches is based on the sinogram processing also known as the pre-processing techniques and the other category of techniques perform processing on the 2-D reconstructed images, recognized as the post-processing techniques in the literature. The strength and weakness of these categories of approaches are yet to be explored from a common platform. Method In this paper, a comparative study of the two categories of ring artifact reduction techniques basically designed for the multi-slice CT instruments is presented from a common platform. For comparison, two representative algorithms from each of the two categories are selected from the published literature. A very recently reported state-of-the-art sinogram domain ring artifact correction method that classifies the ring artifacts according to their strength and then corrects the artifacts using class adaptive correction schemes is also included in this comparative study. The first sinogram domain correction method uses a wavelet based technique to detect the corrupted pixels and then using a simple linear interpolation technique estimates the responses of the bad pixels. The second sinogram based correction method performs all the filtering operations in the transform domain, i.e., in the wavelet and Fourier domain. On the other hand, the two post-processing based correction techniques actually operate on the polar transform domain of the reconstructed CT images. The first method extracts the ring artifact template vector using a homogeneity test and then corrects the CT images by subtracting the artifact template vector from the uncorrected images. The second post-processing based correction technique performs median and mean filtering on the reconstructed images to produce the corrected images. Results The performances of the comparing algorithms have been tested by using both quantitative and perceptual measures. For quantitative analysis, two different numerical performance indices are chosen. On the other hand, different types of artifact patterns, e.g., single/band ring, artifacts from defective and mis-calibrated detector elements, rings in highly structural object and also in hard object, rings from different flat-panel detectors are analyzed to perceptually investigate the strength and weakness of the five methods. An investigation has been also carried out to compare the efficacy of these algorithms in correcting the volume images from a cone beam CT with the parameters determined from one particular slice. Finally, the capability of each correction technique in retaining the image information (e.g., small object at the iso-center) accurately in the corrected CT image has been also tested. Conclusions The results show that the performances of the algorithms are limited and none is fully suitable for correcting different types of ring artifacts without introducing processing distortion to the image structure. To achieve the diagnostic quality of the corrected slices a combination of the two approaches (sinogram- and post-processing) can be used. Also the comparing methods are not suitable for correcting the volume images from a cone beam flat-panel detector based CT. PMID:21846411
Technical aspects of CT imaging of the spine.
Tins, Bernhard
2010-11-01
This review article discusses technical aspects of computed tomography (CT) imaging of the spine. Patient positioning, and its influence on image quality and movement artefact, is discussed. Particular emphasis is placed on the choice of scan parameters and their relation to image quality and radiation burden to the patient. Strategies to reduce radiation burden and artefact from metal implants are outlined. Data acquisition, processing, image display and steps to reduce artefact are reviewed. CT imaging of the spine is put into context with other imaging modalities for specific clinical indications or problems. This review aims to review underlying principles for image acquisition and to provide a rough guide for clinical problems without being prescriptive. Individual practice will always vary and reflect differences in local experience, technical provisions and clinical requirements.
Acuff, Shelley N.; Neveu, Melissa L.; Syed, Mumtaz; Kaman, Austin D.; Fu, Yitong
2018-01-01
Purpose The usage of PET/computed tomography (CT) to monitor hepatocellular carcinoma patients following yttrium-90 (90Y) radioembolization has increased. Respiratory motion causes liver movement, which can be corrected using gating techniques at the expense of added noise. This work examines the use of amplitude-based gating on 90Y-PET/CT and its potential impact on diagnostic integrity. Patients and methods Patients were imaged using PET/CT following 90Y radioembolization. A respiratory band was used to collect respiratory cycle data. Patient data were processed as both standard and motion-corrected images. Regions of interest were drawn and compared using three methods. Activity concentrations were calculated and converted into dose estimates using previously determined and published scaling factors. Diagnostic assessments were performed using a binary scale created from published 90Y-PET/CT image interpretation guidelines. Results Estimates of radiation dose were increased (P<0.05) when using amplitude-gating methods with 90Y PET/CT imaging. Motion-corrected images show increased noise, but the diagnostic determination of success, using the Kao criteria, did not change between static and motion-corrected data. Conclusion Amplitude-gated PET/CT following 90Y radioembolization is feasible and may improve 90Y dose estimates while maintaining diagnostic assessment integrity. PMID:29351124
Generation of synthetic CT data using patient specific daily MR image data and image registration
NASA Astrophysics Data System (ADS)
Melanie Kraus, Kim; Jäkel, Oliver; Niebuhr, Nina I.; Pfaffenberger, Asja
2017-02-01
To fully exploit the advantages of magnetic resonance imaging (MRI) for radiotherapy (RT) treatment planning, a method is required to overcome the problem of lacking electron density information. We aim to establish and evaluate a new method for computed tomography (CT) data generation based on MRI and image registration. The thereby generated CT data is used for dose accumulation. We developed a process flow based on an initial pair of rigidly co-registered CT and T2-weighted MR image representing the same anatomical situation. Deformable image registration using anatomical landmarks is performed between the initial MRI data and daily MR images. The resulting transformation is applied to the initial CT, thus fractional CT data is generated. Furthermore, the dose for a photon intensity modulated RT (IMRT) or intensity modulated proton therapy (IMPT) plan is calculated on the generated fractional CT and accumulated on the initial CT via inverse transformation. The method is evaluated by the use of phantom CT and MRI data. Quantitative validation is performed by evaluation of the mean absolute error (MAE) between the measured and the generated CT. The effect on dose accumulation is examined by means of dose-volume parameters. One patient case is presented to demonstrate the applicability of the method introduced here. Overall, CT data derivation lead to MAEs with a median of 37.0 HU ranging from 29.9 to 66.6 HU for all investigated tissues. The accuracy of image registration showed to be limited in the case of unexpected air cavities and at tissue boundaries. The comparisons of dose distributions based on measured and generated CT data agree well with the published literature. Differences in dose volume parameters kept within 1.6% and 3.2% for photon and proton RT, respectively. The method presented here is particularly suited for application in adaptive RT in current clinical routine, since only minor additional technical equipment is required.
A fully automated non-external marker 4D-CT sorting algorithm using a serial cine scanning protocol.
Carnes, Greg; Gaede, Stewart; Yu, Edward; Van Dyk, Jake; Battista, Jerry; Lee, Ting-Yim
2009-04-07
Current 4D-CT methods require external marker data to retrospectively sort image data and generate CT volumes. In this work we develop an automated 4D-CT sorting algorithm that performs without the aid of data collected from an external respiratory surrogate. The sorting algorithm requires an overlapping cine scan protocol. The overlapping protocol provides a spatial link between couch positions. Beginning with a starting scan position, images from the adjacent scan position (which spatial match the starting scan position) are selected by maximizing the normalized cross correlation (NCC) of the images at the overlapping slice position. The process was continued by 'daisy chaining' all couch positions using the selected images until an entire 3D volume was produced. The algorithm produced 16 phase volumes to complete a 4D-CT dataset. Additional 4D-CT datasets were also produced using external marker amplitude and phase angle sorting methods. The image quality of the volumes produced by the different methods was quantified by calculating the mean difference of the sorted overlapping slices from adjacent couch positions. The NCC sorted images showed a significant decrease in the mean difference (p < 0.01) for the five patients.
Optimization of CT image reconstruction algorithms for the lung tissue research consortium (LTRC)
NASA Astrophysics Data System (ADS)
McCollough, Cynthia; Zhang, Jie; Bruesewitz, Michael; Bartholmai, Brian
2006-03-01
To create a repository of clinical data, CT images and tissue samples and to more clearly understand the pathogenetic features of pulmonary fibrosis and emphysema, the National Heart, Lung, and Blood Institute (NHLBI) launched a cooperative effort known as the Lung Tissue Resource Consortium (LTRC). The CT images for the LTRC effort must contain accurate CT numbers in order to characterize tissues, and must have high-spatial resolution to show fine anatomic structures. This study was performed to optimize the CT image reconstruction algorithms to achieve these criteria. Quantitative analyses of phantom and clinical images were conducted. The ACR CT accreditation phantom containing five regions of distinct CT attenuations (CT numbers of approximately -1000 HU, -80 HU, 0 HU, 130 HU and 900 HU), and a high-contrast spatial resolution test pattern, was scanned using CT systems from two manufacturers (General Electric (GE) Healthcare and Siemens Medical Solutions). Phantom images were reconstructed using all relevant reconstruction algorithms. Mean CT numbers and image noise (standard deviation) were measured and compared for the five materials. Clinical high-resolution chest CT images acquired on a GE CT system for a patient with diffuse lung disease were reconstructed using BONE and STANDARD algorithms and evaluated by a thoracic radiologist in terms of image quality and disease extent. The clinical BONE images were processed with a 3 x 3 x 3 median filter to simulate a thicker slice reconstructed in smoother algorithms, which have traditionally been proven to provide an accurate estimation of emphysema extent in the lungs. Using a threshold technique, the volume of emphysema (defined as the percentage of lung voxels having a CT number lower than -950 HU) was computed for the STANDARD, BONE, and BONE filtered. The CT numbers measured in the ACR CT Phantom images were accurate for all reconstruction kernels for both manufacturers. As expected, visual evaluation of the spatial resolution bar patterns demonstrated that the BONE (GE) and B46f (Siemens) showed higher spatial resolution compared to the STANDARD (GE) or B30f (Siemens) reconstruction algorithms typically used for routine body CT imaging. Only the sharper images were deemed clinically acceptable for the evaluation of diffuse lung disease (e.g. emphysema). Quantitative analyses of the extent of emphysema in patient data showed the percent volumes above the -950 HU threshold as 9.4% for the BONE reconstruction, 5.9% for the STANDARD reconstruction, and 4.7% for the BONE filtered images. Contrary to the practice of using standard resolution CT images for the quantitation of diffuse lung disease, these data demonstrate that a single sharp reconstruction (BONE/B46f) should be used for both the qualitative and quantitative evaluation of diffuse lung disease. The sharper reconstruction images, which are required for diagnostic interpretation, provide accurate CT numbers over the range of -1000 to +900 HU and preserve the fidelity of small structures in the reconstructed images. A filtered version of the sharper images can be accurately substituted for images reconstructed with smoother kernels for comparison to previously published results.
Bagci, Ulas; Foster, Brent; Miller-Jaster, Kirsten; Luna, Brian; Dey, Bappaditya; Bishai, William R; Jonsson, Colleen B; Jain, Sanjay; Mollura, Daniel J
2013-07-23
Infectious diseases are the second leading cause of death worldwide. In order to better understand and treat them, an accurate evaluation using multi-modal imaging techniques for anatomical and functional characterizations is needed. For non-invasive imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), there have been many engineering improvements that have significantly enhanced the resolution and contrast of the images, but there are still insufficient computational algorithms available for researchers to use when accurately quantifying imaging data from anatomical structures and functional biological processes. Since the development of such tools may potentially translate basic research into the clinic, this study focuses on the development of a quantitative and qualitative image analysis platform that provides a computational radiology perspective for pulmonary infections in small animal models. Specifically, we designed (a) a fast and robust automated and semi-automated image analysis platform and a quantification tool that can facilitate accurate diagnostic measurements of pulmonary lesions as well as volumetric measurements of anatomical structures, and incorporated (b) an image registration pipeline to our proposed framework for volumetric comparison of serial scans. This is an important investigational tool for small animal infectious disease models that can help advance researchers' understanding of infectious diseases. We tested the utility of our proposed methodology by using sequentially acquired CT and PET images of rabbit, ferret, and mouse models with respiratory infections of Mycobacterium tuberculosis (TB), H1N1 flu virus, and an aerosolized respiratory pathogen (necrotic TB) for a total of 92, 44, and 24 scans for the respective studies with half of the scans from CT and the other half from PET. Institutional Administrative Panel on Laboratory Animal Care approvals were obtained prior to conducting this research. First, the proposed computational framework registered PET and CT images to provide spatial correspondences between images. Second, the lungs from the CT scans were segmented using an interactive region growing (IRG) segmentation algorithm with mathematical morphology operations to avoid false positive (FP) uptake in PET images. Finally, we segmented significant radiotracer uptake from the PET images in lung regions determined from CT and computed metabolic volumes of the significant uptake. All segmentation processes were compared with expert radiologists' delineations (ground truths). Metabolic and gross volume of lesions were automatically computed with the segmentation processes using PET and CT images, and percentage changes in those volumes over time were calculated. (Continued on next page)(Continued from previous page) Standardized uptake value (SUV) analysis from PET images was conducted as a complementary quantitative metric for disease severity assessment. Thus, severity and extent of pulmonary lesions were examined through both PET and CT images using the aforementioned quantification metrics outputted from the proposed framework. Each animal study was evaluated within the same subject class, and all steps of the proposed methodology were evaluated separately. We quantified the accuracy of the proposed algorithm with respect to the state-of-the-art segmentation algorithms. For evaluation of the segmentation results, dice similarity coefficient (DSC) as an overlap measure and Haussdorf distance as a shape dissimilarity measure were used. Significant correlations regarding the estimated lesion volumes were obtained both in CT and PET images with respect to the ground truths (R2=0.8922,p<0.01 and R2=0.8664,p<0.01, respectively). The segmentation accuracy (DSC (%)) was 93.4±4.5% for normal lung CT scans and 86.0±7.1% for pathological lung CT scans. Experiments showed excellent agreements (all above 85%) with expert evaluations for both structural and functional imaging modalities. Apart from quantitative analysis of each animal, we also qualitatively showed how metabolic volumes were changing over time by examining serial PET/CT scans. Evaluation of the registration processes was based on precisely defined anatomical landmark points by expert clinicians. An average of 2.66, 3.93, and 2.52 mm errors was found in rabbit, ferret, and mouse data (all within the resolution limits), respectively. Quantitative results obtained from the proposed methodology were visually related to the progress and severity of the pulmonary infections as verified by the participating radiologists. Moreover, we demonstrated that lesions due to the infections were metabolically active and appeared multi-focal in nature, and we observed similar patterns in the CT images as well. Consolidation and ground glass opacity were the main abnormal imaging patterns and consistently appeared in all CT images. We also found that the gross and metabolic lesion volume percentage follow the same trend as the SUV-based evaluation in the longitudinal analysis. We explored the feasibility of using PET and CT imaging modalities in three distinct small animal models for two diverse pulmonary infections. We concluded from the clinical findings, derived from the proposed computational pipeline, that PET-CT imaging is an invaluable hybrid modality for tracking pulmonary infections longitudinally in small animals and has great potential to become routinely used in clinics. Our proposed methodology showed that automated computed-aided lesion detection and quantification of pulmonary infections in small animal models are efficient and accurate as compared to the clinical standard of manual and semi-automated approaches. Automated analysis of images in pre-clinical applications can increase the efficiency and quality of pre-clinical findings that ultimately inform downstream experimental design in human clinical studies; this innovation will allow researchers and clinicians to more effectively allocate study resources with respect to research demands without compromising accuracy.
Glenn, W V; Johnston, R J; Morton, P E; Dwyer, S J
1975-01-01
The various limitations to computerized axial tomographic (CT) interpretation are due in part to the 8-13 mm standard tissue plane thickness and in part to the absence of alternative planes of view, such as coronal or sagittal images. This paper describes a method for gathering multiple overlapped 8 mm transverse sections, subjecting these data to a deconvolution process, and then displaying thin (1 mm) transverse as well as reconstructed coronal and sagittal CT images. Verification of the deconvolution technique with phantom experiments is described. Application of the phantom results to human post mortem CT scan data illustrates this method's faithful reconstruction of coronal and sagittal tissue densities when correlated with actual specimen photographs of a sectioned brain. A special CT procedure, limited basal overlap scanning, is proposed for use on current first generation CT scanners without hardware modification.
NASA Astrophysics Data System (ADS)
Xue, Xinwei; Cheryauka, Arvi; Tubbs, David
2006-03-01
CT imaging in interventional and minimally-invasive surgery requires high-performance computing solutions that meet operational room demands, healthcare business requirements, and the constraints of a mobile C-arm system. The computational requirements of clinical procedures using CT-like data are increasing rapidly, mainly due to the need for rapid access to medical imagery during critical surgical procedures. The highly parallel nature of Radon transform and CT algorithms enables embedded computing solutions utilizing a parallel processing architecture to realize a significant gain of computational intensity with comparable hardware and program coding/testing expenses. In this paper, using a sample 2D and 3D CT problem, we explore the programming challenges and the potential benefits of embedded computing using commodity hardware components. The accuracy and performance results obtained on three computational platforms: a single CPU, a single GPU, and a solution based on FPGA technology have been analyzed. We have shown that hardware-accelerated CT image reconstruction can be achieved with similar levels of noise and clarity of feature when compared to program execution on a CPU, but gaining a performance increase at one or more orders of magnitude faster. 3D cone-beam or helical CT reconstruction and a variety of volumetric image processing applications will benefit from similar accelerations.
Micro-CT images reconstruction and 3D visualization for small animal studying
NASA Astrophysics Data System (ADS)
Gong, Hui; Liu, Qian; Zhong, Aijun; Ju, Shan; Fang, Quan; Fang, Zheng
2005-01-01
A small-animal x-ray micro computed tomography (micro-CT) system has been constructed to screen laboratory small animals and organs. The micro-CT system consists of dual fiber-optic taper-coupled CCD detectors with a field-of-view of 25x50 mm2, a microfocus x-ray source, a rotational subject holder. For accurate localization of rotation center, coincidence between the axis of rotation and centre of image was studied by calibration with a polymethylmethacrylate cylinder. Feldkamp"s filtered back-projection cone-beam algorithm is adopted for three-dimensional reconstruction on account of the effective corn-beam angle is 5.67° of the micro-CT system. 200x1024x1024 matrix data of micro-CT is obtained with the magnification of 1.77 and pixel size of 31x31μm2. In our reconstruction software, output image size of micro-CT slices data, magnification factor and rotation sample degree can be modified in the condition of different computational efficiency and reconstruction region. The reconstructed image matrix data is processed and visualization by Visualization Toolkit (VTK). Data parallelism of VTK is performed in surface rendering of reconstructed data in order to improve computing speed. Computing time of processing a 512x512x512 matrix datasets is about 1/20 compared with serial program when 30 CPU is used. The voxel size is 54x54x108 μm3. The reconstruction and 3-D visualization images of laboratory rat ear are presented.
An algorithm for 4D CT image sorting using spatial continuity.
Li, Chen; Liu, Jie
2013-01-01
4D CT, which could locate the position of the movement of the tumor in the entire respiratory cycle and reduce image artifacts effectively, has been widely used in making radiation therapy of tumors. The current 4D CT methods required external surrogates of respiratory motion obtained from extra instruments. However, respiratory signals recorded by these external makers may not always accurately represent the internal tumor and organ movements, especially when irregular breathing patterns happened. In this paper we have proposed a novel automatic 4D CT sorting algorithm that performs without these external surrogates. The sorting algorithm requires collecting the image data with a cine scan protocol. Beginning with the first couch position, images from the adjacent couch position are selected out according to spatial continuity. The process is continued until images from all couch positions are sorted and the entire 3D volume is produced. The algorithm is verified by respiratory phantom image data and clinical image data. The primary test results show that the 4D CT images created by our algorithm have eliminated the motion artifacts effectively and clearly demonstrated the movement of tumor and organ in the breath period.
NASA Astrophysics Data System (ADS)
Dong, Jian; Kudo, Hiroyuki
2017-03-01
Compressed sensing (CS) is attracting growing concerns in sparse-view computed tomography (CT) image reconstruction. The most standard approach of CS is total variation (TV) minimization. However, images reconstructed by TV usually suffer from distortions, especially in reconstruction of practical CT images, in forms of patchy artifacts, improper serrate edges and loss of image textures. Most existing CS approaches including TV achieve image quality improvement by applying linear transforms to object image, but linear transforms usually fail to take discontinuities into account, such as edges and image textures, which is considered to be the key reason for image distortions. Actually, discussions on nonlinear filter based image processing has a long history, leading us to clarify that the nonlinear filters yield better results compared to linear filters in image processing task such as denoising. Median root prior was first utilized by Alenius as nonlinear transform in CT image reconstruction, with significant gains obtained. Subsequently, Zhang developed the application of nonlocal means-based CS. A fact is gradually becoming clear that the nonlinear transform based CS has superiority in improving image quality compared with the linear transform based CS. However, it has not been clearly concluded in any previous paper within the scope of our knowledge. In this work, we investigated the image quality differences between the conventional TV minimization and nonlinear sparsifying transform based CS, as well as image quality differences among different nonlinear sparisying transform based CSs in sparse-view CT image reconstruction. Additionally, we accelerated the implementation of nonlinear sparsifying transform based CS algorithm.
A novel pre-processing technique for improving image quality in digital breast tomosynthesis.
Kim, Hyeongseok; Lee, Taewon; Hong, Joonpyo; Sabir, Sohail; Lee, Jung-Ryun; Choi, Young Wook; Kim, Hak Hee; Chae, Eun Young; Cho, Seungryong
2017-02-01
Nonlinear pre-reconstruction processing of the projection data in computed tomography (CT) where accurate recovery of the CT numbers is important for diagnosis is usually discouraged, for such a processing would violate the physics of image formation in CT. However, one can devise a pre-processing step to enhance detectability of lesions in digital breast tomosynthesis (DBT) where accurate recovery of the CT numbers is fundamentally impossible due to the incompleteness of the scanned data. Since the detection of lesions such as micro-calcifications and mass in breasts is the purpose of using DBT, it is justified that a technique producing higher detectability of lesions is a virtue. A histogram modification technique was developed in the projection data domain. Histogram of raw projection data was first divided into two parts: One for the breast projection data and the other for background. Background pixel values were set to a single value that represents the boundary between breast and background. After that, both histogram parts were shifted by an appropriate amount of offset and the histogram-modified projection data were log-transformed. Filtered-backprojection (FBP) algorithm was used for image reconstruction of DBT. To evaluate performance of the proposed method, we computed the detectability index for the reconstructed images from clinically acquired data. Typical breast border enhancement artifacts were greatly suppressed and the detectability of calcifications and masses was increased by use of the proposed method. Compared to a global threshold-based post-reconstruction processing technique, the proposed method produced images of higher contrast without invoking additional image artifacts. In this work, we report a novel pre-processing technique that improves detectability of lesions in DBT and has potential advantages over the global threshold-based post-reconstruction processing technique. The proposed method not only increased the lesion detectability but also reduced typical image artifacts pronounced in conventional FBP-based DBT. © 2016 American Association of Physicists in Medicine.
Kamalian, Shervin; Atkinson, Wendy L; Florin, Lauren A; Pomerantz, Stuart R; Lev, Michael H; Romero, Javier M
2014-06-01
Evaluation of the posterior fossa (PF) on 5-mm-thick helical CT images (current default) has improved diagnostic accuracy compared to 5-mm sequential CT images; however, 5-mm-thick images may not be ideal for PF pathology due to volume averaging of rapid changes in anatomy in the Z-direction. Therefore, we sought to determine if routine review of 1.25-mm-thin helical CT images has superior accuracy in screening for nontraumatic PF pathology. MRI proof of diagnosis was obtained within 6 h of helical CT acquisition for 90 consecutive ED patients with, and 88 without, posterior fossa lesions. Helical CT images were post-processed at 1.25 and 5-mm-axial slice thickness. Two neuroradiologists blinded to the clinical/MRI findings reviewed both image sets. Interobserver agreement and accuracy were rated using Kappa statistics and ROC analysis, respectively. Of the 90/178 (51 %) who were MR positive, 60/90 (66 %) had stroke and 30/90 (33 %) had other etiologies. There was excellent interobserver agreement (κ > 0.97) for both thick and thin slice assessments. The accuracy, sensitivity, and specificity for 1.25-mm images were 65, 44, and 84 %, respectively, and for 5-mm images were 67, 45, and 85 %, respectively. The diagnostic accuracy was not significantly different (p > 0.5). In this cohort of patients with nontraumatic neurological symptoms referred to the posterior fossa, 1.25-mm-thin slice CT reformatted images do not have superior accuracy compared to 5-mm-thick images. This information has implications on optimizing resource utilizations and efficiency in a busy emergency room. Review of 1.25-mm-thin images may help diagnostic accuracy only when review of 5-mm-thick images as current default is inconclusive.
NASA Astrophysics Data System (ADS)
Chen, Hu; Zhang, Yi; Zhou, Jiliu; Wang, Ge
2017-09-01
Given the potential risk of X-ray radiation to the patient, low-dose CT has attracted a considerable interest in the medical imaging field. Currently, the main stream low-dose CT methods include vendor-specific sinogram domain filtration and iterative reconstruction algorithms, but they need to access raw data whose formats are not transparent to most users. Due to the difficulty of modeling the statistical characteristics in the image domain, the existing methods for directly processing reconstructed images cannot eliminate image noise very well while keeping structural details. Inspired by the idea of deep learning, here we combine the autoencoder, deconvolution network, and shortcut connections into the residual encoder-decoder convolutional neural network (RED-CNN) for low-dose CT imaging. After patch-based training, the proposed RED-CNN achieves a competitive performance relative to the-state-of-art methods. Especially, our method has been favorably evaluated in terms of noise suppression and structural preservation.
Kagna, Olga; Kurash, Marina; Ghanem-Zoubi, Nesrin; Keidar, Zohar; Israel, Ora
2017-11-01
18 F-FDG PET/CT plays a significant role in the assessment of various infectious processes. Patients with suspected or known sites of infection are often referred for 18 F-FDG imaging while already receiving antibiotic treatment. The current study assessed whether antibiotic therapy affected the detectability rate of infectious processes by 18 F-FDG PET/CT. Methods: A 5-y retrospective study of all adult patients who underwent 18 F-FDG PET/CT in search of a focal source of infection was performed. The presence, duration, and appropriateness of antibiotic treatment before 18 F-FDG imaging were recorded. Diagnosis of an infectious process was based on microbiologic or pathologic data as well as on clinical and radiologic follow-up. Results: Two hundred seventeen patients underwent 243 PET/CT studies in search of a focal source of infection and were included in the study. Sixty-seven studies were excluded from further analysis because of a final noninfectious etiology or lack of further follow-up or details regarding the antibiotic treatment. The final study population included 176 18 F-FDG PET/CT studies in 153 patients (107 men, 46 women; age range, 18-86 y). One hundred nineteen studies (68%) were performed in patients receiving antibiotic therapy for a range of 1-73 d. A diagnosis of infection was made in 107 true-positive cases (61%), including 63 studies (59%) in patients receiving appropriate antibiotic therapy started before the performance of the 18 F-FDG PET/CT study. There were 52 true-negative (29%) and 17 false-positive (10%) 18 F-FDG PET/CT studies. No false-negative results were found. Conclusion: 18 F-FDG PET/CT correctly identified foci of increased uptake compatible with infection in most patients, including all patients receiving appropriate antimicrobial therapy, with no false-negative cases. On the basis of the current study results, the administration of antibiotics appears to have no clinically significant impact on the diagnostic accuracy of 18 F-FDG PET/CT performed for evaluation of known or suspected infectious processes. © 2017 by the Society of Nuclear Medicine and Molecular Imaging.
Wu, Junfeng; Dai, Fang; Hu, Gang; Mou, Xuanqin
2018-04-18
Excessive radiation exposure in computed tomography (CT) scans increases the chance of developing cancer and has become a major clinical concern. Recently, statistical iterative reconstruction (SIR) with l0-norm dictionary learning regularization has been developed to reconstruct CT images from the low dose and few-view dataset in order to reduce radiation dose. Nonetheless, the sparse regularization term adopted in this approach is l0-norm, which cannot guarantee the global convergence of the proposed algorithm. To address this problem, in this study we introduced the l1-norm dictionary learning penalty into SIR framework for low dose CT image reconstruction, and developed an alternating minimization algorithm to minimize the associated objective function, which transforms CT image reconstruction problem into a sparse coding subproblem and an image updating subproblem. During the image updating process, an efficient model function approach based on balancing principle is applied to choose the regularization parameters. The proposed alternating minimization algorithm was evaluated first using real projection data of a sheep lung CT perfusion and then using numerical simulation based on sheep lung CT image and chest image. Both visual assessment and quantitative comparison using terms of root mean square error (RMSE) and structural similarity (SSIM) index demonstrated that the new image reconstruction algorithm yielded similar performance with l0-norm dictionary learning penalty and outperformed the conventional filtered backprojection (FBP) and total variation (TV) minimization algorithms.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, L; Tan, S; Lu, W
Purpose: PET images are usually blurred due to the finite spatial resolution, while CT images suffer from low contrast. Segment a tumor from either a single PET or CT image is thus challenging. To make full use of the complementary information between PET and CT, we propose a novel variational method for simultaneous PET image restoration and PET/CT images co-segmentation. Methods: The proposed model was constructed based on the Γ-convergence approximation of Mumford-Shah (MS) segmentation model for PET/CT co-segmentation. Moreover, a PET de-blur process was integrated into the MS model to improve the segmentation accuracy. An interaction edge constraint termmore » over the two modalities were specially designed to share the complementary information. The energy functional was iteratively optimized using an alternate minimization (AM) algorithm. The performance of the proposed method was validated on ten lung cancer cases and five esophageal cancer cases. The ground truth were manually delineated by an experienced radiation oncologist using the complementary visual features of PET and CT. The segmentation accuracy was evaluated by Dice similarity index (DSI) and volume error (VE). Results: The proposed method achieved an expected restoration result for PET image and satisfactory segmentation results for both PET and CT images. For lung cancer dataset, the average DSI (0.72) increased by 0.17 and 0.40 than single PET and CT segmentation. For esophageal cancer dataset, the average DSI (0.85) increased by 0.07 and 0.43 than single PET and CT segmentation. Conclusion: The proposed method took full advantage of the complementary information from PET and CT images. This work was supported in part by the National Cancer Institute Grants R01CA172638. Shan Tan and Laquan Li were supported in part by the National Natural Science Foundation of China, under Grant Nos. 60971112 and 61375018.« less
Using Image Processing to Determine Emphysema Severity
NASA Astrophysics Data System (ADS)
McKenzie, Alexander; Sadun, Alberto
2010-10-01
Currently X-rays and computerized tomography (CT) scans are used to detect emphysema, but other tests are required to accurately quantify the amount of lung that has been affected by the disease. These images clearly show if a patient has emphysema, but are unable by visual scan alone, to quantify the degree of the disease, as it presents as subtle, dark spots on the lung. Our goal is to use these CT scans to accurately diagnose and determine emphysema severity levels in patients. This will be accomplished by performing several different analyses of CT scan images of several patients representing a wide range of severity of the disease. In addition to analyzing the original CT data, this process will convert the data to one and two bit images and will then examine the deviation from a normal distribution curve to determine skewness. Our preliminary results show that this method of assessment appears to be more accurate and robust than the currently utilized methods, which involve looking at percentages of radiodensities in the air passages of the lung.
Bolliger, Stephan A; Ross, Steffen; Thali, Michael J; Hostettler, Bernhard; Menkveld-Gfeller, Ursula
2012-01-01
The study of fossils permits the reconstruction of past life on our planet and enhances our understanding of evolutionary processes. However, many fossils are difficult to recognize, being encased in a lithified matrix whose tedious removal is required before examination is possible. The authors describe the use of multidetector computed tomography (CT) in locating, identifying, and examining fossil remains of crocodilians (Mesosuchia) embedded in hard shale, all without removing the matrix. In addition, they describe how three-dimensional (3D) reformatted CT images provided details that were helpful for extraction and preparation. Multidetector CT can help experienced paleontologists localize and characterize fossils in the matrix of a promising rock specimen in a nondestructive manner. Moreover, with its capacity to generate highly accurate 3D images, multidetector CT can help determine whether the fossils warrant extraction and can assist in planning the extraction process. Thus, multidetector CT may well become an invaluable tool in the field of paleoradiology.
Panetta, Daniele; Pelosi, Gualtiero; Viglione, Federica; Kusmic, Claudia; Terreni, Marianna; Belcari, Nicola; Guerra, Alberto Del; Athanasiou, Lambros; Exarchos, Themistoklis; Fotiadis, Dimitrios I; Filipovic, Nenad; Trivella, Maria Giovanna; Salvadori, Piero A; Parodi, Oberdan
2015-01-01
Micro-CT is an established imaging technique for high-resolution non-destructive assessment of vascular samples, which is gaining growing interest for investigations of atherosclerotic arteries both in humans and in animal models. However, there is still a lack in the definition of micro-CT image metrics suitable for comprehensive evaluation and quantification of features of interest in the field of experimental atherosclerosis (ATS). A novel approach to micro-CT image processing for profiling of coronary ATS is described, providing comprehensive visualization and quantification of contrast agent-free 3D high-resolution reconstruction of full-length artery walls. Accelerated coronary ATS has been induced by high fat cholesterol-enriched diet in swine and left coronary artery (LCA) harvested en bloc for micro-CT scanning and histologic processing. A cylindrical coordinate system has been defined on the image space after curved multiplanar reformation of the coronary vessel for the comprehensive visualization of the main vessel features such as wall thickening and calcium content. A novel semi-automatic segmentation procedure based on 2D histograms has been implemented and the quantitative results validated by histology. The potentiality of attenuation-based micro-CT at low kV to reliably separate arterial wall layers from adjacent tissue as well as identify wall and plaque contours and major tissue components has been validated by histology. Morphometric indexes from histological data corresponding to several micro-CT slices have been derived (double observer evaluation at different coronary ATS stages) and highly significant correlations (R2 > 0.90) evidenced. Semi-automatic morphometry has been validated by double observer manual morphometry of micro-CT slices and highly significant correlations were found (R2 > 0.92). The micro-CT methodology described represents a handy and reliable tool for quantitative high resolution and contrast agent free full length coronary wall profiling, able to assist atherosclerotic vessels morphometry in a preclinical experimental model of coronary ATS and providing a link between in vivo imaging and histology.
Saroha, Kartik; Pandey, Anil Kumar; Sharma, Param Dev; Behera, Abhishek; Patel, Chetan; Bal, Chandrashekhar; Kumar, Rakesh
2017-01-01
The detection of abdomino-pelvic tumors embedded in or nearby radioactive urine containing 18F-FDG activity is a challenging task on PET/CT scan. In this study, we propose and validate the suprathreshold stochastic resonance-based image processing method for the detection of these tumors. The method consists of the addition of noise to the input image, and then thresholding it that creates one frame of intermediate image. One hundred such frames were generated and averaged to get the final image. The method was implemented using MATLAB R2013b on a personal computer. Noisy image was generated using random Poisson variates corresponding to each pixel of the input image. In order to verify the method, 30 sets of pre-diuretic and its corresponding post-diuretic PET/CT scan images (25 tumor images and 5 control images with no tumor) were included. For each sets of pre-diuretic image (input image), 26 images (at threshold values equal to mean counts multiplied by a constant factor ranging from 1.0 to 2.6 with increment step of 0.1) were created and visually inspected, and the image that most closely matched with the gold standard (corresponding post-diuretic image) was selected as the final output image. These images were further evaluated by two nuclear medicine physicians. In 22 out of 25 images, tumor was successfully detected. In five control images, no false positives were reported. Thus, the empirical probability of detection of abdomino-pelvic tumors evaluates to 0.88. The proposed method was able to detect abdomino-pelvic tumors on pre-diuretic PET/CT scan with a high probability of success and no false positives.
A Rare Case of Malignant Melanoma of the Mandible: CT and MRI Findings.
Ogura, Ichiro; Sasaki, Yoshihiko; Kameta, Ayako; Sue, Mikiko; Oda, Takaaki
Malignant melanoma of the mandibular gingiva is extremely rare. It is a malignant tumour of melanocytes or their precursor cells, and often misinterpreted as a benign pigmented process. A few reports have described computed tomography (CT) and magnetic resonance imaging (MRI) findings of malignant melanoma in the oral cavity. We report a rare case of malignant melanoma of the mandible and the related CT and MRI findings. Soft tissue algorithm contrast-enhanced CT showed an expansile mass and irregular destruction of alveolar bone in the right side of the mandibular molar area. MR images showed an enhancing mass and the tumour had a low to intermediate signal intensity and a high-signal intensity. Soft tissue algorithm contrast-enhanced CT and MR images showed lymphadenopathy involving the submandibular lymph nodes. Histopathological examination confirmed the diagnosis of malignant melanoma.
Simultaneous extraction of centerlines, stenosis, and thrombus detection in renal CT angiography
NASA Astrophysics Data System (ADS)
Subramanyan, Krishna; Durgan, Jacob; Hodgkiss, Thomas D.; Chandra, Shalabh
2004-05-01
The Renal Artery Stenosis (RAS) is the major cause of renovascular hypertension and CT angiography has shown tremendous promise as a noninvasive method for reliably detecting renal artery stenosis. The purpose of this study was to validate the semi-automated methods to assist in extraction of renal branches and characterizing the associated renal artery stenosis. Automatically computed diagnostic images such as straight MIP, curved MPR, cross-sections, and diameters from multi-slice CT are presented and evaluated for its acceptance. We used vessel-tracking image processing methods to extract the aortic-renal vessel tree in a CT data in axial slice images. Next, from the topology and anatomy of the aortic vessel tree, the stenosis, and thrombus section and branching of the renal arteries are extracted. The results are presented in curved MPR and continuously variable MIP images. In this study, 15 patients were scanned with contrast on Mx8000 CT scanner (Philips Medical Systems), with 1.0 mm thickness, 0.5mm slice spacing, and 120kVp and a stack of 512x512x150 volume sets were reconstructed. The automated image processing took less than 50 seconds to compute the centerline and borders of the aortic/renal vessel tree. The overall assessment of manual and automatically generated stenosis yielded a weighted kappa statistic of 0.97 at right renal arteries, 0.94 at the left renal branches. The thrombus region contoured manually and semi-automatically agreed upon at 0.93. The manual time to process each case is approximately 25 to 30 minutes.
3D intrathoracic region definition and its application to PET-CT analysis
NASA Astrophysics Data System (ADS)
Cheirsilp, Ronnarit; Bascom, Rebecca; Allen, Thomas W.; Higgins, William E.
2014-03-01
Recently developed integrated PET-CT scanners give co-registered multimodal data sets that offer complementary three-dimensional (3D) digital images of the chest. PET (positron emission tomography) imaging gives highly specific functional information of suspect cancer sites, while CT (X-ray computed tomography) gives associated anatomical detail. Because the 3D CT and PET scans generally span the body from the eyes to the knees, accurate definition of the intrathoracic region is vital for focusing attention to the central-chest region. In this way, diagnostically important regions of interest (ROIs), such as central-chest lymph nodes and cancer nodules, can be more efficiently isolated. We propose a method for automatic segmentation of the intrathoracic region from a given co-registered 3D PET-CT study. Using the 3D CT scan as input, the method begins by finding an initial intrathoracic region boundary for a given 2D CT section. Next, active contour analysis, driven by a cost function depending on local image gradient, gradient-direction, and contour shape features, iteratively estimates the contours spanning the intrathoracic region on neighboring 2D CT sections. This process continues until the complete region is defined. We next present an interactive system that employs the segmentation method for focused 3D PET-CT chest image analysis. A validation study over a series of PET-CT studies reveals that the segmentation method gives a Dice index accuracy of less than 98%. In addition, further results demonstrate the utility of the method for focused 3D PET-CT chest image analysis, ROI definition, and visualization.
Bagci, Ulas; Udupa, Jayaram K.; Mendhiratta, Neil; Foster, Brent; Xu, Ziyue; Yao, Jianhua; Chen, Xinjian; Mollura, Daniel J.
2013-01-01
We present a novel method for the joint segmentation of anatomical and functional images. Our proposed methodology unifies the domains of anatomical and functional images, represents them in a product lattice, and performs simultaneous delineation of regions based on random walk image segmentation. Furthermore, we also propose a simple yet effective object/background seed localization method to make the proposed segmentation process fully automatic. Our study uses PET, PET-CT, MRI-PET, and fused MRI-PET-CT scans (77 studies in all) from 56 patients who had various lesions in different body regions. We validated the effectiveness of the proposed method on different PET phantoms as well as on clinical images with respect to the ground truth segmentation provided by clinicians. Experimental results indicate that the presented method is superior to threshold and Bayesian methods commonly used in PET image segmentation, is more accurate and robust compared to the other PET-CT segmentation methods recently published in the literature, and also it is general in the sense of simultaneously segmenting multiple scans in real-time with high accuracy needed in routine clinical use. PMID:23837967
NASA Astrophysics Data System (ADS)
Zhou, Xiangrong; Yamada, Kazuma; Kojima, Takuya; Takayama, Ryosuke; Wang, Song; Zhou, Xinxin; Hara, Takeshi; Fujita, Hiroshi
2018-02-01
The purpose of this study is to evaluate and compare the performance of modern deep learning techniques for automatically recognizing and segmenting multiple organ regions on 3D CT images. CT image segmentation is one of the important task in medical image analysis and is still very challenging. Deep learning approaches have demonstrated the capability of scene recognition and semantic segmentation on nature images and have been used to address segmentation problems of medical images. Although several works showed promising results of CT image segmentation by using deep learning approaches, there is no comprehensive evaluation of segmentation performance of the deep learning on segmenting multiple organs on different portions of CT scans. In this paper, we evaluated and compared the segmentation performance of two different deep learning approaches that used 2D- and 3D deep convolutional neural networks (CNN) without- and with a pre-processing step. A conventional approach that presents the state-of-the-art performance of CT image segmentation without deep learning was also used for comparison. A dataset that includes 240 CT images scanned on different portions of human bodies was used for performance evaluation. The maximum number of 17 types of organ regions in each CT scan were segmented automatically and compared to the human annotations by using ratio of intersection over union (IU) as the criterion. The experimental results demonstrated the IUs of the segmentation results had a mean value of 79% and 67% by averaging 17 types of organs that segmented by a 3D- and 2D deep CNN, respectively. All the results of the deep learning approaches showed a better accuracy and robustness than the conventional segmentation method that used probabilistic atlas and graph-cut methods. The effectiveness and the usefulness of deep learning approaches were demonstrated for solving multiple organs segmentation problem on 3D CT images.
Visualisation of the Bonebridge by means of CT and CBCT
2013-01-01
Background With the Bonebridge, a new bone-anchored hearing aid has been available since March 2012. The objective of the study was to analyse the visualisation of the implant itself as well as its impact on the representation of the bony structures of the petrosal bone in CT, MRI and cone beam CT (CBCT). Methods The Bonebridge was implanted unilaterally in two completely prepared human heads. The radiological imaging by means of CBCT, 64-slice CT, 1.5-T and 3.0-T MRI was conducted both preoperatively and postoperatively. The images were subsequently evaluated from both the ENT medical and nd radiological perspectives. Results As anticipated, no visualisation of the implant or of the petrosal bones could be realised on MRI because of the interactive technology and the magnet artefact. In contrast, an excellent evaluability of the implant itself as well as of the surrounding neurovascular structures (sinus sigmoideus, skull base, middle ear, inner ear, inner auditory canal) was exhibited in both the CT and in the CBCT. Conclusion The Bonebridge can be excellently imaged with the radiological imaging technologies of CT and CBCT. In the process, CBCT shows discrete advantages in comparison with CT. No relevant restrictions in image quality in the evaluation of the bony structures of the petrosal bones could be seen. PMID:24004903
Greenspan, Bennett S
2017-12-01
This article discusses the role of PET/CT in contributing to precision medicine in lung cancer, and provides the perspective of the Society of Nuclear Medicine and Molecular Imaging (SNMMI) on this process. The mission and vision of SNMMI are listed, along with the guidance provided by SNMMI to promote best practice in precision medicine. Basic principles of PET/CT are presented. An overview of the use of PET/CT imaging in lung cancer is discussed. In lung cancer patients, PET/CT is vitally important for optimal patient management. PET/CT is essential in determining staging and re-staging of disease, detecting recurrent or residual disease, evaluating response to therapy, and providing prognostic information. PET/CT is also critically important in radiation therapy planning by determining the extent of active disease, including an assessment of functional tumor volume. The current approach in tumor imaging is a significant advance over conventional imaging. However, recent advances suggest that therapeutic response criteria in the near future will be based on metabolic characteristics and will include the evaluation of biologic characteristics of tumors to further enhance the effectiveness of precision medicine in lung cancer, producing improved patient outcomes with less morbidity.
Sinibaldi, R; Conti, A; Sinjari, B; Spadone, S; Pecci, R; Palombo, M; Komlev, V S; Ortore, M G; Tromba, G; Capuani, S; Guidotti, R; De Luca, F; Caputi, S; Traini, T; Della Penna, S
2018-03-01
Bone repair/regeneration is usually investigated through X-ray computed microtomography (μCT) supported by histology of extracted samples, to analyse biomaterial structure and new bone formation processes. Magnetic resonance imaging (μMRI) shows a richer tissue contrast than μCT, despite at lower resolution, and could be combined with μCT in the perspective of conducting non-destructive 3D investigations of bone. A pipeline designed to combine μMRI and μCT images of bone samples is here described and applied on samples of extracted human jawbone core following bone graft. We optimized the coregistration procedure between μCT and μMRI images to avoid bias due to the different resolutions and contrasts. Furthermore, we used an Adaptive Multivariate Clustering, grouping homologous voxels in the coregistered images, to visualize different tissue types within a fused 3D metastructure. The tissue grouping matched the 2D histology applied only on 1 slice, thus extending the histology labelling in 3D. Specifically, in all samples, we could separate and map 2 types of regenerated bone, calcified tissue, soft tissues, and/or fat and marrow space. Remarkably, μMRI and μCT alone were not able to separate the 2 types of regenerated bone. Finally, we computed volumes of each tissue in the 3D metastructures, which might be exploited by quantitative simulation. The 3D metastructure obtained through our pipeline represents a first step to bridge the gap between the quality of information obtained from 2D optical microscopy and the 3D mapping of the bone tissue heterogeneity and could allow researchers and clinicians to non-destructively characterize and follow-up bone regeneration. Copyright © 2017 John Wiley & Sons, Ltd.
Sci—Thur PM: Imaging — 06: Canada's National Computed Tomography (CT) Survey
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wardlaw, GM; Martel, N; Blackler, W
2014-08-15
The value of computed tomography (CT) in medical imaging is reflected in its' increased use and availability since the early 1990's; however, given CT's relatively larger exposures (vs. planar x-ray) greater care must be taken to ensure that CT procedures are optimised in terms of providing the smallest dose possible while maintaining sufficient diagnostic image quality. The development of CT Diagnostic Reference Levels (DRLs) supports this process. DRLs have been suggested/supported by international/national bodies since the early 1990's and widely adopted elsewhere, but not on a national basis in Canada. Essentially, CT DRLs provide guidance on what is considered goodmore » practice for common CT exams, but require a representative sample of CT examination data to make any recommendations. Canada's National CT Survey project, in collaboration with provincial/territorial authorities, has collected a large national sample of CT practice data for 7 common examinations (with associated clinical indications) of both adult and pediatric patients. Following completion of data entry into a common database, a survey summary report and recommendations will be made on CT DRLs from this data. It is hoped that these can then be used by local regions to promote CT practice optimisation and support any dose reduction initiatives.« less
NASA Astrophysics Data System (ADS)
Zhou, Bo; Wen, Di; Nye, Katelyn; Gilkeson, Robert C.; Wilson, David L.
2016-03-01
Coronary artery calcification (CAC) as assessed with CT calcium score is the best biomarker of coronary artery disease. Dual energy x-ray provides an inexpensive, low radiation-dose alternative. A two shot system (GE Revolution-XRd) is used, raw images are processed with a custom algorithm, and a coronary calcium image (DECCI) is created, similar to the bone image, but optimized for CAC visualization, not lung visualization. In this report, we developed a physicsbased, digital-phantom containing heart, lung, CAC, spine, ribs, pulmonary artery, and adipose elements, examined effects on DECCI, suggested physics-inspired algorithms to improve CAC contrast, and evaluated the correlation between CT calcium scores and a proposed DE calcium score. In simulation experiment, Beam hardening from increasing adipose thickness (2cm to 8cm) reduced Cg by 19% and 27% in 120kVp and 60kVp images, but only reduced Cg by <7% in DECCI. If a pulmonary artery moves or pulsates with blood filling between exposures, it can give rise to a significantly confounding PA signal in DECCI similar in amplitude to CAC. Observations suggest modifications to DECCI processing, which can further improve CAC contrast by a factor of 2 in clinical exams. The DE score had the best correlation with "CT mass score" among three commonly used CT scores. Results suggest that DE x-ray is a promising tool for imaging and scoring CAC, and there still remains opportunity for further DECCI processing improvements.
Semiautomated spleen volumetry with diffusion-weighted MR imaging.
Lee, Jeongjin; Kim, Kyoung Won; Lee, Ho; Lee, So Jung; Choi, Sanghyun; Jeong, Woo Kyoung; Kye, Heewon; Song, Gi-Won; Hwang, Shin; Lee, Sung-Gyu
2012-07-01
In this article, we determined the relative accuracy of semiautomated spleen volumetry with diffusion-weighted (DW) MR images compared to standard manual volumetry with DW-MR or CT images. Semiautomated spleen volumetry using simple thresholding followed by 3D and 2D connected component analysis was performed with DW-MR images. Manual spleen volumetry was performed on DW-MR and CT images. In this study, 35 potential live liver donor candidates were included. Semiautomated volumetry results were highly correlated with manual volumetry results using DW-MR (r = 0.99; P < 0.0001; mean percentage absolute difference, 1.43 ± 0.94) and CT (r = 0.99; P < 0.0001; 1.76 ± 1.07). Mean total processing time for semiautomated volumetry was significantly shorter compared to that of manual volumetry with DW-MR (P < 0.0001) and CT (P < 0.0001). In conclusion, semiautomated spleen volumetry with DW-MR images can be performed rapidly and accurately when compared with standard manual volumetry. Copyright © 2011 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Wei, Jikun; Sandison, George A.; Hsi, Wen-Chien; Ringor, Michael; Lu, Xiaoyi
2006-10-01
Accurate dose calculation is essential to precision radiation treatment planning and this accuracy depends upon anatomic and tissue electron density information. Modern treatment planning inhomogeneity corrections use x-ray CT images and calibrated scales of tissue CT number to electron density to provide this information. The presence of metal in the volume scanned by an x-ray CT scanner causes metal induced image artefacts that influence CT numbers and thereby introduce errors in the radiation dose distribution calculated. This paper investigates the dosimetric improvement achieved by a previously proposed x-ray CT metal artefact suppression technique when the suppressed images of a patient with bilateral hip prostheses are used in commercial treatment planning systems for proton, electron or photon therapies. For all these beam types, this clinical image and treatment planning study reveals that the target may be severely underdosed if a metal artefact-contaminated image is used for dose calculations instead of the artefact suppressed one. Of the three beam types studied, the metal artefact suppression is most important for proton therapy dose calculations, intermediate for electron therapy and least important for x-ray therapy but still significant. The study of a water phantom having a metal rod simulating a hip prosthesis indicates that CT numbers generated after image processing for metal artefact suppression are accurate and thus dose calculations based on the metal artefact suppressed images will be of high fidelity.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Plets, C.; Baert, A.L.; Nijs, G.L.
1986-01-01
It is of the greatest importance to the radiologist, the neurologist and the neurosurgeon to be able to localize topographically a pathological brain process on the CT scan as precisely as possible. For that purpose, the identification of as many anatomical structures as possible on the CT scan image are necessary and indispensable. In this atlas a great number of detailed anatomical data on frontal horizontal CT scan sections, each being only 2 mm thick, are indicated, e.g. the cortical gyri, the basal ganglia, details of the white matter, extracranial muscles and blood vessels, parts of the base and themore » vault of the skull, etc. The very precise topographical description of the numerous CT scan images was realized by the author by confrontation of these images with the corresponding anatomical sections of the same brain specimen, performed by an original technique.« less
The segmentation of bones in pelvic CT images based on extraction of key frames.
Yu, Hui; Wang, Haijun; Shi, Yao; Xu, Ke; Yu, Xuyao; Cao, Yuzhen
2018-05-22
Bone segmentation is important in computed tomography (CT) imaging of the pelvis, which assists physicians in the early diagnosis of pelvic injury, in planning operations, and in evaluating the effects of surgical treatment. This study developed a new algorithm for the accurate, fast, and efficient segmentation of the pelvis. The proposed method consists of two main parts: the extraction of key frames and the segmentation of pelvic CT images. Key frames were extracted based on pixel difference, mutual information and normalized correlation coefficient. In the pelvis segmentation phase, skeleton extraction from CT images and a marker-based watershed algorithm were combined to segment the pelvis. To meet the requirements of clinical application, physician's judgment is needed. Therefore the proposed methodology is semi-automated. In this paper, 5 sets of CT data were used to test the overlapping area, and 15 CT images were used to determine the average deviation distance. The average overlapping area of the 5 sets was greater than 94%, and the minimum average deviation distance was approximately 0.58 pixels. In addition, the key frame extraction efficiency and the running time of the proposed method were evaluated on 20 sets of CT data. For each set, approximately 13% of the images were selected as key frames, and the average processing time was approximately 2 min (the time for manual marking was not included). The proposed method is able to achieve accurate, fast, and efficient segmentation of pelvic CT image sequences. Segmentation results not only provide an important reference for early diagnosis and decisions regarding surgical procedures, they also offer more accurate data for medical image registration, recognition and 3D reconstruction.
Removal of bone in CT angiography by multiscale matched mask bone elimination.
Gratama van Andel, H A F; Venema, H W; Streekstra, G J; van Straten, M; Majoie, C B L M; den Heeten, G J; Grimbergen, C A
2007-10-01
For clear visualization of vessels in CT angiography (CTA) images of the head and neck using maximum intensity projection (MIP) or volume rendering (VR) bone has to be removed. In the past we presented a fully automatic method to mask the bone [matched mask bone elimination (MMBE)] for this purpose. A drawback is that vessels adjacent to bone may be partly masked as well. We propose a modification, multiscale MMBE, which reduces this problem by using images at two scales: a higher resolution than usual for image processing and a lower resolution to which the processed images are transformed for use in the diagnostic process. A higher in-plane resolution is obtained by the use of a sharper reconstruction kernel. The out-of-plane resolution is improved by deconvolution or by scanning with narrower collimation. The quality of the mask that is used to remove bone is improved by using images at both scales. After masking, the desired resolution for the normal clinical use of the images is obtained by blurring with Gaussian kernels of appropriate widths. Both methods (multiscale and original) were compared in a phantom study and with clinical CTA data sets. With the multiscale approach the width of the strip of soft tissue adjacent to the bone that is masked can be reduced from 1.0 to 0.2 mm without reducing the quality of the bone removal. The clinical examples show that vessels adjacent to bone are less affected and therefore better visible. Images processed with multiscale MMBE have a slightly higher noise level or slightly reduced resolution compared with images processed by the original method and the reconstruction and processing time is also somewhat increased. Nevertheless, multiscale MMBE offers a way to remove bone automatically from CT angiography images without affecting the integrity of the blood vessels. The overall image quality of MIP or VR images is substantially improved relative to images processed with the original MMBE method.
Image reconstruction for PET/CT scanners: past achievements and future challenges
Tong, Shan; Alessio, Adam M; Kinahan, Paul E
2011-01-01
PET is a medical imaging modality with proven clinical value for disease diagnosis and treatment monitoring. The integration of PET and CT on modern scanners provides a synergy of the two imaging modalities. Through different mathematical algorithms, PET data can be reconstructed into the spatial distribution of the injected radiotracer. With dynamic imaging, kinetic parameters of specific biological processes can also be determined. Numerous efforts have been devoted to the development of PET image reconstruction methods over the last four decades, encompassing analytic and iterative reconstruction methods. This article provides an overview of the commonly used methods. Current challenges in PET image reconstruction include more accurate quantitation, TOF imaging, system modeling, motion correction and dynamic reconstruction. Advances in these aspects could enhance the use of PET/CT imaging in patient care and in clinical research studies of pathophysiology and therapeutic interventions. PMID:21339831
Cone beam tomographic imaging anatomy of the maxillofacial region.
Angelopoulos, Christos
2008-10-01
Multiplanar imaging is a fairly new concept in diagnostic imaging available with a number of contemporary imaging modalities such as CT, MR imaging, diagnostic ultrasound, and others. This modality allows reconstruction of images in different planes (flat or curved) from a volume of data that was acquired previously. This concept makes the diagnostic process more interactive, and proper use may increase diagnostic potential. At the same time, the complexity of the anatomical structures on the maxillofacial region may make it harder for these images to be interpreted. This article reviews the anatomy of maxillofacial structures in planar imaging, and more specifically cone-beam CT images.
SU-F-J-172: Hybrid MR/CT Compatible Phantom for MR-Only Based Radiotherapy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kim, M; Lee, S; Song, K
2016-06-15
Purpose: Development of hybrid MR/CT compatible phantom was introduced to fully establish MR image only radiation treatment and this suggested technique using in-house developed hybrid MR/CT compatible phantom image would utilize to generate radiation treatment planning and perform dose calculation without multi-modal registration process or generation of pseudo CT. Methods: Fundamental characteristics for “hybrid MR/CT compatible phantom” was established: Relaxation times equivalent to human tissue, dielectric properties, homogeneous relaxation times, sufficient strength to fabricate a torso, ease of handling, a wide variety of density material for calibration, chemical and physical stability over an extended time. For this requirements, chemical componentmore » in each tested plug which would be tissue equivalent to human tissue on MR and CT image and production of phantom body and plug was performed. Chemical component has described below: Agaros, GdCl{sub 3}, NaN{sub 3}, NaCl, K{sub 2}Co{sub 3}, deionized-distilled water. Various mixture of chemical component to simulate human tissue on both MR and CT image was tested by measuring T1, T2 relaxation time and signal intensity (SI) on MR image and Hounsfield unit (HU) on CT and each value was compared. The hybrid MR/CT compatible phantom with 14 plugs was designed and has made. Total height and external diameter was decided by internal size of 32 channel MR head-coil. Results: Tissue-equivalent chemical component materials and hybrid MR/CT compatible phantom was developed. The range of T1, T2 relaxation time and SI on MR image, HU on CT was acquired and could be adjusted to correspond to simulated human tissue. Conclusion: Current result shows its possibility for MR-only based radiotherapy and the best mixing rate of chemical component for tissue-equivalent image on MR and CT was founded. However, additional technical issues remain to be overcome. Conversion of SI on MR image into HU and dose calculation based on converted MRI will be progressing.« less
Infective endocarditis detection through SPECT/CT images digital processing
NASA Astrophysics Data System (ADS)
Moreno, Albino; Valdés, Raquel; Jiménez, Luis; Vallejo, Enrique; Hernández, Salvador; Soto, Gabriel
2014-03-01
Infective endocarditis (IE) is a difficult-to-diagnose pathology, since its manifestation in patients is highly variable. In this work, it was proposed a semiautomatic algorithm based on SPECT images digital processing for the detection of IE using a CT images volume as a spatial reference. The heart/lung rate was calculated using the SPECT images information. There were no statistically significant differences between the heart/lung rates values of a group of patients diagnosed with IE (2.62+/-0.47) and a group of healthy or control subjects (2.84+/-0.68). However, it is necessary to increase the study sample of both the individuals diagnosed with IE and the control group subjects, as well as to improve the images quality.
Carotid plaque characterization using CT and MRI scans for synergistic image analysis
NASA Astrophysics Data System (ADS)
Getzin, Matthew; Xu, Yiqin; Rao, Arhant; Madi, Saaussan; Bahadur, Ali; Lennartz, Michelle R.; Wang, Ge
2014-09-01
Noninvasive determination of plaque vulnerability has been a holy grail of medical imaging. Despite advances in tomographic technologies , there is currently no effective way to identify vulnerable atherosclerotic plaques with high sensitivity and specificity. Computed tomography (CT) and magnetic resonance imaging (MRI) are widely used, but neither provides sufficient information of plaque properties. Thus, we are motivated to combine CT and MRI imaging to determine if the composite information can better reflect the histological determination of plaque vulnerability. Two human endarterectomy specimens (1 symptomatic carotid and 1 stable femoral) were imaged using Scanco Medical Viva CT40 and Bruker Pharmascan 16cm 7T Horizontal MRI / MRS systems. μCT scans were done at 55 kVp and tube current of 70 mA. Samples underwent RARE-VTR and MSME pulse sequences to measure T1, T2 values, and proton density. The specimens were processed for histology and scored for vulnerability using the American Heart Association criteria. Single modality-based analyses were performed through segmentation of key imaging biomarkers (i.e. calcification and lumen), image registration, measurement of fibrous capsule, and multi-component T1 and T2 decay modeling. Feature differences were analyzed between the unstable and stable controls, symptomatic carotid and femoral plaque, respectively. By building on the techniques used in this study, synergistic CT+MRI analysis may provide a promising solution for plaque characterization in vivo.
[Progress in Application of Measuring Skeleton by CT in Forensic Anthropology Research].
Miao, C Y; Xu, L; Wang, N; Zhang, M; Li, Y S; Lü, J X
2017-02-01
Individual identification by measuring the human skeleton is an important research in the field of forensic anthropology. Computed tomography (CT) technology can provide high-resolution image of skeleton. Skeleton image can be reformed by software in the post-processing workstation. Different skeleton measurement indexes of anthropology, such as diameter, angle, area and volume, can be measured on section and reformative images. Measurement process is barely affected by human factors. This paper reviews the literatures at home and abroad about the application of measuring skeleton by CT in forensic anthropology research for individual identification in four aspects, including sex determination, height infer, facial soft tissue thickness measurement and age estimation. The major technology and the application of CT in forensic anthropology research are compared and discussed, respectively. Copyright© by the Editorial Department of Journal of Forensic Medicine.
Low-dose CT image reconstruction using gain intervention-based dictionary learning
NASA Astrophysics Data System (ADS)
Pathak, Yadunath; Arya, K. V.; Tiwari, Shailendra
2018-05-01
Computed tomography (CT) approach is extensively utilized in clinical diagnoses. However, X-ray residue in human body may introduce somatic damage such as cancer. Owing to radiation risk, research has focused on the radiation exposure distributed to patients through CT investigations. Therefore, low-dose CT has become a significant research area. Many researchers have proposed different low-dose CT reconstruction techniques. But, these techniques suffer from various issues such as over smoothing, artifacts, noise, etc. Therefore, in this paper, we have proposed a novel integrated low-dose CT reconstruction technique. The proposed technique utilizes global dictionary-based statistical iterative reconstruction (GDSIR) and adaptive dictionary-based statistical iterative reconstruction (ADSIR)-based reconstruction techniques. In case the dictionary (D) is predetermined, then GDSIR can be used and if D is adaptively defined then ADSIR is appropriate choice. The gain intervention-based filter is also used as a post-processing technique for removing the artifacts from low-dose CT reconstructed images. Experiments have been done by considering the proposed and other low-dose CT reconstruction techniques on well-known benchmark CT images. Extensive experiments have shown that the proposed technique outperforms the available approaches.
Evaluation of aortic contractility based on analysis of CT images of the heart
NASA Astrophysics Data System (ADS)
DzierŻak, RóŻa; Maciejewski, Ryszard; Uhlig, Sebastian
2017-08-01
The paper presents a method to assess the aortic contractility based on the analysis of CT images of the heart. This is an alternative method that can be used for patients who cannot be examined by using echocardiography. Usage of medical imaging application for DICOM file processing allows to evaluate the aortic cross section during systole and diastole. It makes possible to assess the level of aortic contractility.
2013-01-01
Background Infectious diseases are the second leading cause of death worldwide. In order to better understand and treat them, an accurate evaluation using multi-modal imaging techniques for anatomical and functional characterizations is needed. For non-invasive imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), there have been many engineering improvements that have significantly enhanced the resolution and contrast of the images, but there are still insufficient computational algorithms available for researchers to use when accurately quantifying imaging data from anatomical structures and functional biological processes. Since the development of such tools may potentially translate basic research into the clinic, this study focuses on the development of a quantitative and qualitative image analysis platform that provides a computational radiology perspective for pulmonary infections in small animal models. Specifically, we designed (a) a fast and robust automated and semi-automated image analysis platform and a quantification tool that can facilitate accurate diagnostic measurements of pulmonary lesions as well as volumetric measurements of anatomical structures, and incorporated (b) an image registration pipeline to our proposed framework for volumetric comparison of serial scans. This is an important investigational tool for small animal infectious disease models that can help advance researchers’ understanding of infectious diseases. Methods We tested the utility of our proposed methodology by using sequentially acquired CT and PET images of rabbit, ferret, and mouse models with respiratory infections of Mycobacterium tuberculosis (TB), H1N1 flu virus, and an aerosolized respiratory pathogen (necrotic TB) for a total of 92, 44, and 24 scans for the respective studies with half of the scans from CT and the other half from PET. Institutional Administrative Panel on Laboratory Animal Care approvals were obtained prior to conducting this research. First, the proposed computational framework registered PET and CT images to provide spatial correspondences between images. Second, the lungs from the CT scans were segmented using an interactive region growing (IRG) segmentation algorithm with mathematical morphology operations to avoid false positive (FP) uptake in PET images. Finally, we segmented significant radiotracer uptake from the PET images in lung regions determined from CT and computed metabolic volumes of the significant uptake. All segmentation processes were compared with expert radiologists’ delineations (ground truths). Metabolic and gross volume of lesions were automatically computed with the segmentation processes using PET and CT images, and percentage changes in those volumes over time were calculated. (Continued on next page)(Continued from previous page) Standardized uptake value (SUV) analysis from PET images was conducted as a complementary quantitative metric for disease severity assessment. Thus, severity and extent of pulmonary lesions were examined through both PET and CT images using the aforementioned quantification metrics outputted from the proposed framework. Results Each animal study was evaluated within the same subject class, and all steps of the proposed methodology were evaluated separately. We quantified the accuracy of the proposed algorithm with respect to the state-of-the-art segmentation algorithms. For evaluation of the segmentation results, dice similarity coefficient (DSC) as an overlap measure and Haussdorf distance as a shape dissimilarity measure were used. Significant correlations regarding the estimated lesion volumes were obtained both in CT and PET images with respect to the ground truths (R2=0.8922,p<0.01 and R2=0.8664,p<0.01, respectively). The segmentation accuracy (DSC (%)) was 93.4±4.5% for normal lung CT scans and 86.0±7.1% for pathological lung CT scans. Experiments showed excellent agreements (all above 85%) with expert evaluations for both structural and functional imaging modalities. Apart from quantitative analysis of each animal, we also qualitatively showed how metabolic volumes were changing over time by examining serial PET/CT scans. Evaluation of the registration processes was based on precisely defined anatomical landmark points by expert clinicians. An average of 2.66, 3.93, and 2.52 mm errors was found in rabbit, ferret, and mouse data (all within the resolution limits), respectively. Quantitative results obtained from the proposed methodology were visually related to the progress and severity of the pulmonary infections as verified by the participating radiologists. Moreover, we demonstrated that lesions due to the infections were metabolically active and appeared multi-focal in nature, and we observed similar patterns in the CT images as well. Consolidation and ground glass opacity were the main abnormal imaging patterns and consistently appeared in all CT images. We also found that the gross and metabolic lesion volume percentage follow the same trend as the SUV-based evaluation in the longitudinal analysis. Conclusions We explored the feasibility of using PET and CT imaging modalities in three distinct small animal models for two diverse pulmonary infections. We concluded from the clinical findings, derived from the proposed computational pipeline, that PET-CT imaging is an invaluable hybrid modality for tracking pulmonary infections longitudinally in small animals and has great potential to become routinely used in clinics. Our proposed methodology showed that automated computed-aided lesion detection and quantification of pulmonary infections in small animal models are efficient and accurate as compared to the clinical standard of manual and semi-automated approaches. Automated analysis of images in pre-clinical applications can increase the efficiency and quality of pre-clinical findings that ultimately inform downstream experimental design in human clinical studies; this innovation will allow researchers and clinicians to more effectively allocate study resources with respect to research demands without compromising accuracy. PMID:23879987
Lam, D L; Mitsumori, L M; Neligan, P C; Warren, B H; Shuman, W P; Dubinsky, T J
2012-12-01
Autologous breast reconstructive surgery with deep inferior epigastric artery (DIEA) perforator flaps has become the mainstay for breast reconstructive surgery. CT angiography and three-dimensional image post processing can depict the number, size, course and location of the DIEA perforating arteries for the pre-operative selection of the best artery to use for the tissue flap. Knowledge of the location and selection of the optimal perforating artery shortens operative times and decreases patient morbidity.
High speed imaging of dynamic processes with a switched source x-ray CT system
NASA Astrophysics Data System (ADS)
Thompson, William M.; Lionheart, William R. B.; Morton, Edward J.; Cunningham, Mike; Luggar, Russell D.
2015-05-01
Conventional x-ray computed tomography (CT) scanners are limited in their scanning speed by the mechanical constraints of their rotating gantries and as such do not provide the necessary temporal resolution for imaging of fast-moving dynamic processes, such as moving fluid flows. The Real Time Tomography (RTT) system is a family of fast cone beam CT scanners which instead use multiple fixed discrete sources and complete rings of detectors in an offset geometry. We demonstrate the potential of this system for use in the imaging of such high speed dynamic processes and give results using simulated and real experimental data. The unusual scanning geometry results in some challenges in image reconstruction, which are overcome using algebraic iterative reconstruction techniques and explicit regularisation. Through the use of a simple temporal regularisation term and by optimising the source firing pattern, we show that temporal resolution of the system may be increased at the expense of spatial resolution, which may be advantageous in some situations. Results are given showing temporal resolution of approximately 500 µs with simulated data and 3 ms with real experimental data.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wu, Meng, E-mail: mengwu@stanford.edu; Fahrig, Rebecca
2014-11-01
Purpose: The scanning beam digital x-ray system (SBDX) is an inverse geometry fluoroscopic system with high dose efficiency and the ability to perform continuous real-time tomosynthesis in multiple planes. This system could be used for image guidance during lung nodule biopsy. However, the reconstructed images suffer from strong out-of-plane artifact due to the small tomographic angle of the system. Methods: The authors propose an out-of-plane artifact subtraction tomosynthesis (OPAST) algorithm that utilizes a prior CT volume to augment the run-time image processing. A blur-and-add (BAA) analytical model, derived from the project-to-backproject physical model, permits the generation of tomosynthesis images thatmore » are a good approximation to the shift-and-add (SAA) reconstructed image. A computationally practical algorithm is proposed to simulate images and out-of-plane artifacts from patient-specific prior CT volumes using the BAA model. A 3D image registration algorithm to align the simulated and reconstructed images is described. The accuracy of the BAA analytical model and the OPAST algorithm was evaluated using three lung cancer patients’ CT data. The OPAST and image registration algorithms were also tested with added nonrigid respiratory motions. Results: Image similarity measurements, including the correlation coefficient, mean squared error, and structural similarity index, indicated that the BAA model is very accurate in simulating the SAA images from the prior CT for the SBDX system. The shift-variant effect of the BAA model can be ignored when the shifts between SBDX images and CT volumes are within ±10 mm in the x and y directions. The nodule visibility and depth resolution are improved by subtracting simulated artifacts from the reconstructions. The image registration and OPAST are robust in the presence of added respiratory motions. The dominant artifacts in the subtraction images are caused by the mismatches between the real object and the prior CT volume. Conclusions: Their proposed prior CT-augmented OPAST reconstruction algorithm improves lung nodule visibility and depth resolution for the SBDX system.« less
Spanier, A B; Caplan, N; Sosna, J; Acar, B; Joskowicz, L
2018-01-01
The goal of medical content-based image retrieval (M-CBIR) is to assist radiologists in the decision-making process by retrieving medical cases similar to a given image. One of the key interests of radiologists is lesions and their annotations, since the patient treatment depends on the lesion diagnosis. Therefore, a key feature of M-CBIR systems is the retrieval of scans with the most similar lesion annotations. To be of value, M-CBIR systems should be fully automatic to handle large case databases. We present a fully automatic end-to-end method for the retrieval of CT scans with similar liver lesion annotations. The input is a database of abdominal CT scans labeled with liver lesions, a query CT scan, and optionally one radiologist-specified lesion annotation of interest. The output is an ordered list of the database CT scans with the most similar liver lesion annotations. The method starts by automatically segmenting the liver in the scan. It then extracts a histogram-based features vector from the segmented region, learns the features' relative importance, and ranks the database scans according to the relative importance measure. The main advantages of our method are that it fully automates the end-to-end querying process, that it uses simple and efficient techniques that are scalable to large datasets, and that it produces quality retrieval results using an unannotated CT scan. Our experimental results on 9 CT queries on a dataset of 41 volumetric CT scans from the 2014 Image CLEF Liver Annotation Task yield an average retrieval accuracy (Normalized Discounted Cumulative Gain index) of 0.77 and 0.84 without/with annotation, respectively. Fully automatic end-to-end retrieval of similar cases based on image information alone, rather that on disease diagnosis, may help radiologists to better diagnose liver lesions.
Dong, Jian; Hayakawa, Yoshihiko; Kannenberg, Sven; Kober, Cornelia
2013-02-01
The objective of this study was to reduce metal-induced streak artifact on oral and maxillofacial x-ray computed tomography (CT) images by developing the fast statistical image reconstruction system using iterative reconstruction algorithms. Adjacent CT images often depict similar anatomical structures in thin slices. So, first, images were reconstructed using the same projection data of an artifact-free image. Second, images were processed by the successive iterative restoration method where projection data were generated from reconstructed image in sequence. Besides the maximum likelihood-expectation maximization algorithm, the ordered subset-expectation maximization algorithm (OS-EM) was examined. Also, small region of interest (ROI) setting and reverse processing were applied for improving performance. Both algorithms reduced artifacts instead of slightly decreasing gray levels. The OS-EM and small ROI reduced the processing duration without apparent detriments. Sequential and reverse processing did not show apparent effects. Two alternatives in iterative reconstruction methods were effective for artifact reduction. The OS-EM algorithm and small ROI setting improved the performance. Copyright © 2012 Elsevier Inc. All rights reserved.
The new frontiers of multimodality and multi-isotope imaging
NASA Astrophysics Data System (ADS)
Behnam Azad, Babak; Nimmagadda, Sridhar
2014-06-01
Technological advances in imaging systems and the development of target specific imaging tracers has been rapidly growing over the past two decades. Recent progress in "all-in-one" imaging systems that allow for automated image coregistration has significantly added to the growth of this field. These developments include ultra high resolution PET and SPECT scanners that can be integrated with CT or MR resulting in PET/CT, SPECT/CT, SPECT/PET and PET/MRI scanners for simultaneous high resolution high sensitivity anatomical and functional imaging. These technological developments have also resulted in drastic enhancements in image quality and acquisition time while eliminating cross compatibility issues between modalities. Furthermore, the most cutting edge technology, though mostly preclinical, also allows for simultaneous multimodality multi-isotope image acquisition and image reconstruction based on radioisotope decay characteristics. These scientific advances, in conjunction with the explosion in the development of highly specific multimodality molecular imaging agents, may aid in realizing simultaneous imaging of multiple biological processes and pave the way towards more efficient diagnosis and improved patient care.
Lab-X-ray multidimensional imaging of processes inside porous media
NASA Astrophysics Data System (ADS)
Godinho, Jose
2017-04-01
Time-lapse and other multidimensional X-ray imaging techniques have mostly been applied using synchrotron radiation, which limits accessibility and complicates data analysis. Here, we present new time-lapse imaging approaches using laboratory X-ray computed microtomography (CT) to study transformations inside porous media. Specifically, three methods will be presented: 1) Quantitative time-lapse radiography to study sub-second processes. For example to study the penetration of particles into fractures and pores, which is essential to understand how proppants keep fractures opened during hydraulic fracturing and how filter cakes form during borehole drilling. 2) Combination of time-lapse CT with diffraction tomography to study the transformation between bio-inspired polymorphs in 6D, e.g. mineral phase transformation between ACC, Vaterite and Calcite - CaCO3, and between ACS, Anhydrite and Gypsum - CaSO4. Crystals can be resolved in nanopores down to 7 nm (over 100 times smaller than the resolution of CT), which allows studying the effect of confinement on phase stability and growth rates. 3) Fast iterative helical micro-CT scanning to study samples of high ratio height to width (e.g. long cores) with optimal resolution. Here we show how this can be useful to study the distribution of the products from fluid-mediated mineral reactions throughout longer reaction paths and more representative volumes. Using state of the art reconstruction algorithms allows reducing the scanning times from over ten hours to below two hours enabling time-lapse studies. It is expected that these new techniques will open new possibilities for time-lapse imaging of a wider range of geological processes using laboratory X-ray CT, thereby increasing the accessibility of multidimensional imaging to a larger number of users and applications in geology.
Selected PET radiomic features remain the same.
Tsujikawa, Tetsuya; Tsuyoshi, Hideaki; Kanno, Masafumi; Yamada, Shizuka; Kobayashi, Masato; Narita, Norihiko; Kimura, Hirohiko; Fujieda, Shigeharu; Yoshida, Yoshio; Okazawa, Hidehiko
2018-04-17
We investigated whether PET radiomic features are affected by differences in the scanner, scan protocol, and lesion location using 18 F-FDG PET/CT and PET/MR scans. SUV, TMR, skewness, kurtosis, entropy, and homogeneity strongly correlated between PET/CT and PET/MR images. SUVs were significantly higher on PET/MR 0-2 min and PET/MR 0-10 min than on PET/CT in gynecological cancer ( p = 0.008 and 0.008, respectively), whereas no significant difference was observed between PET/CT, PET/MR 0-2 min , and PET/MR 0-10 min images in oral cavity/oropharyngeal cancer. TMRs on PET/CT, PET/MR 0-2 min , and PET/MR 0-10 min increased in this order in gynecological cancer and oral cavity/oropharyngeal cancer. In contrast to conventional and histogram indices, 4 textural features (entropy, homogeneity, SRE, and LRE) were not significantly different between PET/CT, PET/MR 0-2 min , and PET/MR 0-10 min images. 18 F-FDG PET radiomic features strongly correlated between PET/CT and PET/MR images. Dixon-based attenuation correction on PET/MR images underestimated tumor tracer uptake more significantly in oral cavity/oropharyngeal cancer than in gynecological cancer. 18 F-FDG PET textural features were affected less by differences in the scanner and scan protocol than conventional and histogram features, possibly due to the resampling process using a medium bin width. Eight patients with gynecological cancer and 7 with oral cavity/oropharyngeal cancer underwent a whole-body 18 F-FDG PET/CT scan and regional PET/MR scan in one day. PET/MR scans were performed for 10 minutes in the list mode, and PET/CT and 0-2 min and 0-10 min PET/MR images were reconstructed. The standardized uptake value (SUV), tumor-to-muscle SUV ratio (TMR), skewness, kurtosis, entropy, homogeneity, short-run emphasis (SRE), and long-run emphasis (LRE) were compared between PET/CT, PET/MR 0-2 min , and PET/MR 0-10 min images.
Sun, Yajuan; Yu, Hongjuan; Ma, Jingquan; Lu, Peiou
2016-01-01
The aim of our study was to evaluate the role of 18F-FDG PET/CT integrated imaging in differentiating malignant from benign pleural effusion. A total of 176 patients with pleural effusion who underwent 18F-FDG PET/CT examination to differentiate malignancy from benignancy were retrospectively researched. The images of CT imaging, 18F-FDG PET imaging and 18F-FDG PET/CT integrated imaging were visually analyzed. The suspected malignant effusion was characterized by the presence of nodular or irregular pleural thickening on CT imaging. Whereas on PET imaging, pleural 18F-FDG uptake higher than mediastinal activity was interpreted as malignant effusion. Images of 18F-FDG PET/CT integrated imaging were interpreted by combining the morphologic feature of pleura on CT imaging with the degree and form of pleural 18F-FDG uptake on PET imaging. One hundred and eight patients had malignant effusion, including 86 with pleural metastasis and 22 with pleural mesothelioma, whereas 68 patients had benign effusion. The sensitivities of CT imaging, 18F-FDG PET imaging and 18F-FDG PET/CT integrated imaging in detecting malignant effusion were 75.0%, 91.7% and 93.5%, respectively, which were 69.8%, 91.9% and 93.0% in distinguishing metastatic effusion. The sensitivity of 18F-FDG PET/CT integrated imaging in detecting malignant effusion was higher than that of CT imaging (p = 0.000). For metastatic effusion, 18F-FDG PET imaging had higher sensitivity (p = 0.000) and better diagnostic consistency with 18F-FDG PET/CT integrated imaging compared with CT imaging (Kappa = 0.917 and Kappa = 0.295, respectively). The specificities of CT imaging, 18F-FDG PET imaging and 18F-FDG PET/CT integrated imaging were 94.1%, 63.2% and 92.6% in detecting benign effusion. The specificities of CT imaging and 18F-FDG PET/CT integrated imaging were higher than that of 18F-FDG PET imaging (p = 0.000 and p = 0.000, respectively), and CT imaging had better diagnostic consistency with 18F-FDG PET/CT integrated imaging compared with 18F-FDG PET imaging (Kappa = 0.881 and Kappa = 0.240, respectively). 18F-FDG PET/CT integrated imaging is a more reliable modality in distinguishing malignant from benign pleural effusion than 18F-FDG PET imaging and CT imaging alone. For image interpretation of 18F-FDG PET/CT integrated imaging, the PET and CT portions play a major diagnostic role in identifying metastatic effusion and benign effusion, respectively.
Nithiananthan, Sajendra; Schafer, Sebastian; Uneri, Ali; Mirota, Daniel J; Stayman, J Webster; Zbijewski, Wojciech; Brock, Kristy K; Daly, Michael J; Chan, Harley; Irish, Jonathan C; Siewerdsen, Jeffrey H
2011-04-01
A method of intensity-based deformable registration of CT and cone-beam CT (CBCT) images is described, in which intensity correction occurs simultaneously within the iterative registration process. The method preserves the speed and simplicity of the popular Demons algorithm while providing robustness and accuracy in the presence of large mismatch between CT and CBCT voxel values ("intensity"). A variant of the Demons algorithm was developed in which an estimate of the relationship between CT and CBCT intensity values for specific materials in the image is computed at each iteration based on the set of currently overlapping voxels. This tissue-specific intensity correction is then used to estimate the registration output for that iteration and the process is repeated. The robustness of the method was tested in CBCT images of a cadaveric head exhibiting a broad range of simulated intensity variations associated with x-ray scatter, object truncation, and/or errors in the reconstruction algorithm. The accuracy of CT-CBCT registration was also measured in six real cases, exhibiting deformations ranging from simple to complex during surgery or radiotherapy guided by a CBCT-capable C-arm or linear accelerator, respectively. The iterative intensity matching approach was robust against all levels of intensity variation examined, including spatially varying errors in voxel value of a factor of 2 or more, as can be encountered in cases of high x-ray scatter. Registration accuracy without intensity matching degraded severely with increasing magnitude of intensity error and introduced image distortion. A single histogram match performed prior to registration alleviated some of these effects but was also prone to image distortion and was quantifiably less robust and accurate than the iterative approach. Within the six case registration accuracy study, iterative intensity matching Demons reduced mean TRE to (2.5 +/- 2.8) mm compared to (3.5 +/- 3.0) mm with rigid registration. A method was developed to iteratively correct CT-CBCT intensity disparity during Demons registration, enabling fast, intensity-based registration in CBCT-guided procedures such as surgery and radiotherapy, in which CBCT voxel values may be inaccurate. Accurate CT-CBCT registration in turn facilitates registration of multimodality preoperative image and planning data to intraoperative CBCT by way of the preoperative CT, thereby linking the intraoperative frame of reference to a wealth of preoperative information that could improve interventional guidance.
Chen, Liang; Carlton Jones, Anoma Lalani; Mair, Grant; Patel, Rajiv; Gontsarova, Anastasia; Ganesalingam, Jeban; Math, Nikhil; Dawson, Angela; Aweid, Basaam; Cohen, David; Mehta, Amrish; Wardlaw, Joanna; Rueckert, Daniel; Bentley, Paul
2018-05-15
Purpose To validate a random forest method for segmenting cerebral white matter lesions (WMLs) on computed tomographic (CT) images in a multicenter cohort of patients with acute ischemic stroke, by comparison with fluid-attenuated recovery (FLAIR) magnetic resonance (MR) images and expert consensus. Materials and Methods A retrospective sample of 1082 acute ischemic stroke cases was obtained that was composed of unselected patients who were treated with thrombolysis or who were undergoing contemporaneous MR imaging and CT, and a subset of International Stroke Thrombolysis-3 trial participants. Automated delineations of WML on images were validated relative to experts' manual tracings on CT images, and co-registered FLAIR MR imaging, and ratings were performed by using two conventional ordinal scales. Analyses included correlations between CT and MR imaging volumes, and agreements between automated and expert ratings. Results Automated WML volumes correlated strongly with expert-delineated WML volumes at MR imaging and CT (r 2 = 0.85 and 0.71 respectively; P < .001). Spatial-similarity of automated maps, relative to WML MR imaging, was not significantly different to that of expert WML tracings on CT images. Individual expert WML volumes at CT correlated well with each other (r 2 = 0.85), but varied widely (range, 91% of mean estimate; median estimate, 11 mL; range of estimated ranges, 0.2-68 mL). Agreements (κ) between automated ratings and consensus ratings were 0.60 (Wahlund system) and 0.64 (van Swieten system) compared with agreements between individual pairs of experts of 0.51 and 0.67, respectively, for the two rating systems (P < .01 for Wahlund system comparison of agreements). Accuracy was unaffected by established infarction, acute ischemic changes, or atrophy (P > .05). Automated preprocessing failure rate was 4%; rating errors occurred in a further 4%. Total automated processing time averaged 109 seconds (range, 79-140 seconds). Conclusion An automated method for quantifying CT cerebral white matter lesions achieves a similar accuracy to experts in unselected and multicenter cohorts. © RSNA, 2018 Online supplemental material is available for this article.
Kersemans, Veerle; Kannan, Pavitra; Beech, John S.; Bates, Russell; Irving, Benjamin; Gilchrist, Stuart; Allen, Philip D.; Thompson, James; Kinchesh, Paul; Casteleyn, Christophe; Schnabel, Julia; Partridge, Mike; Muschel, Ruth J.; Smart, Sean C.
2015-01-01
Introduction Preclinical in vivo CT is commonly used to visualise vessels at a macroscopic scale. However, it is prone to many artefacts which can degrade the quality of CT images significantly. Although some artefacts can be partially corrected for during image processing, they are best avoided during acquisition. Here, a novel imaging cradle and tumour holder was designed to maximise CT resolution. This approach was used to improve preclinical in vivo imaging of the tumour vasculature. Procedures A custom built cradle containing a tumour holder was developed and fix-mounted to the CT system gantry to avoid artefacts arising from scanner vibrations and out-of-field sample positioning. The tumour holder separated the tumour from bones along the axis of rotation of the CT scanner to avoid bone-streaking. It also kept the tumour stationary and insensitive to respiratory motion. System performance was evaluated in terms of tumour immobilisation and reduction of motion and bone artefacts. Pre- and post-contrast CT followed by sequential DCE-MRI of the tumour vasculature in xenograft transplanted mice was performed to confirm vessel patency and demonstrate the multimodal capacity of the new cradle. Vessel characteristics such as diameter, and branching were quantified. Results Image artefacts originating from bones and out-of-field sample positioning were avoided whilst those resulting from motions were reduced significantly, thereby maximising the resolution that can be achieved with CT imaging in vivo. Tumour vessels ≥ 77 μm could be resolved and blood flow to the tumour remained functional. The diameter of each tumour vessel was determined and plotted as histograms and vessel branching maps were created. Multimodal imaging using this cradle assembly was preserved and demonstrated. Conclusions The presented imaging workflow minimised image artefacts arising from scanner induced vibrations, respiratory motion and radiopaque structures and enabled in vivo CT imaging and quantitative analysis of the tumour vasculature at higher resolution than was possible before. Moreover, it can be applied in a multimodal setting, therefore combining anatomical and dynamic information. PMID:26046526
Gregg, Chelsea L; Recknagel, Andrew K; Butcher, Jonathan T
2015-01-01
Tissue morphogenesis and embryonic development are dynamic events challenging to quantify, especially considering the intricate events that happen simultaneously in different locations and time. Micro- and more recently nano-computed tomography (micro/nanoCT) has been used for the past 15 years to characterize large 3D fields of tortuous geometries at high spatial resolution. We and others have advanced micro/nanoCT imaging strategies for quantifying tissue- and organ-level fate changes throughout morphogenesis. Exogenous soft tissue contrast media enables visualization of vascular lumens and tissues via extravasation. Furthermore, the emergence of antigen-specific tissue contrast enables direct quantitative visualization of protein and mRNA expression. Micro-CT X-ray doses appear to be non-embryotoxic, enabling longitudinal imaging studies in live embryos. In this chapter we present established soft tissue contrast protocols for obtaining high-quality micro/nanoCT images and the image processing techniques useful for quantifying anatomical and physiological information from the data sets.
Evaluation of the OSC-TV iterative reconstruction algorithm for cone-beam optical CT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Matenine, Dmitri, E-mail: dmitri.matenine.1@ulaval.ca; Mascolo-Fortin, Julia, E-mail: julia.mascolo-fortin.1@ulaval.ca; Goussard, Yves, E-mail: yves.goussard@polymtl.ca
Purpose: The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. Methods: This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numericalmore » simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. Results: The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. Conclusions: The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of spatial features and reduce cone-beam optical CT artifacts.« less
Evaluation of the OSC-TV iterative reconstruction algorithm for cone-beam optical CT.
Matenine, Dmitri; Mascolo-Fortin, Julia; Goussard, Yves; Després, Philippe
2015-11-01
The present work evaluates an iterative reconstruction approach, namely, the ordered subsets convex (OSC) algorithm with regularization via total variation (TV) minimization in the field of cone-beam optical computed tomography (optical CT). One of the uses of optical CT is gel-based 3D dosimetry for radiation therapy, where it is employed to map dose distributions in radiosensitive gels. Model-based iterative reconstruction may improve optical CT image quality and contribute to a wider use of optical CT in clinical gel dosimetry. This algorithm was evaluated using experimental data acquired by a cone-beam optical CT system, as well as complementary numerical simulations. A fast GPU implementation of OSC-TV was used to achieve reconstruction times comparable to those of conventional filtered backprojection. Images obtained via OSC-TV were compared with the corresponding filtered backprojections. Spatial resolution and uniformity phantoms were scanned and respective reconstructions were subject to evaluation of the modulation transfer function, image uniformity, and accuracy. The artifacts due to refraction and total signal loss from opaque objects were also studied. The cone-beam optical CT data reconstructions showed that OSC-TV outperforms filtered backprojection in terms of image quality, thanks to a model-based simulation of the photon attenuation process. It was shown to significantly improve the image spatial resolution and reduce image noise. The accuracy of the estimation of linear attenuation coefficients remained similar to that obtained via filtered backprojection. Certain image artifacts due to opaque objects were reduced. Nevertheless, the common artifact due to the gel container walls could not be eliminated. The use of iterative reconstruction improves cone-beam optical CT image quality in many ways. The comparisons between OSC-TV and filtered backprojection presented in this paper demonstrate that OSC-TV can potentially improve the rendering of spatial features and reduce cone-beam optical CT artifacts.
TBIdoc: 3D content-based CT image retrieval system for traumatic brain injury
NASA Astrophysics Data System (ADS)
Li, Shimiao; Gong, Tianxia; Wang, Jie; Liu, Ruizhe; Tan, Chew Lim; Leong, Tze Yun; Pang, Boon Chuan; Lim, C. C. Tchoyoson; Lee, Cheng Kiang; Tian, Qi; Zhang, Zhuo
2010-03-01
Traumatic brain injury (TBI) is a major cause of death and disability. Computed Tomography (CT) scan is widely used in the diagnosis of TBI. Nowadays, large amount of TBI CT data is stacked in the hospital radiology department. Such data and the associated patient information contain valuable information for clinical diagnosis and outcome prediction. However, current hospital database system does not provide an efficient and intuitive tool for doctors to search out cases relevant to the current study case. In this paper, we present the TBIdoc system: a content-based image retrieval (CBIR) system which works on the TBI CT images. In this web-based system, user can query by uploading CT image slices from one study, retrieval result is a list of TBI cases ranked according to their 3D visual similarity to the query case. Specifically, cases of TBI CT images often present diffuse or focal lesions. In TBIdoc system, these pathological image features are represented as bin-based binary feature vectors. We use the Jaccard-Needham measure as the similarity measurement. Based on these, we propose a 3D similarity measure for computing the similarity score between two series of CT slices. nDCG is used to evaluate the system performance, which shows the system produces satisfactory retrieval results. The system is expected to improve the current hospital data management in TBI and to give better support for the clinical decision-making process. It may also contribute to the computer-aided education in TBI.
NASA Astrophysics Data System (ADS)
Gillen, Rebecca; Firbank, Michael J.; Lloyd, Jim; O'Brien, John T.
2015-09-01
This study investigated if the appearance and diagnostic accuracy of HMPAO brain perfusion SPECT images could be improved by using CT-based attenuation and scatter correction compared with the uniform attenuation correction method. A cohort of subjects who were clinically categorized as Alzheimer’s Disease (n=38 ), Dementia with Lewy Bodies (n=29 ) or healthy normal controls (n=30 ), underwent SPECT imaging with Tc-99m HMPAO and a separate CT scan. The SPECT images were processed using: (a) correction map derived from the subject’s CT scan or (b) the Chang uniform approximation for correction or (c) no attenuation correction. Images were visually inspected. The ratios between key regions of interest known to be affected or spared in each condition were calculated for each correction method, and the differences between these ratios were evaluated. The images produced using the different corrections were noted to be visually different. However, ROI analysis found similar statistically significant differences between control and dementia groups and between AD and DLB groups regardless of the correction map used. We did not identify an improvement in diagnostic accuracy in images which were corrected using CT-based attenuation and scatter correction, compared with those corrected using a uniform correction map.
NASA Astrophysics Data System (ADS)
Ghiorso, M. S.
2014-12-01
Computational thermodynamics (CT) represents a collection of numerical techniques that are used to calculate quantitative results from thermodynamic theory. In the Earth sciences, CT is most often applied to estimate the equilibrium properties of solutions, to calculate phase equilibria from models of the thermodynamic properties of materials, and to approximate irreversible reaction pathways by modeling these as a series of local equilibrium steps. The thermodynamic models that underlie CT calculations relate the energy of a phase to temperature, pressure and composition. These relationships are not intuitive and they are seldom well constrained by experimental data; often, intuition must be applied to generate a robust model that satisfies the expectations of use. As a consequence of this situation, the models and databases the support CT applications in geochemistry and petrology are tedious to maintain as new data and observations arise. What is required to make the process more streamlined and responsive is a computational framework that permits the rapid generation of observable outcomes from the underlying data/model collections, and importantly, the ability to update and re-parameterize the constitutive models through direct manipulation of those outcomes. CT procedures that take models/data to the experiential reference frame of phase equilibria involve function minimization, gradient evaluation, the calculation of implicit lines, curves and surfaces, contour extraction, and other related geometrical measures. All these procedures are the mainstay of image processing analysis. Since the commercial escalation of video game technology, open source image processing libraries have emerged (e.g., VTK) that permit real time manipulation and analysis of images. These tools find immediate application to CT calculations of phase equilibria by permitting rapid calculation and real time feedback between model outcome and the underlying model parameters.
A Shearlet-based algorithm for quantum noise removal in low-dose CT images
NASA Astrophysics Data System (ADS)
Zhang, Aguan; Jiang, Huiqin; Ma, Ling; Liu, Yumin; Yang, Xiaopeng
2016-03-01
Low-dose CT (LDCT) scanning is a potential way to reduce the radiation exposure of X-ray in the population. It is necessary to improve the quality of low-dose CT images. In this paper, we propose an effective algorithm for quantum noise removal in LDCT images using shearlet transform. Because the quantum noise can be simulated by Poisson process, we first transform the quantum noise by using anscombe variance stabilizing transform (VST), producing an approximately Gaussian noise with unitary variance. Second, the non-noise shearlet coefficients are obtained by adaptive hard-threshold processing in shearlet domain. Third, we reconstruct the de-noised image using the inverse shearlet transform. Finally, an anscombe inverse transform is applied to the de-noised image, which can produce the improved image. The main contribution is to combine the anscombe VST with the shearlet transform. By this way, edge coefficients and noise coefficients can be separated from high frequency sub-bands effectively. A number of experiments are performed over some LDCT images by using the proposed method. Both quantitative and visual results show that the proposed method can effectively reduce the quantum noise while enhancing the subtle details. It has certain value in clinical application.
Koyuncu, Hasan; Ceylan, Rahime
2018-04-01
Dynamic Contrast-Enhanced Computed Tomography (DCE-CT) is applied to observe adrenal tumours in detail by utilising from the contrast matter, which generally brings the tumour into the forefront. However, DCE-CT images are generally influenced by noises that occur as the result of the trade-off between radiation doses vs. noise. Herein, this situation constitutes a challenge in the achievement of accurate tumour segmentation. In CT images, most of the noises are similar to Gaussian Noise. In this study, arterial phase CT images containing adrenal tumours are utilised, and elimination of Gaussian Noise is realised by fourteen different techniques reported in literature for the achievement of the best denoising process. In this study, the Block Matching and 3D Filtering (BM3D) algorithm typically achieve reliable Peak Signal-to-Noise Ratios (PSNR) and resolves challenges of similar techniques when addressing different levels of noise. Furthermore, BM3D obtains the best mean PSNR values among the first five techniques. BM3D outperforms to other techniques by obtaining better Total Statistical Success (TSS), CPU time and computation cost. Consequently, it prepares clearer arterial phase CT images for the next step (segmentation of adrenal tumours). Copyright © 2017 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pasciak, A; Kao, J
2014-06-15
Purpose The process of converting Yttrium-90 (Y90) PET/CT images into 3D absorbed dose maps will be explained. The simple methods presented will allow the medical physicst to analyze Y90 PET images following radioembolization and determine the absorbed dose to tumor, normal liver parenchyma and other areas of interest, without application of Monte-Carlo radiation transport or dose-point-kernel (DPK) convolution. Methods Absorbed dose can be computed from Y90 PET/CT images based on the premise that radioembolization is a permanent implant with a constant relative activity distribution after infusion. Many Y90 PET/CT publications have used DPK convolution to obtain 3D absorbed dose maps.more » However, this method requires specialized software limiting clinical utility. The Local Deposition method, an alternative to DPK convolution, can be used to obtain absorbed dose and requires no additional computer processing. Pixel values from regions of interest drawn on Y90 PET/CT images can be converted to absorbed dose (Gy) by multiplication with a scalar constant. Results There is evidence that suggests the Local Deposition method may actually be more accurate than DPK convolution and it has been successfully used in a recent Y90 PET/CT publication. We have analytically compared dose-volume-histograms (DVH) for phantom hot-spheres to determine the difference between the DPK and Local Deposition methods, as a function of PET scanner point-spread-function for Y90. We have found that for PET/CT systems with a FWHM greater than 3.0 mm when imaging Y90, the Local Deposition Method provides a more accurate representation of DVH, regardless of target size than DPK convolution. Conclusion Using the Local Deposition Method, post-radioembolization Y90 PET/CT images can be transformed into 3D absorbed dose maps of the liver. An interventional radiologist or a Medical Physicist can perform this transformation in a clinical setting, allowing for rapid prediction of treatment efficacy by comparison to published tumoricidal thresholds.« less
Truong, Quynh A.; Thai, Wai-ee; Wai, Bryan; Cordaro, Kevin; Cheng, Teresa; Beaudoin, Jonathan; Xiong, Guanglei; Cheung, Jim W.; Altman, Robert; Min, James K.; Singh, Jagmeet P.; Barrett, Conor D.; Danik, Stephan
2015-01-01
Background Myocardial scar is a substrate for ventricular tachycardia and sudden cardiac death. Late enhancement computed tomography (CT) imaging can detect scar, but it remains unclear whether newer late enhancement dual-energy (LE-DECT) acquisition has benefit over standard single-energy late enhancement (LE-CT). Objective We aim to compare late enhancement CT using newer LE-DECT acquisition and single-energy LE-CT acquisitions to pathology and electroanatomical map (EAM) in an experimental chronic myocardial infarction (MI) porcine study. Methods In 8 chronic MI pigs (59±5 kg), we performed dual-source CT, EAM, and pathology. For CT imaging, we performed 3 acquisitions at 10 minutes post-contrast: LE-CT 80 kV, LE-CT 100 kV, and LE-DECT with two post-processing software settings. Results Of the sequences, LE-CT 100 kV provided the best contrast-to-noise ratio (all p≤0.03) and correlation to pathology for scar (ρ=0.88). While LE-DECT overestimated scar (both p=0.02), LE-CT images did not (both p=0.08). On a segment basis (n=136), all CT sequences had high specificity (87–93%) and modest sensitivity (50–67%), with LE-CT 100 kV having the highest specificity of 93% for scar detection compared to pathology and agreement with EAM (κ 0.69). Conclusions Standard single-energy LE-CT, particularly 100kV, matched better to pathology and EAM than dual-energy LE-DECT for scar detection. Larger human trials as well as more technical-based studies that optimize varying different energies with newer hardware and software are warranted. PMID:25977115
Niska, Jared A.; Meganck, Jeffrey A.; Pribaz, Jonathan R.; Shahbazian, Jonathan H.; Lim, Ed; Zhang, Ning; Rice, Brad W.; Akin, Ali; Ramos, Romela Irene; Bernthal, Nicholas M.; Francis, Kevin P.; Miller, Lloyd S.
2012-01-01
Background Recent advances in non-invasive optical, radiographic and μCT imaging provide an opportunity to monitor biological processes longitudinally in an anatomical context. One particularly relevant application for combining these modalities is to study orthopaedic implant infections. These infections are characterized by the formation of persistent bacterial biofilms on the implanted materials, causing inflammation, periprosthetic osteolysis, osteomyelitis, and bone damage, resulting in implant loosening and failure. Methodology/Principal Findings An orthopaedic implant infection model was used in which a titanium Kirshner-wire was surgically placed in femurs of LysEGFP mice, which possess EGFP-fluorescent neutrophils, and a bioluminescent S. aureus strain (Xen29; 1×103 CFUs) was inoculated in the knee joint before closure. In vivo bioluminescent, fluorescent, X-ray and μCT imaging were performed on various postoperative days. The bacterial bioluminescent signals of the S. aureus-infected mice peaked on day 19, before decreasing to a basal level of light, which remained measurable for the entire 48 day experiment. Neutrophil EGFP-fluorescent signals of the S. aureus-infected mice were statistically greater than uninfected mice on days 2 and 5, but afterwards the signals for both groups approached background levels of detection. To visualize the three-dimensional location of the bacterial infection and neutrophil infiltration, a diffuse optical tomography reconstruction algorithm was used to co-register the bioluminescent and fluorescent signals with μCT images. To quantify the anatomical bone changes on the μCT images, the outer bone volume of the distal femurs were measured using a semi-automated contour based segmentation process. The outer bone volume increased through day 48, indicating that bone damage continued during the implant infection. Conclusions/Significance Bioluminescent and fluorescent optical imaging was combined with X-ray and μCT imaging to provide noninvasive and longitudinal measurements of the dynamic changes in bacterial burden, neutrophil recruitment and bone damage in a mouse orthopaedic implant infection model. PMID:23082163
DOE Office of Scientific and Technical Information (OSTI.GOV)
NONE
2011-02-15
Purpose: The development of computer-aided diagnostic (CAD) methods for lung nodule detection, classification, and quantitative assessment can be facilitated through a well-characterized repository of computed tomography (CT) scans. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI) completed such a database, establishing a publicly available reference for the medical imaging research community. Initiated by the National Cancer Institute (NCI), further advanced by the Foundation for the National Institutes of Health (FNIH), and accompanied by the Food and Drug Administration (FDA) through active participation, this public-private partnership demonstrates the success of a consortium founded on a consensus-based process.more » Methods: Seven academic centers and eight medical imaging companies collaborated to identify, address, and resolve challenging organizational, technical, and clinical issues to provide a solid foundation for a robust database. The LIDC/IDRI Database contains 1018 cases, each of which includes images from a clinical thoracic CT scan and an associated XML file that records the results of a two-phase image annotation process performed by four experienced thoracic radiologists. In the initial blinded-read phase, each radiologist independently reviewed each CT scan and marked lesions belonging to one of three categories (''nodule{>=}3 mm,''''nodule<3 mm,'' and ''non-nodule{>=}3 mm''). In the subsequent unblinded-read phase, each radiologist independently reviewed their own marks along with the anonymized marks of the three other radiologists to render a final opinion. The goal of this process was to identify as completely as possible all lung nodules in each CT scan without requiring forced consensus. Results: The Database contains 7371 lesions marked ''nodule'' by at least one radiologist. 2669 of these lesions were marked ''nodule{>=}3 mm'' by at least one radiologist, of which 928 (34.7%) received such marks from all four radiologists. These 2669 lesions include nodule outlines and subjective nodule characteristic ratings. Conclusions: The LIDC/IDRI Database is expected to provide an essential medical imaging research resource to spur CAD development, validation, and dissemination in clinical practice.« less
CT imaging spectrum of infiltrative renal diseases.
Ballard, David H; De Alba, Luis; Migliaro, Matias; Previgliano, Carlos H; Sangster, Guillermo P
2017-11-01
Most renal lesions replace the renal parenchyma as a focal space-occupying mass with borders distinguishing the mass from normal parenchyma. However, some renal lesions exhibit interstitial infiltration-a process that permeates the renal parenchyma by using the normal renal architecture for growth. These infiltrative lesions frequently show nonspecific patterns that lead to little or no contour deformity and have ill-defined borders on CT, making detection and diagnosis challenging. The purpose of this pictorial essay is to describe the CT imaging findings of various conditions that may manifest as infiltrative renal lesions.
Processing of CT images for analysis of diffuse lung disease in the lung tissue research consortium
NASA Astrophysics Data System (ADS)
Karwoski, Ronald A.; Bartholmai, Brian; Zavaletta, Vanessa A.; Holmes, David; Robb, Richard A.
2008-03-01
The goal of Lung Tissue Resource Consortium (LTRC) is to improve the management of diffuse lung diseases through a better understanding of the biology of Chronic Obstructive Pulmonary Disease (COPD) and fibrotic interstitial lung disease (ILD) including Idiopathic Pulmonary Fibrosis (IPF). Participants are subjected to a battery of tests including tissue biopsies, physiologic testing, clinical history reporting, and CT scanning of the chest. The LTRC is a repository from which investigators can request tissue specimens and test results as well as semi-quantitative radiology reports, pathology reports, and automated quantitative image analysis results from the CT scan data performed by the LTRC core laboratories. The LTRC Radiology Core Laboratory (RCL), in conjunction with the Biomedical Imaging Resource (BIR), has developed novel processing methods for comprehensive characterization of pulmonary processes on volumetric high-resolution CT scans to quantify how these diseases manifest in radiographic images. Specifically, the RCL has implemented a semi-automated method for segmenting the anatomical regions of the lungs and airways. In these anatomic regions, automated quantification of pathologic features of disease including emphysema volumes and tissue classification are performed using both threshold techniques and advanced texture measures to determine the extent and location of emphysema, ground glass opacities, "honeycombing" (HC) and "irregular linear" or "reticular" pulmonary infiltrates and normal lung. Wall thickness measurements of the trachea, and its branches to the 3 rd and limited 4 th order are also computed. The methods for processing, segmentation and quantification are described. The results are reviewed and verified by an expert radiologist following processing and stored in the public LTRC database for use by pulmonary researchers. To date, over 1200 CT scans have been processed by the RCL and the LTRC project is on target for recruitment of the 2200 patients with 1800 CT scans in the repository for the 5-year effort. Ongoing analysis of the results in the LTRC database by the LTRC participating institutions and outside investigators are underway to look at the clinical and physiological significance of the imaging features of these diseases and correlate these findings with quality of life and other important prognostic indicators of severity. In the future, the quantitative measures of disease may have greater utility by showing correlation with prognosis, disease severity and other physiological parameters. These imaging features may provide non-invasive alternative endpoints or surrogate markers to alleviate the need for tissue biopsy or provide an accurate means to monitor rate of disease progression or response to therapy.
Three-dimensional analysis of alveolar bone resorption by image processing of 3-D dental CT images
NASA Astrophysics Data System (ADS)
Nagao, Jiro; Kitasaka, Takayuki; Mori, Kensaku; Suenaga, Yasuhito; Yamada, Shohzoh; Naitoh, Munetaka
2006-03-01
We have developed a novel system that provides total support for assessment of alveolar bone resorption, caused by periodontitis, based on three-dimensional (3-D) dental CT images. In spite of the difficulty in perceiving the complex 3-D shape of resorption, dentists assessing resorption location and severity have been relying on two-dimensional radiography and probing, which merely provides one-dimensional information (depth) about resorption shape. However, there has been little work on assisting assessment of the disease by 3-D image processing and visualization techniques. This work provides quantitative evaluation results and figures for our system that measures the three-dimensional shape and spread of resorption. It has the following functions: (1) measures the depth of resorption by virtually simulating probing in the 3-D CT images, taking advantage of image processing of not suffering obstruction by teeth on the inter-proximal sides and much smaller measurement intervals than the conventional examination; (2) visualizes the disposition of the depth by movies and graphs; (3) produces a quantitative index and intuitive visual representation of the spread of resorption in the inter-radicular region in terms of area; and (4) calculates the volume of resorption as another severity index in the inter-radicular region and the region outside it. Experimental results in two cases of 3-D dental CT images and a comparison of the results with the clinical examination results and experts' measurements of the corresponding patients confirmed that the proposed system gives satisfying results, including 0.1 to 0.6mm of resorption measurement (probing) error and fairly intuitive presentation of measurement and calculation results.
Neves, A A; Silva, E J; Roter, J M; Belladona, F G; Alves, H D; Lopes, R T; Paciornik, S; De-Deus, G A
2015-11-01
To propose an automated image processing routine based on free software to quantify root canal preparation outcomes in pairs of sound and instrumented roots after micro-CT scanning procedures. Seven mesial roots of human mandibular molars with different canal configuration systems were studied: (i) Vertucci's type 1, (ii) Vertucci's type 2, (iii) two individual canals, (iv) Vertucci's type 6, canals (v) with and (vi) without debris, and (vii) canal with visible pulp calcification. All teeth were instrumented with the BioRaCe system and scanned in a Skyscan 1173 micro-CT before and after canal preparation. After reconstruction, the instrumented stack of images (IS) was registered against the preoperative sound stack of images (SS). Image processing included contrast equalization and noise filtering. Sound canal volumes were obtained by a minimum threshold. For the IS, a fixed conservative threshold was chosen as the best compromise between instrumented canal and dentine whilst avoiding debris, resulting in instrumented canal plus empty spaces. Arithmetic and logical operations between sound and instrumented stacks were used to identify debris. Noninstrumented dentine was calculated using a minimum threshold in the IS and subtracting from the SS and total debris. Removed dentine volume was obtained by subtracting SS from IS. Quantitative data on total debris present in the root canal space after instrumentation, noninstrumented areas and removed dentine volume were obtained for each test case, as well as three-dimensional volume renderings. After standardization of acquisition, reconstruction and image processing micro-CT images, a quantitative approach for calculation of root canal biomechanical outcomes was achieved using free software. © 2014 International Endodontic Journal. Published by John Wiley & Sons Ltd.
Second cancers discovered by (18)FDG PET/CT imaging for choroidal melanoma.
Chin, Kimberly; Finger, Paul T; Kurli, Madhavi; Tena, Lawrence B; Reddy, Shantan
2007-08-01
Positron-emission tomography/computed tomography (PET/CT) is a unique imaging tool that aids in the detection of cancerous lesions. It is currently and widely used for cancer staging (both initial and follow-up). Here we report our findings of second primary cancers incidentally discovered during PET/CT staging of patients with choroidal melanomas. We performed a retrospective case review of 139 patients with uveal melanoma who were subsequently evaluated by whole-body [18-fluorine-labeled] 2-deoxy-2-fluoro-D-glucose ((18)FDG) PET/CT imaging. In this series, 93 were scanned before treatment and 46 during the course of their follow-up systemic examinations. Their mean follow-up was 50.9 months. Six patients (4.3%) had second primary cancers revealed by PET/CT imaging. Three patients (50%) were synchronous (found at initial staging), and the remaining 3 patients (50%) were metachronous (found at follow-up staging). Second primary cancers were found in the lung, breast, uterus, colon, and thyroid. Although whole-body PET/CT scans were ordered as part of the staging process of patients with diagnosed choroidal melanoma, both synchronous and metachronous second primary cancers were found. PET/CT has become an indispensable tool for staging, diagnosis, and treatment planning for choroidal melanoma. The possibility of detecting second primary cancers should also be considered valuable.
Shading correction assisted iterative cone-beam CT reconstruction
NASA Astrophysics Data System (ADS)
Yang, Chunlin; Wu, Pengwei; Gong, Shutao; Wang, Jing; Lyu, Qihui; Tang, Xiangyang; Niu, Tianye
2017-11-01
Recent advances in total variation (TV) technology enable accurate CT image reconstruction from highly under-sampled and noisy projection data. The standard iterative reconstruction algorithms, which work well in conventional CT imaging, fail to perform as expected in cone beam CT (CBCT) applications, wherein the non-ideal physics issues, including scatter and beam hardening, are more severe. These physics issues result in large areas of shading artifacts and cause deterioration to the piecewise constant property assumed in reconstructed images. To overcome this obstacle, we incorporate a shading correction scheme into low-dose CBCT reconstruction and propose a clinically acceptable and stable three-dimensional iterative reconstruction method that is referred to as the shading correction assisted iterative reconstruction. In the proposed method, we modify the TV regularization term by adding a shading compensation image to the reconstructed image to compensate for the shading artifacts while leaving the data fidelity term intact. This compensation image is generated empirically, using image segmentation and low-pass filtering, and updated in the iterative process whenever necessary. When the compensation image is determined, the objective function is minimized using the fast iterative shrinkage-thresholding algorithm accelerated on a graphic processing unit. The proposed method is evaluated using CBCT projection data of the Catphan© 600 phantom and two pelvis patients. Compared with the iterative reconstruction without shading correction, the proposed method reduces the overall CT number error from around 200 HU to be around 25 HU and increases the spatial uniformity by a factor of 20 percent, given the same number of sparsely sampled projections. A clinically acceptable and stable iterative reconstruction algorithm for CBCT is proposed in this paper. Differing from the existing algorithms, this algorithm incorporates a shading correction scheme into the low-dose CBCT reconstruction and achieves more stable optimization path and more clinically acceptable reconstructed image. The method proposed by us does not rely on prior information and thus is practically attractive to the applications of low-dose CBCT imaging in the clinic.
Improving Low-dose Cardiac CT Images based on 3D Sparse Representation
NASA Astrophysics Data System (ADS)
Shi, Luyao; Hu, Yining; Chen, Yang; Yin, Xindao; Shu, Huazhong; Luo, Limin; Coatrieux, Jean-Louis
2016-03-01
Cardiac computed tomography (CCT) is a reliable and accurate tool for diagnosis of coronary artery diseases and is also frequently used in surgery guidance. Low-dose scans should be considered in order to alleviate the harm to patients caused by X-ray radiation. However, low dose CT (LDCT) images tend to be degraded by quantum noise and streak artifacts. In order to improve the cardiac LDCT image quality, a 3D sparse representation-based processing (3D SR) is proposed by exploiting the sparsity and regularity of 3D anatomical features in CCT. The proposed method was evaluated by a clinical study of 14 patients. The performance of the proposed method was compared to the 2D spares representation-based processing (2D SR) and the state-of-the-art noise reduction algorithm BM4D. The visual assessment, quantitative assessment and qualitative assessment results show that the proposed approach can lead to effective noise/artifact suppression and detail preservation. Compared to the other two tested methods, 3D SR method can obtain results with image quality most close to the reference standard dose CT (SDCT) images.
NASA Astrophysics Data System (ADS)
Zhou, Xiangrong; Morita, Syoichi; Zhou, Xinxin; Chen, Huayue; Hara, Takeshi; Yokoyama, Ryujiro; Kanematsu, Masayuki; Hoshi, Hiroaki; Fujita, Hiroshi
2015-03-01
This paper describes an automatic approach for anatomy partitioning on three-dimensional (3D) computedtomography (CT) images that divide the human torso into several volume-of-interesting (VOI) images based on anatomical definition. The proposed approach combines several individual detections of organ-location with a groupwise organ-location calibration and correction to achieve an automatic and robust multiple-organ localization task. The essence of the proposed method is to jointly detect the 3D minimum bounding box for each type of organ shown on CT images based on intra-organ-image-textures and inter-organ-spatial-relationship in the anatomy. Machine-learning-based template matching and generalized Hough transform-based point-distribution estimation are used in the detection and calibration processes. We apply this approach to the automatic partitioning of a torso region on CT images, which are divided into 35 VOIs presenting major organ regions and tissues required by routine diagnosis in clinical medicine. A database containing 4,300 patient cases of high-resolution 3D torso CT images is used for training and performance evaluations. We confirmed that the proposed method was successful in target organ localization on more than 95% of CT cases. Only two organs (gallbladder and pancreas) showed a lower success rate: 71 and 78% respectively. In addition, we applied this approach to another database that included 287 patient cases of whole-body CT images scanned for positron emission tomography (PET) studies and used for additional performance evaluation. The experimental results showed that no significant difference between the anatomy partitioning results from those two databases except regarding the spleen. All experimental results showed that the proposed approach was efficient and useful in accomplishing localization tasks for major organs and tissues on CT images scanned using different protocols.
Sun, Yajuan; Yu, Hongjuan; Ma, Jingquan
2016-01-01
Objective The aim of our study was to evaluate the role of 18F-FDG PET/CT integrated imaging in differentiating malignant from benign pleural effusion. Methods A total of 176 patients with pleural effusion who underwent 18F-FDG PET/CT examination to differentiate malignancy from benignancy were retrospectively researched. The images of CT imaging, 18F-FDG PET imaging and 18F-FDG PET/CT integrated imaging were visually analyzed. The suspected malignant effusion was characterized by the presence of nodular or irregular pleural thickening on CT imaging. Whereas on PET imaging, pleural 18F-FDG uptake higher than mediastinal activity was interpreted as malignant effusion. Images of 18F-FDG PET/CT integrated imaging were interpreted by combining the morphologic feature of pleura on CT imaging with the degree and form of pleural 18F-FDG uptake on PET imaging. Results One hundred and eight patients had malignant effusion, including 86 with pleural metastasis and 22 with pleural mesothelioma, whereas 68 patients had benign effusion. The sensitivities of CT imaging, 18F-FDG PET imaging and 18F-FDG PET/CT integrated imaging in detecting malignant effusion were 75.0%, 91.7% and 93.5%, respectively, which were 69.8%, 91.9% and 93.0% in distinguishing metastatic effusion. The sensitivity of 18F-FDG PET/CT integrated imaging in detecting malignant effusion was higher than that of CT imaging (p = 0.000). For metastatic effusion, 18F-FDG PET imaging had higher sensitivity (p = 0.000) and better diagnostic consistency with 18F-FDG PET/CT integrated imaging compared with CT imaging (Kappa = 0.917 and Kappa = 0.295, respectively). The specificities of CT imaging, 18F-FDG PET imaging and 18F-FDG PET/CT integrated imaging were 94.1%, 63.2% and 92.6% in detecting benign effusion. The specificities of CT imaging and 18F-FDG PET/CT integrated imaging were higher than that of 18F-FDG PET imaging (p = 0.000 and p = 0.000, respectively), and CT imaging had better diagnostic consistency with 18F-FDG PET/CT integrated imaging compared with 18F-FDG PET imaging (Kappa = 0.881 and Kappa = 0.240, respectively). Conclusion 18F-FDG PET/CT integrated imaging is a more reliable modality in distinguishing malignant from benign pleural effusion than 18F-FDG PET imaging and CT imaging alone. For image interpretation of 18F-FDG PET/CT integrated imaging, the PET and CT portions play a major diagnostic role in identifying metastatic effusion and benign effusion, respectively. PMID:27560933
A method for smoothing segmented lung boundary in chest CT images
NASA Astrophysics Data System (ADS)
Yim, Yeny; Hong, Helen
2007-03-01
To segment low density lung regions in chest CT images, most of methods use the difference in gray-level value of pixels. However, radiodense pulmonary vessels and pleural nodules that contact with the surrounding anatomy are often excluded from the segmentation result. To smooth lung boundary segmented by gray-level processing in chest CT images, we propose a new method using scan line search. Our method consists of three main steps. First, lung boundary is extracted by our automatic segmentation method. Second, segmented lung contour is smoothed in each axial CT slice. We propose a scan line search to track the points on lung contour and find rapidly changing curvature efficiently. Finally, to provide consistent appearance between lung contours in adjacent axial slices, 2D closing in coronal plane is applied within pre-defined subvolume. Our method has been applied for performance evaluation with the aspects of visual inspection, accuracy and processing time. The results of our method show that the smoothness of lung contour was considerably increased by compensating for pulmonary vessels and pleural nodules.
Nesterets, Yakov I; Gureyev, Timur E; Mayo, Sheridan C; Stevenson, Andrew W; Thompson, Darren; Brown, Jeremy M C; Kitchen, Marcus J; Pavlov, Konstantin M; Lockie, Darren; Brun, Francesco; Tromba, Giuliana
2015-11-01
Results are presented of a recent experiment at the Imaging and Medical beamline of the Australian Synchrotron intended to contribute to the implementation of low-dose high-sensitivity three-dimensional mammographic phase-contrast imaging, initially at synchrotrons and subsequently in hospitals and medical imaging clinics. The effect of such imaging parameters as X-ray energy, source size, detector resolution, sample-to-detector distance, scanning and data processing strategies in the case of propagation-based phase-contrast computed tomography (CT) have been tested, quantified, evaluated and optimized using a plastic phantom simulating relevant breast-tissue characteristics. Analysis of the data collected using a Hamamatsu CMOS Flat Panel Sensor, with a pixel size of 100 µm, revealed the presence of propagation-based phase contrast and demonstrated significant improvement of the quality of phase-contrast CT imaging compared with conventional (absorption-based) CT, at medically acceptable radiation doses.
WE-E-18C-01: Multi-Energy CT: Current Status and Recent Innovations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pelc, N; McCollough, C; Yu, L
2014-06-15
Conventional computed tomography (CT) uses a single polychromatic x-ray spectrum and energy integrating detectors, and produces images whose contrast depends on the effective attenuation coefficient of the broad spectrum beam. This can introduce errors from beam hardening and does not produce the optimal contrast-to-noise ratio. In addition, multiple materials can have the same effective attenuation coefficient, causing different materials to be indistinguishable in conventional CT images. If transmission measurements at two or more energies are obtained, even with polychromatic beams, more specific information about the object can be obtained. If the object does not contain materials with k-edges in themore » spectrum, the x-ray attenuation can be well-approximated by a linear combination of two processes (photoelectric absorption and Compton scattering) or, equivalently, two basis materials. For such cases, two spectral measurements suffice, although additional measurements can provide higher precision. If K-edge materials are present, additional spectral measurements can allow these materials to be isolated. Current commercial implementations use varied approaches, including two sources operating a different kVp, one source whose kVp is rapidly switched in a single scan, and a dual layer detector that can provide spectral information in every reading. Processing of the spectral information can be performed in the raw data domain or in the image domain. The process of calculating the amount of the two basis functions implicitly corrects for beam hardening and therefore can lead to improvements in quantitative accuracy. Information can be extracted to provide material specific information beyond that of conventional CT. This additional information has been shown to be important in several clinical applications, and can also lead to more efficient clinical protocols. Recent innovations in x-ray sources, detectors, and systems have made multi-energy CT much more practical and improved its performance. In addition, this is a very active area of research and further improvements are expected through further technological improvements. Learning Objectives: Basic principles of multi-energy CT Current implementations of mutli-energy CT Data and image analysis methods in multi-energy CT Current clinical applications of dual energy CT5. recent innovations and anticipated advances in multi-energy CT.« less
Low-dose CT in clinical diagnostics.
Fuentes-Orrego, Jorge M; Sahani, Dushyant V
2013-09-01
Computed tomography (CT) has become key for patient management due to its outstanding capabilities for detecting disease processes and assessing treatment response, which has led to expansion in CT imaging for diagnostic and image-guided therapeutic interventions. Despite these benefits, the growing use of CT has raised concerns as radiation risks associated with radiation exposure. The purpose of this article is to familiarize the reader with fundamental concepts of dose metrics for assessing radiation exposure and weighting radiation-associated risks. The article also discusses general approaches for reducing radiation dose while preserving diagnostic quality. The authors provide additional insight for undertaking protocol optimization, customizing scanning techniques based on the patients' clinical scenario and demographics. Supplemental strategies are postulated using more advanced post-processing techniques for achieving further dose improvements. The technologic offerings of CT are integral to modern medicine and its role will continue to evolve. Although, the estimated risks from low levels of radiation of a single CT exam are uncertain, it is prudent to minimize the dose from CT by applying common sense solutions and using other simple strategies as well as exploiting technologic innovations. These efforts will enable us to take advantage of all the clinical benefits of CT while minimizing the likelihood of harm to patients.
High Resolution X-Ray Micro-CT of Ultra-Thin Wall Space Components
NASA Technical Reports Server (NTRS)
Roth, Don J.; Rauser, R. W.; Bowman, Randy R.; Bonacuse, Peter; Martin, Richard E.; Locci, I. E.; Kelley, M.
2012-01-01
A high resolution micro-CT system has been assembled and is being used to provide optimal characterization for ultra-thin wall space components. The Glenn Research Center NDE Sciences Team, using this CT system, has assumed the role of inspection vendor for the Advanced Stirling Convertor (ASC) project at NASA. This article will discuss many aspects of the development of the CT scanning for this type of component, including CT system overview; inspection requirements; process development, software utilized and developed to visualize, process, and analyze results; calibration sample development; results on actual samples; correlation with optical/SEM characterization; CT modeling; and development of automatic flaw recognition software. Keywords: Nondestructive Evaluation, NDE, Computed Tomography, Imaging, X-ray, Metallic Components, Thin Wall Inspection
Diagnosis of non-osseous spinal metastatic disease: the role of PET/CT and PET/MRI.
Batouli, Ali; Braun, John; Singh, Kamal; Gholamrezanezhad, Ali; Casagranda, Bethany U; Alavi, Abass
2018-06-01
The spine is the third most common site for distant metastasis in cancer patients with approximately 70% of patients with metastatic cancer having spinal involvement. Positron emission tomography (PET), combined with computed tomography (CT) or magnetic resonance imaging (MRI), has been deeply integrated in modern clinical oncology as a pivotal component of the diagnostic work-up of patients with cancer. PET is able to diagnose several neoplastic processes before any detectable morphological changes can be identified by anatomic imaging modalities alone. In this review, we discuss the role of PET/CT and PET/MRI in the diagnostic management of non-osseous metastatic disease of the spinal canal. While sometimes subtle, recognizing such disease on FDG PET/CT and PET/MRI imaging done routinely in cancer patients can guide treatment strategies to potentially prevent irreversible neurological damage.
Information granules in image histogram analysis.
Wieclawek, Wojciech
2018-04-01
A concept of granular computing employed in intensity-based image enhancement is discussed. First, a weighted granular computing idea is introduced. Then, the implementation of this term in the image processing area is presented. Finally, multidimensional granular histogram analysis is introduced. The proposed approach is dedicated to digital images, especially to medical images acquired by Computed Tomography (CT). As the histogram equalization approach, this method is based on image histogram analysis. Yet, unlike the histogram equalization technique, it works on a selected range of the pixel intensity and is controlled by two parameters. Performance is tested on anonymous clinical CT series. Copyright © 2017 Elsevier Ltd. All rights reserved.
Computer Tomography Analysis of Fastrac Composite Thrust Chamber Assemblies
NASA Technical Reports Server (NTRS)
Beshears, Ronald D.
2000-01-01
Computed tomography (CT) inspection has been integrated into the production process for NASA's Fastrac composite thrust chamber assemblies (TCAs). CT has been proven to be uniquely qualified to detect the known critical flaw for these nozzles, liner cracks that are adjacent to debonds between the liner and overwrap. CT is also being used as a process monitoring tool through analysis of low density indications in the nozzle overwraps. 3d reconstruction of CT images to produce models of flawed areas is being used to give program engineers better insight into the location and nature of nozzle flaws.
Glemser, Philip A; Pfleiderer, Michael; Heger, Anna; Tremper, Jan; Krauskopf, Astrid; Schlemmer, Heinz-Peter; Yen, Kathrin; Simons, David
2017-03-01
The aim of this multi-reader feasibility study was to evaluate new post-processing CT imaging tools in rib fracture assessment of forensic cases by analyzing detection time and diagnostic accuracy. Thirty autopsy cases (20 with and 10 without rib fractures in autopsy) were randomly selected and included in this study. All cases received a native whole body CT scan prior to the autopsy procedure, which included dissection and careful evaluation of each rib. In addition to standard transverse sections (modality A), CT images were subjected to a reconstruction algorithm to compute axial labelling of the ribs (modality B) as well as "unfolding" visualizations of the rib cage (modality C, "eagle tool"). Three radiologists with different clinical and forensic experience who were blinded to autopsy results evaluated all cases in a random manner of modality and case. Rib fracture assessment of each reader was evaluated compared to autopsy and a CT consensus read as radiologic reference. A detailed evaluation of relevant test parameters revealed a better accordance to the CT consensus read as to the autopsy. Modality C was the significantly quickest rib fracture detection modality despite slightly reduced statistic test parameters compared to modalities A and B. Modern CT post-processing software is able to shorten reading time and to increase sensitivity and specificity compared to standard autopsy alone. The eagle tool as an easy to use tool is suited for an initial rib fracture screening prior to autopsy and can therefore be beneficial for forensic pathologists.
Hsu, Shu-Hui; Cao, Yue; Lawrence, Theodore S.; Tsien, Christina; Feng, Mary; Grodzki, David M.; Balter, James M.
2015-01-01
Accurate separation of air and bone is critical for creating synthetic CT from MRI to support Radiation Oncology workflow. This study compares two different ultrashort echo-time sequences in the separation of air from bone, and evaluates post-processing methods that correct intensity nonuniformity of images and account for intensity gradients at tissue boundaries to improve this discriminatory power. CT and MRI scans were acquired on 12 patients under an institution review board-approved prospective protocol. The two MRI sequences tested were ultra-short TE imaging using 3D radial acquisition (UTE), and using pointwise encoding time reduction with radial acquisition (PETRA). Gradient nonlinearity correction was applied to both MR image volumes after acquisition. MRI intensity nonuniformity was corrected by vendor-provided normalization methods, and then further corrected using the N4itk algorithm. To overcome the intensity-gradient at air-tissue boundaries, spatial dilations, from 0 to 4 mm, were applied to threshold-defined air regions from MR images. Receiver operating characteristic (ROC) analyses, by comparing predicted (defined by MR images) versus “true” regions of air and bone (defined by CT images), were performed with and without residual bias field correction and local spatial expansion. The post-processing corrections increased the areas under the ROC curves (AUC) from 0.944 ± 0.012 to 0.976 ± 0.003 for UTE images, and from 0.850 ± 0.022 to 0.887 ± 0.012 for PETRA images, compared to without corrections. When expanding the threshold-defined air volumes, as expected, sensitivity of air identification decreased with an increase in specificity of bone discrimination, but in a non-linear fashion. A 1-mm air mask expansion yielded AUC increases of 1% and 4% for UTE and PETRA images, respectively. UTE images had significantly greater discriminatory power in separating air from bone than PETRA images. Post-processing strategies improved the discriminatory power of air from bone for both UTE and PETRA images, and reduced the difference between the two imaging sequences. Both postprocessed UTE and PETRA images demonstrated sufficient power to discriminate air from bone to support synthetic CT generation from MRI data. PMID:25776205
Ahlman, Mark A; Nietert, Paul J; Wahlquist, Amy E; Serguson, Jill M; Berry, Max W; Suranyi, Pal; Liu, Songtao; Spicer, Kenneth M
2014-01-01
Purpose: In the effort to reduce radiation exposure to patients undergoing myocardial perfusion imaging (MPI) with SPECT/CT, we evaluate the feasibility of a single CT for attenuation correction (AC) of single-day rest (R)/stress (S) perfusion. Methods: Processing of 20 single isotope and 20 dual isotope MPI with perfusion defects were retrospectively repeated in three steps: (1) the standard method using a concurrent R-CT for AC of R-SPECT and S-CT for S-SPECT; (2) the standard method repeated; and (3) with the R-CT used for AC of S-SPECT, and the S-CT used for AC of R-SPECT. Intra-Class Correlation Coefficients (ICC) and Choen’s kappa were used to measure intra-operator variability in sum scoring. Results: The highest level of intra-operator reliability was seen with the reproduction of the sum rest score (SRS) and sum stress score (SSS) (ICC > 95%). ICCs were > 85% for SRS and SSS when alternate CTs were used for AC, but when sum difference scores were calculated, ICC values were much lower (~22% to 27%), which may imply that neither CT substitution resulted in a reproducible difference score. Similar results were seen when evaluating dichotomous outcomes (sum scores difference of ≥ 4) when comparing different processing techniques (kappas ~0.32 to 0.43). Conclusions: When a single CT is used for AC of both rest and stress SPECT, there is disproportionately high variability in sum scoring that is independent of user error. This information can be used to direct further investigation in radiation reduction for common imaging exams in nuclear medicine. PMID:24482701
DOE Office of Scientific and Technical Information (OSTI.GOV)
Maspero, M.; Meijer, G.J.; Lagendijk, J.J.W.
2015-06-15
Purpose: To develop an image processing method for MRI-based generation of electron density maps, known as pseudo-CT (pCT), without usage of model- or atlas-based segmentation, and to evaluate the method in the pelvic and head-neck region against CT. Methods: CT and MRI scans were obtained from the pelvic region of four patients in supine position using a flat table top only for CT. Stratified CT maps were generated by classifying each voxel based on HU ranges into one of four classes: air, adipose tissue, soft tissue or bone.A hierarchical region-selective algorithm, based on automatic thresholding and clustering, was used tomore » classify tissues from MR Dixon reconstructed fat, In-Phase (IP) and Opposed-Phase (OP) images. First, a body mask was obtained by thresholding the IP image. Subsequently, an automatic threshold on the Dixon fat image differentiated soft and adipose tissue. K-means clustering on IP and OP images resulted in a mask that, via a connected neighborhood analysis, allowing the user to select the components corresponding to bone structures.The pCT was estimated through assignment of bulk HU to the tissue classes. Bone-only Digital Reconstructed Radiographs (DRR) were generated as well. The pCT images were rigidly registered to the stratified CT to allow a volumetric and voxelwise comparison. Moreover, pCTs were also calculated within the head-neck region in two volunteers using the same pipeline. Results: The volumetric comparison resulted in differences <1% for each tissue class. A voxelwise comparison showed a good classification, ranging from 64% to 98%. The primary misclassified classes were adipose/soft tissue and bone/soft tissue. As the patients have been imaged on different table tops, part of the misclassification error can be explained by misregistration. Conclusion: The proposed approach does not rely on an anatomy model providing the flexibility to successfully generate the pCT in two different body sites. This research is founded by ZonMw IMDI Programme, project name: “RASOR sharp: MRI based radiotherapy planning using a single MRI sequence”, project number: 10-104003010.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hua, C.
This session will update therapeutic physicists on technological advancements and radiation oncology features of commercial CT, MRI, and PET/CT imaging systems. Also described are physicists’ roles in every stage of equipment selection, purchasing, and operation, including defining specifications, evaluating vendors, making recommendations, and optimal and safe use of imaging equipment in radiation oncology environment. The first presentation defines important terminology of CT and PET/CT followed by a review of latest innovations, such as metal artifact reduction, statistical iterative reconstruction, radiation dose management, tissue classification by dual energy CT and spectral CT, improvement in spatial resolution and sensitivity in PET, andmore » potentials of PET/MR. We will also discuss important technical specifications and items in CT and PET/CT purchasing quotes and their impacts. The second presentation will focus on key components in the request for proposal for a MRI simulator and how to evaluate vendor proposals. MRI safety issues in radiation Oncology, including MRI scanner Zones (4-zone design), will be discussed. Basic MR terminologies, important functionalities, and advanced features, which are relevant to radiation therapy, will be discussed. In the third presentation, justification of imaging systems for radiation oncology, considerations in room design and construction in a RO department, shared use with diagnostic radiology, staffing needs and training, clinical/research use cases and implementation, will be discussed. The emphasis will be on understanding and bridging the differences between diagnostic and radiation oncology installations, building consensus amongst stakeholders for purchase and use, and integrating imaging technologies into the radiation oncology environment. Learning Objectives: Learn the latest innovations of major imaging systems relevant to radiation therapy Be able to describe important technical specifications of CT, MRI, and PET/CT Understand the process of budget request, equipment justification, comparisons of technical specifications, site visits, vendor selection, and contract development.« less
Outside CT imaging among emergency department transfer patients.
Sung, Jeffrey C; Sodickson, Aaron; Ledbetter, Stephen
2009-09-01
The aim of this study was to characterize the quantity and types of outside computed tomographic (CT) examinations submitted for reinterpretation among emergency department (ED) transfers to a tertiary care, level I trauma, academic medical center and the frequency of and reasons for repeat imaging. Reinterpretation requests for outside CT studies accompanying ED transfer patients over a 4-month period were prospectively audited. Clinicians completed forms specifying type of CT study, outside report availability, interpretational discrepancies, repeat imaging requests, and reasons for repeat imaging. A total of 425 CT studies were reviewed among 255 transfer patients, with a mean of 2.8 examinations (range, 0-16) on 1.7 patients (range, 0-8) per day. The patients' mean age was 59 years, and 57% were male. The clinicians reported no outside verbal or written reports for 16% of patients. Interpretational discrepancies were noted in 12% of those with outside reports. Repeat scans might have been avoided in as many as 25% of rescanned patients (35% of repeat examinations) because they were performed solely for imaging or information technology reasons (inadequate imaging, compact disc inoperability, or unavailable images within the hospital's picture archiving and communication system). Rescanned trauma patients in particular had a high per patient rate (32%) of potentially avoidable reasons, with a lower rate (11%) in nontrauma patients. Outside CT imaging in ED transfers adds workload and resource requirements for receiving institutions. A communication gap exists between transferring and receiving institutions, and interpretational discrepancies are common. Process improvement measures are suggested that might reduce the substantial rates of potentially avoidable reimaging.
The cheating liver: imaging of focal steatosis and fatty sparing.
Dioguardi Burgio, Marco; Bruno, Onorina; Agnello, Francesco; Torrisi, Chiara; Vernuccio, Federica; Cabibbo, Giuseppe; Soresi, Maurizio; Petta, Salvatore; Calamia, Mauro; Papia, Giovanni; Gambino, Angelo; Ricceri, Viola; Midiri, Massimo; Lagalla, Roberto; Brancatelli, Giuseppe
2016-06-01
Focal steatosis and fatty sparing are a frequent finding in liver imaging, and can mimic solid lesions. Liver regional variations in the degree of fat accumulation can be related to vascular anomalies, metabolic disorders, use of certain drugs or coexistence of hepatic masses. CT and MRI are the modalities of choice for the noninvasive diagnosis of hepatic steatosis. Knowledge of CT and MRI appearance of focal steatosis and fatty sparing is crucial for an accurate diagnosis, and to rule-out other pathologic processes. This paper will review the CT and MRI techniques for the diagnosis of hepatic steatosis and the CT and MRI features of common and uncommon causes of focal steatosis and fatty sparing.
TU-G-201-00: Imaging Equipment Specification and Selection in Radiation Oncology Departments
DOE Office of Scientific and Technical Information (OSTI.GOV)
NONE
This session will update therapeutic physicists on technological advancements and radiation oncology features of commercial CT, MRI, and PET/CT imaging systems. Also described are physicists’ roles in every stage of equipment selection, purchasing, and operation, including defining specifications, evaluating vendors, making recommendations, and optimal and safe use of imaging equipment in radiation oncology environment. The first presentation defines important terminology of CT and PET/CT followed by a review of latest innovations, such as metal artifact reduction, statistical iterative reconstruction, radiation dose management, tissue classification by dual energy CT and spectral CT, improvement in spatial resolution and sensitivity in PET, andmore » potentials of PET/MR. We will also discuss important technical specifications and items in CT and PET/CT purchasing quotes and their impacts. The second presentation will focus on key components in the request for proposal for a MRI simulator and how to evaluate vendor proposals. MRI safety issues in radiation Oncology, including MRI scanner Zones (4-zone design), will be discussed. Basic MR terminologies, important functionalities, and advanced features, which are relevant to radiation therapy, will be discussed. In the third presentation, justification of imaging systems for radiation oncology, considerations in room design and construction in a RO department, shared use with diagnostic radiology, staffing needs and training, clinical/research use cases and implementation, will be discussed. The emphasis will be on understanding and bridging the differences between diagnostic and radiation oncology installations, building consensus amongst stakeholders for purchase and use, and integrating imaging technologies into the radiation oncology environment. Learning Objectives: Learn the latest innovations of major imaging systems relevant to radiation therapy Be able to describe important technical specifications of CT, MRI, and PET/CT Understand the process of budget request, equipment justification, comparisons of technical specifications, site visits, vendor selection, and contract development.« less
Mansoor, Awais; Foster, Brent; Xu, Ziyue; Papadakis, Georgios Z.; Folio, Les R.; Udupa, Jayaram K.; Mollura, Daniel J.
2015-01-01
The computer-based process of identifying the boundaries of lung from surrounding thoracic tissue on computed tomographic (CT) images, which is called segmentation, is a vital first step in radiologic pulmonary image analysis. Many algorithms and software platforms provide image segmentation routines for quantification of lung abnormalities; however, nearly all of the current image segmentation approaches apply well only if the lungs exhibit minimal or no pathologic conditions. When moderate to high amounts of disease or abnormalities with a challenging shape or appearance exist in the lungs, computer-aided detection systems may be highly likely to fail to depict those abnormal regions because of inaccurate segmentation methods. In particular, abnormalities such as pleural effusions, consolidations, and masses often cause inaccurate lung segmentation, which greatly limits the use of image processing methods in clinical and research contexts. In this review, a critical summary of the current methods for lung segmentation on CT images is provided, with special emphasis on the accuracy and performance of the methods in cases with abnormalities and cases with exemplary pathologic findings. The currently available segmentation methods can be divided into five major classes: (a) thresholding-based, (b) region-based, (c) shape-based, (d) neighboring anatomy–guided, and (e) machine learning–based methods. The feasibility of each class and its shortcomings are explained and illustrated with the most common lung abnormalities observed on CT images. In an overview, practical applications and evolving technologies combining the presented approaches for the practicing radiologist are detailed. ©RSNA, 2015 PMID:26172351
NASA Astrophysics Data System (ADS)
Eck, Brendan L.; Fahmi, Rachid; Levi, Jacob; Fares, Anas; Wu, Hao; Li, Yuemeng; Vembar, Mani; Dhanantwari, Amar; Bezerra, Hiram G.; Wilson, David L.
2016-03-01
Myocardial perfusion imaging using CT (MPI-CT) has the potential to provide quantitative measures of myocardial blood flow (MBF) which can aid the diagnosis of coronary artery disease. We evaluated the quantitative accuracy of MPI-CT in a porcine model of balloon-induced LAD coronary artery ischemia guided by fractional flow reserve (FFR). We quantified MBF at baseline (FFR=1.0) and under moderate ischemia (FFR=0.7) using MPI-CT and compared to fluorescent microsphere-based MBF from high-resolution cryo-images. Dynamic, contrast-enhanced CT images were obtained using a spectral detector CT (Philips Healthcare). Projection-based mono-energetic images were reconstructed and processed to obtain MBF. Three MBF quantification approaches were evaluated: singular value decomposition (SVD) with fixed Tikhonov regularization (ThSVD), SVD with regularization determined by the L-Curve criterion (LSVD), and Johnson-Wilson parameter estimation (JW). The three approaches over-estimated MBF compared to cryo-images. JW produced the most accurate MBF, with average error 33.3+/-19.2mL/min/100g, whereas LSVD and ThSVD had greater over-estimation, 59.5+/-28.3mL/min/100g and 78.3+/-25.6 mL/min/100g, respectively. Relative blood flow as assessed by a flow ratio of LAD-to-remote myocardium was strongly correlated between JW and cryo-imaging, with R2=0.97, compared to R2=0.88 and 0.78 for LSVD and ThSVD, respectively. We assessed tissue impulse response functions (IRFs) from each approach for sources of error. While JW was constrained to physiologic solutions, both LSVD and ThSVD produced IRFs with non-physiologic properties due to noise. The L-curve provided noise-adaptive regularization but did not eliminate non-physiologic IRF properties or optimize for MBF accuracy. These findings suggest that model-based MPI-CT approaches may be more appropriate for quantitative MBF estimation and that cryo-imaging can support the development of MPI-CT by providing spatial distributions of MBF.
A new methodological approach for PET implementation in radiotherapy treatment planning.
Bellan, Elena; Ferretti, Alice; Capirci, Carlo; Grassetto, Gaia; Gava, Marcello; Chondrogiannis, Sotirios; Virdis, Graziella; Marzola, Maria Cristina; Massaro, Arianna; Rubello, Domenico; Nibale, Otello
2012-05-01
In this paper, a new methodological approach to using PET information in radiotherapy treatment planning has been discussed. Computed tomography (CT) represents the primary modality to plan personalized radiation treatment, because it provides the basic electron density map for correct dose calculation. If PET scanning is also performed it is typically coregistered with the CT study. This operation can be executed automatically by a hybrid PET/CT scanner or, if the PET and CT imaging sets have been acquired through different equipment, by a dedicated module of the radiotherapy treatment planning system. Both approaches have some disadvantages: in the first case, the bore of a PET/CT system generally used in clinical practice often does not allow the use of certain bulky devices for patient immobilization in radiotherapy, whereas in the second case the result could be affected by limitations in window/level visualization of two different image modalities, and the displayed PET volumes can appear not to be related to the actual uptake into the patient. To overcome these problems, at our centre a specific procedure has been studied and tested in 30 patients, allowing good results of precision in the target contouring to be obtained. The process consists of segmentation of the biological target volume by a dedicated PET/CT console and its export to a dedicated radiotherapy system, where an image registration between the CT images acquired by the PET/CT scanner and a large-bore CT is performed. The planning target volume is contoured only on the large-bore CT and is used for virtual simulation, to individuate permanent skin markers on the patient.
Improved proton CT imaging using a bismuth germanium oxide scintillator.
Tanaka, Sodai; Nishio, Teiji; Tsuneda, Masato; Matsushita, Keiichiro; Kabuki, Shigeto; Uesaka, Mitsuru
2018-02-02
Range uncertainty is among the most formidable challenges associated with the treatment planning of proton therapy. Proton imaging, which includes proton radiography and proton computed tomography (pCT), is a useful verification tool. We have developed a pCT detection system that uses a thick bismuth germanium oxide (BGO) scintillator and a CCD camera. The current method is based on a previous detection system that used a plastic scintillator, and implements improved image processing techniques. In the new system, the scintillation light intensity is integrated along the proton beam path by the BGO scintillator, and acquired as a two-dimensional distribution with the CCD camera. The range of a penetrating proton is derived from the integrated light intensity using a light-to-range conversion table, and a pCT image can be reconstructed. The proton range in the BGO scintillator is shorter than in the plastic scintillator, so errors due to extended proton ranges can be reduced. To demonstrate the feasibility of the pCT system, an experiment was performed using a 70 MeV proton beam created by the AVF930 cyclotron at the National Institute of Radiological Sciences. The accuracy of the light-to-range conversion table, which is susceptible to errors due to its spatial dependence, was investigated, and the errors in the acquired pixel values were less than 0.5 mm. Images of various materials were acquired, and the pixel-value errors were within 3.1%, which represents an improvement over previous results. We also obtained a pCT image of an edible chicken piece, the first of its kind for a biological material, and internal structures approximately one millimeter in size were clearly observed. This pCT imaging system is fast and simple, and based on these findings, we anticipate that we can acquire 200 MeV pCT images using the BGO scintillator system.
King, Kathryn S; Chen, Clara C; Alexopoulos, Dimitrios K; Whatley, Millie A; Reynolds, James C; Patronas, Nicholas; Ling, Alexander; Adams, Karen T; Xekouki, Paraskevi; Lando, Howard; Stratakis, Constantine A; Pacak, Karel
2011-09-01
Accurate diagnosis of head and neck paragangliomas is often complicated by biochemical silence and lack of catecholamine-associated symptoms, making accurate anatomical and functional imaging techniques essential to the diagnostic process. Ten patients (seven SDHD, three SDHB), with a total of 26 head and neck paragangliomas, were evaluated with anatomical and functional imaging. This study compares five different functional imaging techniques [(18)F-fluorodihydroxyphenylalanine ((18)F-FDOPA) positron emission tomography (PET), (18)F-fluorodopamine ((18)F-FDA) PET/computed tomography (CT), (18)F-fluoro-2-deoxy-D-glucose ((18)F-FDG) PET/CT, (123)I-metaiodobenzylguanidine ((123)I-MIBG) scintigraphy, and (111)In-pentetreotide scintigraphy] in the localization of head and neck paragangliomas. Prospectively (18)F-FDOPA PET localized 26 of 26 lesions in the 10 patients, CT/magnetic resonance imaging localized 21 of 26 lesions, (18)F-FDG PET/CT localized 20 of 26 lesions, (111)In-pentetreotide scintigraphy localized 16 of 25 lesions, (18)F-FDA PET/CT localized 12 of 26 lesions, and (123)I-MIBG scintigraphy localized eight of 26 lesions. Differences in imaging efficacy related to genetic phenotype, even in the present small sample size, included the negativity of (18)F-FDA PET/CT and (123)I-MIBG scintigraphy in patients with SDHB mutations and the accuracy of (18)F-FDG PET/CT in all patients with SDHD mutations, as compared with the accuracy of (18)F-FDG PET/CT in only one patient with an SDHB mutation. Overall, (18)F-FDOPA PET proved to be the most efficacious functional imaging modality in the localization of SDHx-related head and neck paragangliomas and may be a potential first-line functional imaging agent for the localization of these tumors.
Improved proton CT imaging using a bismuth germanium oxide scintillator
NASA Astrophysics Data System (ADS)
Tanaka, Sodai; Nishio, Teiji; Tsuneda, Masato; Matsushita, Keiichiro; Kabuki, Shigeto; Uesaka, Mitsuru
2018-02-01
Range uncertainty is among the most formidable challenges associated with the treatment planning of proton therapy. Proton imaging, which includes proton radiography and proton computed tomography (pCT), is a useful verification tool. We have developed a pCT detection system that uses a thick bismuth germanium oxide (BGO) scintillator and a CCD camera. The current method is based on a previous detection system that used a plastic scintillator, and implements improved image processing techniques. In the new system, the scintillation light intensity is integrated along the proton beam path by the BGO scintillator, and acquired as a two-dimensional distribution with the CCD camera. The range of a penetrating proton is derived from the integrated light intensity using a light-to-range conversion table, and a pCT image can be reconstructed. The proton range in the BGO scintillator is shorter than in the plastic scintillator, so errors due to extended proton ranges can be reduced. To demonstrate the feasibility of the pCT system, an experiment was performed using a 70 MeV proton beam created by the AVF930 cyclotron at the National Institute of Radiological Sciences. The accuracy of the light-to-range conversion table, which is susceptible to errors due to its spatial dependence, was investigated, and the errors in the acquired pixel values were less than 0.5 mm. Images of various materials were acquired, and the pixel-value errors were within 3.1%, which represents an improvement over previous results. We also obtained a pCT image of an edible chicken piece, the first of its kind for a biological material, and internal structures approximately one millimeter in size were clearly observed. This pCT imaging system is fast and simple, and based on these findings, we anticipate that we can acquire 200 MeV pCT images using the BGO scintillator system.
Combined X-ray CT and mass spectrometry for biomedical imaging applications
NASA Astrophysics Data System (ADS)
Schioppa, E., Jr.; Ellis, S.; Bruinen, A. L.; Visser, J.; Heeren, R. M. A.; Uher, J.; Koffeman, E.
2014-04-01
Imaging technologies play a key role in many branches of science, especially in biology and medicine. They provide an invaluable insight into both internal structure and processes within a broad range of samples. There are many techniques that allow one to obtain images of an object. Different techniques are based on the analysis of a particular sample property by means of a dedicated imaging system, and as such, each imaging modality provides the researcher with different information. The use of multimodal imaging (imaging with several different techniques) can provide additional and complementary information that is not possible when employing a single imaging technique alone. In this study, we present for the first time a multi-modal imaging technique where X-ray computerized tomography (CT) is combined with mass spectrometry imaging (MSI). While X-ray CT provides 3-dimensional information regarding the internal structure of the sample based on X-ray absorption coefficients, MSI of thin sections acquired from the same sample allows the spatial distribution of many elements/molecules, each distinguished by its unique mass-to-charge ratio (m/z), to be determined within a single measurement and with a spatial resolution as low as 1 μm or even less. The aim of the work is to demonstrate how molecular information from MSI can be spatially correlated with 3D structural information acquired from X-ray CT. In these experiments, frozen samples are imaged in an X-ray CT setup using Medipix based detectors equipped with a CO2 cooled sample holder. Single projections are pre-processed before tomographic reconstruction using a signal-to-thickness calibration. In the second step, the object is sliced into thin sections (circa 20 μm) that are then imaged using both matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and secondary ion (SIMS) mass spectrometry, where the spatial distribution of specific molecules within the sample is determined. The combination of two vastly different imaging approaches provides complementary information (i.e., anatomical and molecular distributions) that allows the correlation of distinct structural features with specific molecules distributions leading to unique insights in disease development.
Computer-aided diagnosis of splenic enlargement using wave pattern of spleen in abdominal CT images
NASA Astrophysics Data System (ADS)
Seong, Won; Cho, June-Sik; Noh, Seung-Moo; Park, Jong Won
2006-03-01
It is known that the spleen accompanied by liver cirrhosis is hypertrophied or enlarged. We have examined a wave pattern at the left boundary of spleen on the abdominal CT images having liver cirrhosis, and found that they are different from those on the images having a normal liver. It is noticed that the abdominal CT images of patient with liver cirrhosis shows strong bending in the wave pattern. In the case of normal liver, the images may also have a wave pattern, but its bends are not strong. Therefore, the total waving area of the spleen with liver cirrhosis is found to be greater than that of the spleen with a normal liver. Moreover, we found that the waves of the spleen from the image with liver cirrhosis have the higher degree of circularity compared to the normal liver case. Based on the two observations above, we propose an automatic method to diagnose splenic enlargement by using the wave pattern of the spleen in abdominal CT images. The proposed automatic method improves the diagnostic performance compared with the conventional process based on the size of spleen.
SU-D-206-03: Segmentation Assisted Fast Iterative Reconstruction Method for Cone-Beam CT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wu, P; Mao, T; Gong, S
2016-06-15
Purpose: Total Variation (TV) based iterative reconstruction (IR) methods enable accurate CT image reconstruction from low-dose measurements with sparse projection acquisition, due to the sparsifiable feature of most CT images using gradient operator. However, conventional solutions require large amount of iterations to generate a decent reconstructed image. One major reason is that the expected piecewise constant property is not taken into consideration at the optimization starting point. In this work, we propose an iterative reconstruction method for cone-beam CT (CBCT) using image segmentation to guide the optimization path more efficiently on the regularization term at the beginning of the optimizationmore » trajectory. Methods: Our method applies general knowledge that one tissue component in the CT image contains relatively uniform distribution of CT number. This general knowledge is incorporated into the proposed reconstruction using image segmentation technique to generate the piecewise constant template on the first-pass low-quality CT image reconstructed using analytical algorithm. The template image is applied as an initial value into the optimization process. Results: The proposed method is evaluated on the Shepp-Logan phantom of low and high noise levels, and a head patient. The number of iterations is reduced by overall 40%. Moreover, our proposed method tends to generate a smoother reconstructed image with the same TV value. Conclusion: We propose a computationally efficient iterative reconstruction method for CBCT imaging. Our method achieves a better optimization trajectory and a faster convergence behavior. It does not rely on prior information and can be readily incorporated into existing iterative reconstruction framework. Our method is thus practical and attractive as a general solution to CBCT iterative reconstruction. This work is supported by the Zhejiang Provincial Natural Science Foundation of China (Grant No. LR16F010001), National High-tech R&D Program for Young Scientists by the Ministry of Science and Technology of China (Grant No. 2015AA020917).« less
Yuki, I; Kambayashi, Y; Ikemura, A; Abe, Y; Kan, I; Mohamed, A; Dahmani, C; Suzuki, T; Ishibashi, T; Takao, H; Urashima, M; Murayama, Y
2016-02-01
Combination of high-resolution C-arm CT and novel metal artifact reduction software may contribute to the assessment of aneurysms treated with stent-assisted coil embolization. This study aimed to evaluate the efficacy of a novel Metal Artifact Reduction prototype software combined with the currently available high spatial-resolution C-arm CT prototype implementation by using an experimental aneurysm model treated with stent-assisted coil embolization. Eight experimental aneurysms were created in 6 swine. Coil embolization of each aneurysm was performed by using a stent-assisted technique. High-resolution C-arm CT with intra-arterial contrast injection was performed immediately after the treatment. The obtained images were processed with Metal Artifact Reduction. Five neurointerventional specialists reviewed the image quality before and after Metal Artifact Reduction. Observational and quantitative analyses (via image analysis software) were performed. Every aneurysm was successfully created and treated with stent-assisted coil embolization. Before Metal Artifact Reduction, coil loops protruding through the stent lumen were not visualized due to the prominent metal artifacts produced by the coils. These became visible after Metal Artifact Reduction processing. Contrast filling in the residual aneurysm was also visualized after Metal Artifact Reduction in every aneurysm. Both the observational (P < .0001) and quantitative (P < .001) analyses showed significant reduction of the metal artifacts after application of the Metal Artifact Reduction prototype software. The combination of high-resolution C-arm CT and Metal Artifact Reduction enables differentiation of the coil mass, stent, and contrast material on the same image by significantly reducing the metal artifacts produced by the platinum coils. This novel image technique may improve the assessment of aneurysms treated with stent-assisted coil embolization. © 2016 by American Journal of Neuroradiology.
Teoh, Raymond; Johnson, Raleigh F; Nishino, Thomas K; Ethridge, Richard T
2007-01-01
The deep inferior epigastric perforator flap procedure has become a popular alternative for women who require breast reconstruction. One of the difficulties with this procedure is identifying perforator arteries large enough to ensure that the harvested tissue is well vascularized. Current techniques involve imaging the perforator arteries with computed tomography (CT) to produce a grid mapping the locations of the perforator arteries relative to the umbilicus. To compare the time it takes to produce a map of the perforators using either two-dimensional (2D) or three-dimensional (3D) CT, and to see whether there is a benefit in using a 3D model. Patient CT abdomen and pelvis scans were acquired from a GE 64-slice scanner. CT image processing was performed with the GE 3D Advantage Workstation v4.2 software. Maps of the perforators were generated both as 2D and 3D representations. Perforators within a region 5 cm rostral and 7 cm caudal to the umbilicus were measured and the times to perform these measurements using both 2D and 3D images were recorded by a stopwatch. Although the 3D method took longer than the 2D method (mean [+/- SD] time 1:51+/-0:35 min versus 1:08+/-0:16 min per perforator artery, respectively), producing a 3D image provides much more information than the 2D images alone. Additionally, an actual-sized 3D image can be printed out, removing the need to make measurements and producing a grid. Although it took less time to create a grid of the perforators using 2D axial CT scans, the 3D reconstruction of the abdomen allows the plastic surgeons to better visualize the patient's anatomy and has definite clinical utility.
Myoanatomy of the velvet worm leg revealed by laboratory-based nanofocus X-ray source tomography.
Müller, Mark; de Sena Oliveira, Ivo; Allner, Sebastian; Ferstl, Simone; Bidola, Pidassa; Mechlem, Korbinian; Fehringer, Andreas; Hehn, Lorenz; Dierolf, Martin; Achterhold, Klaus; Gleich, Bernhard; Hammel, Jörg U; Jahn, Henry; Mayer, Georg; Pfeiffer, Franz
2017-11-21
X-ray computed tomography (CT) is a powerful noninvasive technique for investigating the inner structure of objects and organisms. However, the resolution of laboratory CT systems is typically limited to the micrometer range. In this paper, we present a table-top nanoCT system in conjunction with standard processing tools that is able to routinely reach resolutions down to 100 nm without using X-ray optics. We demonstrate its potential for biological investigations by imaging a walking appendage of Euperipatoides rowelli , a representative of Onychophora-an invertebrate group pivotal for understanding animal evolution. Comparative analyses proved that the nanoCT can depict the external morphology of the limb with an image quality similar to scanning electron microscopy, while simultaneously visualizing internal muscular structures at higher resolutions than confocal laser scanning microscopy. The obtained nanoCT data revealed hitherto unknown aspects of the onychophoran limb musculature, enabling the 3D reconstruction of individual muscle fibers, which was previously impossible using any laboratory-based imaging technique.
NASA Astrophysics Data System (ADS)
Zhou, Xiangrong; Kano, Takuya; Koyasu, Hiromi; Li, Shuo; Zhou, Xinxin; Hara, Takeshi; Matsuo, Masayuki; Fujita, Hiroshi
2017-03-01
This paper describes a novel approach for the automatic assessment of breast density in non-contrast three-dimensional computed tomography (3D CT) images. The proposed approach trains and uses a deep convolutional neural network (CNN) from scratch to classify breast tissue density directly from CT images without segmenting the anatomical structures, which creates a bottleneck in conventional approaches. Our scheme determines breast density in a 3D breast region by decomposing the 3D region into several radial 2D-sections from the nipple, and measuring the distribution of breast tissue densities on each 2D section from different orientations. The whole scheme is designed as a compact network without the need for post-processing and provides high robustness and computational efficiency in clinical settings. We applied this scheme to a dataset of 463 non-contrast CT scans obtained from 30- to 45-year-old-women in Japan. The density of breast tissue in each CT scan was assigned to one of four categories (glandular tissue within the breast <25%, 25%-50%, 50%-75%, and >75%) by a radiologist as ground truth. We used 405 CT scans for training a deep CNN and the remaining 58 CT scans for testing the performance. The experimental results demonstrated that the findings of the proposed approach and those of the radiologist were the same in 72% of the CT scans among the training samples and 76% among the testing samples. These results demonstrate the potential use of deep CNN for assessing breast tissue density in non-contrast 3D CT images.
Pai, Vinay M; Kozlowski, Megan; Donahue, Danielle; Miller, Elishiah; Xiao, Xianghui; Chen, Marcus Y; Yu, Zu-Xi; Connelly, Patricia; Jeffries, Kenneth; Wen, Han
2012-05-01
The high spatial resolution of micro-computed tomography (micro-CT) is ideal for 3D imaging of coronary arteries in intact mouse heart specimens. Previously, micro-CT of mouse heart specimens utilized intravascular contrast agents that hardened within the vessel lumen and allowed a vascular cast to be made. However, for mouse coronary artery disease models, it is highly desirable to image coronary artery walls and highlight plaques. For this purpose, we describe an ex vivo contrast-enhanced micro-CT imaging technique based on tissue staining with osmium tetroxide (OsO(4) ) solution. As a tissue-staining contrast agent, OsO(4) is retained in the vessel wall and surrounding tissue during the fixation process and cleared from the vessel lumens. Its high X-ray attenuation makes the artery wall visible in CT. Additionally, since OsO(4) preferentially binds to lipids, it highlights lipid deposition in the artery wall. We performed micro-CT of heart specimens of 5- to 25-week-old C57BL/6 wild-type mice and 5- to 13-week-old apolipoprotein E knockout (apoE(-/-) ) mice at 10 μm resolution. The results show that walls of coronary arteries as small as 45 μm in diameter are visible using a table-top micro-CT scanner. Similar image clarity was achieved with 1/2000th the scan time using a synchrotron CT scanner. In 13-week-old apoE mice, lipid-rich plaques are visible in the aorta. Our study shows that the combination of OsO(4) and micro-CT permits the visualization of the coronary artery wall in intact mouse hearts. Published 2012. This article is a US Government work and is in the public domain in the USA. Journal of Anatomy © 2012 Anatomical Society.
Coronary artery wall imaging in mice using osmium tetroxide and micro-computed tomography (micro-CT)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pai, Vinay M.; Kozlowski, Megan; Donahue, Danielle
2012-05-10
The high spatial resolution of micro-computed tomography (micro-CT) is ideal for 3D imaging of coronary arteries in intact mouse heart specimens. Previously, micro-CT of mouse heart specimens utilized intravascular contrast agents that hardened within the vessel lumen and allowed a vascular cast to be made. However, for mouse coronary artery disease models, it is highly desirable to image coronary artery walls and highlight plaques. For this purpose, we describe an ex vivo contrast-enhanced micro-CT imaging technique based on tissue staining with osmium tetroxide (OsO{sub 4}) solution. As a tissue-staining contrast agent, OsO{sub 4} is retained in the vessel wall andmore » surrounding tissue during the fixation process and cleared from the vessel lumens. Its high X-ray attenuation makes the artery wall visible in CT. Additionally, since OsO{sub 4} preferentially binds to lipids, it highlights lipid deposition in the artery wall. We performed micro-CT of heart specimens of 5- to 25-week-old C57BL/6 wild-type mice and 5- to 13-week-old apolipoprotein E knockout (apoE{sup -/-}) mice at 10 {mu}m resolution. The results show that walls of coronary arteries as small as 45 {mu}m in diameter are visible using a table-top micro-CT scanner. Similar image clarity was achieved with 1/2000th the scan time using a synchrotron CT scanner. In 13-week-old apoE mice, lipid-rich plaques are visible in the aorta. Our study shows that the combination of OsO{sub 4} and micro-CT permits the visualization of the coronary artery wall in intact mouse hearts.« less
Image fusion pitfalls for cranial radiosurgery.
Jonker, Benjamin P
2013-01-01
Stereotactic radiosurgery requires imaging to define both the stereotactic space in which the treatment is delivered and the target itself. Image fusion is the process of using rotation and translation to bring a second image set into alignment with the first image set. This allows the potential concurrent use of multiple image sets to define the target and stereotactic space. While a single magnetic resonance imaging (MRI) sequence alone can be used for delineation of the target and fiducials, there may be significant advantages to using additional imaging sets including other MRI sequences, computed tomography (CT) scans, and advanced imaging sets such as catheter-based angiography, diffusor tension imaging-based fiber tracking and positon emission tomography in order to more accurately define the target and surrounding critical structures. Stereotactic space is usually defined by detection of fiducials on the stereotactic head frame or mask system. Unfortunately MRI sequences are susceptible to geometric distortion, whereas CT scans do not face this problem (although they have poorer resolution of the target in most cases). Thus image fusion can allow the definition of stereotactic space to proceed from the geometrically accurate CT images at the same time as using MRI to define the target. The use of image fusion is associated with risk of error introduced by inaccuracies of the fusion process, as well as workflow changes that if not properly accounted for can mislead the treating clinician. The purpose of this review is to describe the uses of image fusion in stereotactic radiosurgery as well as its potential pitfalls.
Radiological Findings in a case of Advance staged Mesothelioma
Aziz, Fahad
2009-01-01
Chest X Ray is the initial screening test for the mesothelioma like all other the chest diseases. But computed tomography (CT) is the imaging technique of choice for charactering pleural masses. CT also gives important information regarding invasion of the chest wall and surrounding structures. Certain CT features help differentiate benign from malignant processes. This short article highlights the salient CT appearance of mesothelioma; the most common pleural tumor. PMID:22263002
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kim, H; Chen, J; Pouliot, J
2015-06-15
Purpose: Compressed sensing (CS) has been used for CT (4DCT/CBCT) reconstruction with few projections to reduce dose of radiation. Total-variation (TV) in L1-minimization (min.) with local information is the prevalent technique in CS, while it can be prone to noise. To address the problem, this work proposes to apply a new image processing technique, called non-local TV (NLTV), to CS based CT reconstruction, and incorporate reweighted L1-norm into it for more precise reconstruction. Methods: TV minimizes intensity variations by considering two local neighboring voxels, which can be prone to noise, possibly damaging the reconstructed CT image. NLTV, contrarily, utilizes moremore » global information by computing a weight function of current voxel relative to surrounding search area. In fact, it might be challenging to obtain an optimal solution due to difficulty in defining the weight function with appropriate parameters. Introducing reweighted L1-min., designed for approximation to ideal L0-min., can reduce the dependence on defining the weight function, therefore improving accuracy of the solution. This work implemented the NLTV combined with reweighted L1-min. by Split Bregman Iterative method. For evaluation, a noisy digital phantom and a pelvic CT images are employed to compare the quality of images reconstructed by TV, NLTV and reweighted NLTV. Results: In both cases, conventional and reweighted NLTV outperform TV min. in signal-to-noise ratio (SNR) and root-mean squared errors of the reconstructed images. Relative to conventional NLTV, NLTV with reweighted L1-norm was able to slightly improve SNR, while greatly increasing the contrast between tissues due to additional iterative reweighting process. Conclusion: NLTV min. can provide more precise compressed sensing based CT image reconstruction by incorporating the reweighted L1-norm, while maintaining greater robustness to the noise effect than TV min.« less
Advances in Pancreatic CT Imaging.
Almeida, Renata R; Lo, Grace C; Patino, Manuel; Bizzo, Bernardo; Canellas, Rodrigo; Sahani, Dushyant V
2018-07-01
The purpose of this article is to discuss the advances in CT acquisition and image postprocessing as they apply to imaging the pancreas and to conceptualize the role of radiogenomics and machine learning in pancreatic imaging. CT is the preferred imaging modality for assessment of pancreatic diseases. Recent advances in CT (dual-energy CT, CT perfusion, CT volumetry, and radiogenomics) and emerging computational algorithms (machine learning) have the potential to further increase the value of CT in pancreatic imaging.
Brain CT image similarity retrieval method based on uncertain location graph.
Pan, Haiwei; Li, Pengyuan; Li, Qing; Han, Qilong; Feng, Xiaoning; Gao, Linlin
2014-03-01
A number of brain computed tomography (CT) images stored in hospitals that contain valuable information should be shared to support computer-aided diagnosis systems. Finding the similar brain CT images from the brain CT image database can effectively help doctors diagnose based on the earlier cases. However, the similarity retrieval for brain CT images requires much higher accuracy than the general images. In this paper, a new model of uncertain location graph (ULG) is presented for brain CT image modeling and similarity retrieval. According to the characteristics of brain CT image, we propose a novel method to model brain CT image to ULG based on brain CT image texture. Then, a scheme for ULG similarity retrieval is introduced. Furthermore, an effective index structure is applied to reduce the searching time. Experimental results reveal that our method functions well on brain CT images similarity retrieval with higher accuracy and efficiency.
NASA Astrophysics Data System (ADS)
Cho, Hyo Sung; Woo, Tae Ho; Park, Chul Kyu
2016-10-01
Using the metal artifact property, it is analyzed for the X-ray computed tomography (CT) in the aspect of the security on the examined places like airport and surveillance areas. Since the importance of terror prevention strategy has been increased, the security application of X-ray CT has the significant remark. One shot X-ray image has the limitation to find out the exact shape to property in the closed box, which could be solved by the CT scanning without the tearing off the box in this work. Cleaner images can be obtained by the advanced technology if the CT scanning is utilized in the security purposes on the secured areas. A metal sample is treated by the metal artifact removal (MAR) method for the enhanced image. The mimicked explosive is experimented for the imaging processing application where the cleaner one is obtained. The procedure is explained and the further study is discussed.
Tomographic image reconstruction using x-ray phase information
NASA Astrophysics Data System (ADS)
Momose, Atsushi; Takeda, Tohoru; Itai, Yuji; Hirano, Keiichi
1996-04-01
We have been developing phase-contrast x-ray computed tomography (CT) to make possible the observation of biological soft tissues without contrast enhancement. Phase-contrast x-ray CT requires for its input data the x-ray phase-shift distributions or phase-mapping images caused by an object. These were measured with newly developed fringe-scanning x-ray interferometry. Phase-mapping images at different projection directions were obtained by rotating the object in an x-ray interferometer, and were processed with a standard CT algorithm. A phase-contrast x-ray CT image of a nonstained cancerous tissue was obtained using 17.7 keV synchrotron x rays with 12 micrometer voxel size, although the size of the observation area was at most 5 mm. The cancerous lesions were readily distinguishable from normal tissues. Moreover, fine structures corresponding to cancerous degeneration and fibrous tissues were clearly depicted. It is estimated that the present system is sensitive down to a density deviation of 4 mg/cm3.
Modeling of polychromatic attenuation using computed tomography reconstructed images
NASA Technical Reports Server (NTRS)
Yan, C. H.; Whalen, R. T.; Beaupre, G. S.; Yen, S. Y.; Napel, S.
1999-01-01
This paper presents a procedure for estimating an accurate model of the CT imaging process including spectral effects. As raw projection data are typically unavailable to the end-user, we adopt a post-processing approach that utilizes the reconstructed images themselves. This approach includes errors from x-ray scatter and the nonidealities of the built-in soft tissue correction into the beam characteristics, which is crucial to beam hardening correction algorithms that are designed to be applied directly to CT reconstructed images. We formulate this approach as a quadratic programming problem and propose two different methods, dimension reduction and regularization, to overcome ill conditioning in the model. For the regularization method we use a statistical procedure, Cross Validation, to select the regularization parameter. We have constructed step-wedge phantoms to estimate the effective beam spectrum of a GE CT-I scanner. Using the derived spectrum, we computed the attenuation ratios for the wedge phantoms and found that the worst case modeling error is less than 3% of the corresponding attenuation ratio. We have also built two test (hybrid) phantoms to evaluate the effective spectrum. Based on these test phantoms, we have shown that the effective beam spectrum provides an accurate model for the CT imaging process. Last, we used a simple beam hardening correction experiment to demonstrate the effectiveness of the estimated beam profile for removing beam hardening artifacts. We hope that this estimation procedure will encourage more independent research on beam hardening corrections and will lead to the development of application-specific beam hardening correction algorithms.
NASA Astrophysics Data System (ADS)
Dogan, M.; Moysey, S. M.; Mamun, A. A.; DeVol, T. A.; Powell, B. A.; Murdoch, L. C.
2017-12-01
Single Photon Emission Computed Tomography (SPECT) and x-ray Computed Tomography (CT) are both high-resolution imaging methods for investigating laboratory scale samples. We have recently conducted several experiments to determine the capabilities of two preclinical imaging systems; the imaging resolution of the two systems studied were found to be 0.2 mm for CT and 2-4 mm for SPECT depending on the tracer and scan times. While the resolution of these instruments is not sufficient for imaging the pore structure of most soils, it is sufficient to resolve macropore structures such as cracks and root channels and to observe their impact on transport. For example, we have used CT scans to monitor the formation of desiccation cracks within soils obtained from the Savannah River Site. We were then able to observe the interaction between the crack network and pore matrix during an infiltration experiment by spiking the infiltrating water with an iodide contrast agent as a tracer. We found a complex interaction between the flow systems, where flow shifted from matrix dominated at low flow rates to macropore dominated at high flow rates. SPECT imaging is capable of monitoring the distribution of gamma-ray emitting radionuclides in 3D. It is therefore also a useful tool for monitoring transport processes, but is particularly powerful when a redox sensitive isotope like 99mTc is used as the tracer. We show an example of a transport experiment where a 99mTc solution is passed through a column containing zones with different redox properties, i.e., a zone amended with titanomagnetite, another with anatase, and a third with silica flour. The 99mTc is captured by the strongly reducing materials, but not the zone with silica flour. The example illustrates how these imaging modalities can be used to discriminate between chemical and physical processes controlling fate and transport of the radionuclide. In particular, CT and SPECT can be used to image contaminant transport in lab scale columns by combining the structural information obtained from CT with the concentration distributions from SPECT.
Molecular imaging of malignant tumor metabolism: whole-body image fusion of DWI/CT vs. PET/CT.
Reiner, Caecilia S; Fischer, Michael A; Hany, Thomas; Stolzmann, Paul; Nanz, Daniel; Donati, Olivio F; Weishaupt, Dominik; von Schulthess, Gustav K; Scheffel, Hans
2011-08-01
To prospectively investigate the technical feasibility and performance of image fusion for whole-body diffusion-weighted imaging (wbDWI) and computed tomography (CT) to detect metastases using hybrid positron emission tomography/computed tomography (PET/CT) as reference standard. Fifty-two patients (60 ± 14 years; 18 women) with different malignant tumor disease examined by PET/CT for clinical reasons consented to undergo additional wbDWI at 1.5 Tesla. WbDWI was performed using a diffusion-weighted single-shot echo-planar imaging during free breathing. Images at b = 0 s/mm(2) and b = 700 s/mm(2) were acquired and apparent diffusion coefficient (ADC) maps were generated. Image fusion of wbDWI and CT (from PET/CT scan) was performed yielding for wbDWI/CT fused image data. One radiologist rated the success of image fusion and diagnostic image quality. The presence or absence of metastases on wbDWI/CT fused images was evaluated together with the separate wbDWI and CT images by two different, independent radiologists blinded to results from PET/CT. Detection rate and positive predictive values for diagnosing metastases was calculated. PET/CT examinations were used as reference standard. PET/CT identified 305 malignant lesions in 39 of 52 (75%) patients. WbDWI/CT image fusion was technically successful and yielded diagnostic image quality in 73% and 92% of patients, respectively. Interobserver agreement for the evaluation of wbDWI/CT images was κ = 0.78. WbDWI/CT identified 270 metastases in 43 of 52 (83%) patients. Overall detection rate and positive predictive value of wbDWI/CT was 89% (95% CI, 0.85-0.92) and 94% (95% CI, 0.92-0.97), respectively. WbDWI/CT image fusion is technically feasible in a clinical setting and allows the diagnostic assessment of metastatic tumor disease detecting nine of 10 lesions as compared with PET/CT. Copyright © 2011 AUR. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Otake, Y.; Leonard, S.; Reiter, A.; Rajan, P.; Siewerdsen, J. H.; Ishii, M.; Taylor, R. H.; Hager, G. D.
2015-03-01
We present a system for registering the coordinate frame of an endoscope to pre- or intra- operatively acquired CT data based on optimizing the similarity metric between an endoscopic image and an image predicted via rendering of CT. Our method is robust and semi-automatic because it takes account of physical constraints, specifically, collisions between the endoscope and the anatomy, to initialize and constrain the search. The proposed optimization method is based on a stochastic optimization algorithm that evaluates a large number of similarity metric functions in parallel on a graphics processing unit. Images from a cadaver and a patient were used for evaluation. The registration error was 0.83 mm and 1.97 mm for cadaver and patient images respectively. The average registration time for 60 trials was 4.4 seconds. The patient study demonstrated robustness of the proposed algorithm against a moderate anatomical deformation.
Varying-energy CT imaging method based on EM-TV
NASA Astrophysics Data System (ADS)
Chen, Ping; Han, Yan
2016-11-01
For complicated structural components with wide x-ray attenuation ranges, conventional fixed-energy computed tomography (CT) imaging cannot obtain all the structural information. This limitation results in a shortage of CT information because the effective thickness of the components along the direction of x-ray penetration exceeds the limit of the dynamic range of the x-ray imaging system. To address this problem, a varying-energy x-ray CT imaging method is proposed. In this new method, the tube voltage is adjusted several times with the fixed lesser interval. Next, the fusion of grey consistency and logarithm demodulation are applied to obtain full and lower noise projection with a high dynamic range (HDR). In addition, for the noise suppression problem of the analytical method, EM-TV (expectation maximization-total Jvariation) iteration reconstruction is used. In the process of iteration, the reconstruction result obtained at one x-ray energy is used as the initial condition of the next iteration. An accompanying experiment demonstrates that this EM-TV reconstruction can also extend the dynamic range of x-ray imaging systems and provide a higher reconstruction quality relative to the fusion reconstruction method.
Tensor-based Dictionary Learning for Spectral CT Reconstruction
Zhang, Yanbo; Wang, Ge
2016-01-01
Spectral computed tomography (CT) produces an energy-discriminative attenuation map of an object, extending a conventional image volume with a spectral dimension. In spectral CT, an image can be sparsely represented in each of multiple energy channels, and are highly correlated among energy channels. According to this characteristics, we propose a tensor-based dictionary learning method for spectral CT reconstruction. In our method, tensor patches are extracted from an image tensor, which is reconstructed using the filtered backprojection (FBP), to form a training dataset. With the Candecomp/Parafac decomposition, a tensor-based dictionary is trained, in which each atom is a rank-one tensor. Then, the trained dictionary is used to sparsely represent image tensor patches during an iterative reconstruction process, and the alternating minimization scheme is adapted for optimization. The effectiveness of our proposed method is validated with both numerically simulated and real preclinical mouse datasets. The results demonstrate that the proposed tensor-based method generally produces superior image quality, and leads to more accurate material decomposition than the currently popular popular methods. PMID:27541628
Novel SPECT Technologies and Approaches in Cardiac Imaging
Slomka, Piotr; Hung, Guang-Uei; Germano, Guido; Berman, Daniel S.
2017-01-01
Recent novel approaches in myocardial perfusion single photon emission CT (SPECT) have been facilitated by new dedicated high-efficiency hardware with solid-state detectors and optimized collimators. New protocols include very low-dose (1 mSv) stress-only, two-position imaging to mitigate attenuation artifacts, and simultaneous dual-isotope imaging. Attenuation correction can be performed by specialized low-dose systems or by previously obtained CT coronary calcium scans. Hybrid protocols using CT angiography have been proposed. Image quality improvements have been demonstrated by novel reconstructions and motion correction. Fast SPECT acquisition facilitates dynamic flow and early function measurements. Image processing algorithms have become automated with virtually unsupervised extraction of quantitative imaging variables. This automation facilitates integration with clinical variables derived by machine learning to predict patient outcome or diagnosis. In this review, we describe new imaging protocols made possible by the new hardware developments. We also discuss several novel software approaches for the quantification and interpretation of myocardial perfusion SPECT scans. PMID:29034066
Processing of CT sinograms acquired using a VRX detector
NASA Astrophysics Data System (ADS)
Jordan, Lawrence M.; DiBianca, Frank A.; Zou, Ping; Laughter, Joseph S.; Zeman, Herbert D.
2000-04-01
A 'variable resolution x-ray detector' (VRX) capable of resolving beyond 100 cycles/main a single dimension has been proposed by DiBianca, et al. The use of detectors of this design for computed-tomography (CT) imaging requires novel preprocessing of data to correct for the detector's non- uniform imaging characteristics over its range of view. This paper describes algorithms developed specifically to adjust VRX data for varying magnification, source-to-detector range and beam obliquity and to sharpen reconstructions by deconvolving the ray impulse function. The preprocessing also incorporates nonlinear interpolation of VRX raw data into canonical CT sinogram formats.
Body-wide anatomy recognition in PET/CT images
NASA Astrophysics Data System (ADS)
Wang, Huiqian; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Zhao, Liming; Torigian, Drew A.
2015-03-01
With the rapid growth of positron emission tomography/computed tomography (PET/CT)-based medical applications, body-wide anatomy recognition on whole-body PET/CT images becomes crucial for quantifying body-wide disease burden. This, however, is a challenging problem and seldom studied due to unclear anatomy reference frame and low spatial resolution of PET images as well as low contrast and spatial resolution of the associated low-dose CT images. We previously developed an automatic anatomy recognition (AAR) system [15] whose applicability was demonstrated on diagnostic computed tomography (CT) and magnetic resonance (MR) images in different body regions on 35 objects. The aim of the present work is to investigate strategies for adapting the previous AAR system to low-dose CT and PET images toward automated body-wide disease quantification. Our adaptation of the previous AAR methodology to PET/CT images in this paper focuses on 16 objects in three body regions - thorax, abdomen, and pelvis - and consists of the following steps: collecting whole-body PET/CT images from existing patient image databases, delineating all objects in these images, modifying the previous hierarchical models built from diagnostic CT images to account for differences in appearance in low-dose CT and PET images, automatically locating objects in these images following object hierarchy, and evaluating performance. Our preliminary evaluations indicate that the performance of the AAR approach on low-dose CT images achieves object localization accuracy within about 2 voxels, which is comparable to the accuracies achieved on diagnostic contrast-enhanced CT images. Object recognition on low-dose CT images from PET/CT examinations without requiring diagnostic contrast-enhanced CT seems feasible.
CT Image Sequence Processing For Wood Defect Recognition
Dongping Zhu; R.W. Conners; Philip A. Araman
1991-01-01
The research reported in this paper explores a non-destructive testing application of x-ray computed tomography (CT) in the forest products industry. This application involves a computer vision system that uses CT to locate and identify internal defects in hardwood logs. The knowledge of log defects is critical in deciding whether to veneer or to saw up a log, and how...
Time-Domain Terahertz Computed Axial Tomography NDE System
NASA Technical Reports Server (NTRS)
Zimdars, David
2012-01-01
NASA has identified the need for advanced non-destructive evaluation (NDE) methods to characterize aging and durability in aircraft materials to improve the safety of the nation's airline fleet. 3D THz tomography can play a major role in detection and characterization of flaws and degradation in aircraft materials, including Kevlar-based composites and Kevlar and Zylon fabric covers for soft-shell fan containment where aging and durability issues are critical. A prototype computed tomography (CT) time-domain (TD) THz imaging system has been used to generate 3D images of several test objects including a TUFI tile (a thermal protection system tile used on the Space Shuttle and possibly the Orion or similar capsules). This TUFI tile had simulated impact damage that was located and the depth of damage determined. The CT motion control gan try was designed and constructed, and then integrated with a T-Ray 4000 control unit and motion controller to create a complete CT TD-THz imaging system prototype. A data collection software script was developed that takes multiple z-axis slices in sequence and saves the data for batch processing. The data collection software was integrated with the ability to batch process the slice data with the CT TD-THz image reconstruction software. The time required to take a single CT slice was decreased from six minutes to approximately one minute by replacing the 320 ps, 100-Hz waveform acquisition system with an 80 ps, 1,000-Hz waveform acquisition system. The TD-THZ computed tomography system was built from pre-existing commercial off-the-shelf subsystems. A CT motion control gantry was constructed from COTS components that can handle larger samples. The motion control gantry allows inspection of sample sizes of up to approximately one cubic foot (.0.03 cubic meters). The system reduced to practice a CT-TDTHz system incorporating a COTS 80- ps/l-kHz waveform scanner. The incorporation of this scanner in the system allows acquisition of 3D slice data with better signal-to-noise using a COTS scanner rather than the gchirped h scanner. The system also reduced to practice a prototype for commercial CT systems for insulating materials where safety concerns cannot accommodate x-ray. A software script was written to automate the COTS software to collect and process TD-THz CT data.
Quirce, R; Martínez-Rodríguez, I; Banzo, I; de Arcocha-Torres, M; Jiménez-Bonilla, J F; Martínez-Amador, N; Ibáñez-Bravo, S; Ramos, L; Amado, J A; Carril, J M
2015-01-01
Diabetes is a major frequent cause of atherosclerosis vascular disease. Arterial calcification in diabetic patients is responsible for peripheral vascular involvement. Molecular imaging using (18)F-sodium fluoride ((18)F-NaF) positron emission tomography (PET)/computed tomography (CT) has been recently proposed as a marker to study the in vivo mineralization process in the atheroma plaque. A 69-year-old man with a history of type 2 diabetes and no clinical evidence of peripheral arterial disease underwent an (18)F-NaF PET/CT scan. A linear, well-defined (18)F-NaF uptake was detected along the femoral arteries. In addition, the CT component of the PET/CT identified an unsuspected "tram-track" calcification in his femoral arteries, suggestive of medial calcification (Mönckeberg's sclerosis). In other vascular territories, focal (18)F-NaF uptake was also detected in carotid and aorta atheroma plaques. Molecular imaging with (18)F-NaF PET/CT might provide new functional information about the in vivo vascular calcification process in diabetic patients. Copyright © 2015 Elsevier España, S.L.U. and SEMNIM. All rights reserved.
Value of PET/CT 3D visualization of head and neck squamous cell carcinoma extended to mandible.
Lopez, R; Gantet, P; Julian, A; Hitzel, A; Herbault-Barres, B; Alshehri, S; Payoux, P
2018-05-01
To study an original 3D visualization of head and neck squamous cell carcinoma extending to the mandible by using [18F]-NaF PET/CT and [18F]-FDG PET/CT imaging along with a new innovative FDG and NaF image analysis using dedicated software. The main interest of the 3D evaluation is to have a better visualization of bone extension in such cancers and that could also avoid unsatisfying surgical treatment later on. A prospective study was carried out from November 2016 to September 2017. Twenty patients with head and neck squamous cell carcinoma extending to the mandible (stage 4 in the UICC classification) underwent [18F]-NaF and [18F]-FDG PET/CT. We compared the delineation of 3D quantification obtained with [18F]-NaF and [18F]-FDG PET/CT. In order to carry out this comparison, a method of visualisation and quantification of PET images was developed. This new approach was based on a process of quantification of radioactive activity within the mandibular bone that objectively defined the significant limits of this activity on PET images and on a 3D visualization. Furthermore, the spatial limits obtained by analysis of the PET/CT 3D images were compared to those obtained by histopathological examination of mandibular resection which confirmed intraosseous extension to the mandible. The [18F]-NaF PET/CT imaging confirmed the mandibular extension in 85% of cases and was not shown in [18F]-FDG PET/CT imaging. The [18F]-NaF PET/CT was significantly more accurate than [18F]-FDG PET/CT in 3D assessment of intraosseous extension of head and neck squamous cell carcinoma. This new 3D information shows the importance in the imaging approach of cancers. All cases of mandibular extension suspected on [18F]-NaF PET/CT imaging were confirmed based on histopathological results as a reference. The [18F]-NaF PET/CT 3D visualization should be included in the pre-treatment workups of head and neck cancers. With the use of a dedicated software which enables objective delineation of radioactive activity within the bone, it gives a very encouraging results. The [18F]-FDG PET/CT appears insufficient to confirm mandibular extension. This new 3D simulation management is expected to avoid under treatment of patients with intraosseous mandibular extension of head and neck cancers. However, there is also a need for a further study that will compare the interest of PET/CT and PET/MRI in this indication. Copyright © 2018 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.
SU-E-J-90: MRI-Based Treatment Simulation and Patient Setup for Radiation Therapy of Brain Cancer
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Y; Cao, M; Han, F
2014-06-01
Purpose: Traditional radiation therapy of cancer is heavily dependent on CT. CT provides excellent depiction of the bones but lacks good soft tissue contrast, which makes contouring difficult. Often, MRIs are fused with CT to take advantage of its superior soft tissue contrast. Such an approach has drawbacks. It is desirable to perform treatment simulation entirely based on MRI. To achieve MR-based simulation for radiation therapy, bone imaging is an important challenge because of the low MR signal intensity from bone due to its ultra-short T2 and T1, which presents difficulty for both dose calculation and patient setup in termsmore » of digitally reconstructed radiograph (DRR) generation. Current solutions will either require manual bone contouring or multiple MR scans. We present a technique to generate DRR using MRI with an Ultra Short Echo Time (UTE) sequence which is applicable to both OBI and ExacTrac 2D patient setup. Methods: Seven brain cancer patients were scanned at 1.5 Tesla using a radial UTE sequence. The sequence acquires two images at two different echo times. The two images were processed using in-house software. The resultant bone images were subsequently loaded into commercial systems to generate DRRs. Simulation and patient clinical on-board images were used to evaluate 2D patient setup with MRI-DRRs. Results: The majority bones are well visualized in all patients. The fused image of patient CT with the MR bone image demonstrates the accuracy of automatic bone identification using our technique. The generated DRR is of good quality. Accuracy of 2D patient setup by using MRI-DRR is comparable to CT-based 2D patient setup. Conclusion: This study shows the potential of DRR generation with single MR sequence. Further work will be needed on MR sequence development and post-processing procedure to achieve robust MR bone imaging for other human sites in addition to brain.« less
Demons deformable registration of CT and cone-beam CT using an iterative intensity matching approach
Nithiananthan, Sajendra; Schafer, Sebastian; Uneri, Ali; Mirota, Daniel J.; Stayman, J. Webster; Zbijewski, Wojciech; Brock, Kristy K.; Daly, Michael J.; Chan, Harley; Irish, Jonathan C.; Siewerdsen, Jeffrey H.
2011-01-01
Purpose: A method of intensity-based deformable registration of CT and cone-beam CT (CBCT) images is described, in which intensity correction occurs simultaneously within the iterative registration process. The method preserves the speed and simplicity of the popular Demons algorithm while providing robustness and accuracy in the presence of large mismatch between CT and CBCT voxel values (“intensity”). Methods: A variant of the Demons algorithm was developed in which an estimate of the relationship between CT and CBCT intensity values for specific materials in the image is computed at each iteration based on the set of currently overlapping voxels. This tissue-specific intensity correction is then used to estimate the registration output for that iteration and the process is repeated. The robustness of the method was tested in CBCT images of a cadaveric head exhibiting a broad range of simulated intensity variations associated with x-ray scatter, object truncation, and∕or errors in the reconstruction algorithm. The accuracy of CT-CBCT registration was also measured in six real cases, exhibiting deformations ranging from simple to complex during surgery or radiotherapy guided by a CBCT-capable C-arm or linear accelerator, respectively. Results: The iterative intensity matching approach was robust against all levels of intensity variation examined, including spatially varying errors in voxel value of a factor of 2 or more, as can be encountered in cases of high x-ray scatter. Registration accuracy without intensity matching degraded severely with increasing magnitude of intensity error and introduced image distortion. A single histogram match performed prior to registration alleviated some of these effects but was also prone to image distortion and was quantifiably less robust and accurate than the iterative approach. Within the six case registration accuracy study, iterative intensity matching Demons reduced mean TRE to (2.5±2.8) mm compared to (3.5±3.0) mm with rigid registration. Conclusions: A method was developed to iteratively correct CT-CBCT intensity disparity during Demons registration, enabling fast, intensity-based registration in CBCT-guided procedures such as surgery and radiotherapy, in which CBCT voxel values may be inaccurate. Accurate CT-CBCT registration in turn facilitates registration of multimodality preoperative image and planning data to intraoperative CBCT by way of the preoperative CT, thereby linking the intraoperative frame of reference to a wealth of preoperative information that could improve interventional guidance. PMID:21626913
Demons deformable registration of CT and cone-beam CT using an iterative intensity matching approach
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nithiananthan, Sajendra; Schafer, Sebastian; Uneri, Ali
2011-04-15
Purpose: A method of intensity-based deformable registration of CT and cone-beam CT (CBCT) images is described, in which intensity correction occurs simultaneously within the iterative registration process. The method preserves the speed and simplicity of the popular Demons algorithm while providing robustness and accuracy in the presence of large mismatch between CT and CBCT voxel values (''intensity''). Methods: A variant of the Demons algorithm was developed in which an estimate of the relationship between CT and CBCT intensity values for specific materials in the image is computed at each iteration based on the set of currently overlapping voxels. This tissue-specificmore » intensity correction is then used to estimate the registration output for that iteration and the process is repeated. The robustness of the method was tested in CBCT images of a cadaveric head exhibiting a broad range of simulated intensity variations associated with x-ray scatter, object truncation, and/or errors in the reconstruction algorithm. The accuracy of CT-CBCT registration was also measured in six real cases, exhibiting deformations ranging from simple to complex during surgery or radiotherapy guided by a CBCT-capable C-arm or linear accelerator, respectively. Results: The iterative intensity matching approach was robust against all levels of intensity variation examined, including spatially varying errors in voxel value of a factor of 2 or more, as can be encountered in cases of high x-ray scatter. Registration accuracy without intensity matching degraded severely with increasing magnitude of intensity error and introduced image distortion. A single histogram match performed prior to registration alleviated some of these effects but was also prone to image distortion and was quantifiably less robust and accurate than the iterative approach. Within the six case registration accuracy study, iterative intensity matching Demons reduced mean TRE to (2.5{+-}2.8) mm compared to (3.5{+-}3.0) mm with rigid registration. Conclusions: A method was developed to iteratively correct CT-CBCT intensity disparity during Demons registration, enabling fast, intensity-based registration in CBCT-guided procedures such as surgery and radiotherapy, in which CBCT voxel values may be inaccurate. Accurate CT-CBCT registration in turn facilitates registration of multimodality preoperative image and planning data to intraoperative CBCT by way of the preoperative CT, thereby linking the intraoperative frame of reference to a wealth of preoperative information that could improve interventional guidance.« less
Instrumentation in molecular imaging.
Wells, R Glenn
2016-12-01
In vivo molecular imaging is a challenging task and no single type of imaging system provides an ideal solution. Nuclear medicine techniques like SPECT and PET provide excellent sensitivity but have poor spatial resolution. Optical imaging has excellent sensitivity and spatial resolution, but light photons interact strongly with tissues and so only small animals and targets near the surface can be accurately visualized. CT and MRI have exquisite spatial resolution, but greatly reduced sensitivity. To overcome the limitations of individual modalities, molecular imaging systems often combine individual cameras together, for example, merging nuclear medicine cameras with CT or MRI to allow the visualization of molecular processes with both high sensitivity and high spatial resolution.
Review methods for image segmentation from computed tomography images
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mamat, Nurwahidah; Rahman, Wan Eny Zarina Wan Abdul; Soh, Shaharuddin Cik
Image segmentation is a challenging process in order to get the accuracy of segmentation, automation and robustness especially in medical images. There exist many segmentation methods that can be implemented to medical images but not all methods are suitable. For the medical purposes, the aims of image segmentation are to study the anatomical structure, identify the region of interest, measure tissue volume to measure growth of tumor and help in treatment planning prior to radiation therapy. In this paper, we present a review method for segmentation purposes using Computed Tomography (CT) images. CT images has their own characteristics that affectmore » the ability to visualize anatomic structures and pathologic features such as blurring of the image and visual noise. The details about the methods, the goodness and the problem incurred in the methods will be defined and explained. It is necessary to know the suitable segmentation method in order to get accurate segmentation. This paper can be a guide to researcher to choose the suitable segmentation method especially in segmenting the images from CT scan.« less
Axial segmentation of lungs CT scan images using canny method and morphological operation
NASA Astrophysics Data System (ADS)
Noviana, Rina; Febriani, Rasal, Isram; Lubis, Eva Utari Cintamurni
2017-08-01
Segmentation is a very important topic in digital image process. It is found simply in varied fields of image analysis, particularly within the medical imaging field. Axial segmentation of lungs CT scan is beneficial in designation of abnormalities and surgery planning. It will do to ascertain every section within the lungs. The results of the segmentation are accustomed discover the presence of nodules. The method which utilized in this analysis are image cropping, image binarization, Canny edge detection and morphological operation. Image cropping is done so as to separate the lungs areas, that is the region of interest. Binarization method generates a binary image that has 2 values with grey level, that is black and white (ROI), from another space of lungs CT scan image. Canny method used for the edge detection. Morphological operation is applied to smoothing the lungs edge. The segmentation methodology shows an honest result. It obtains an awfully smooth edge. Moreover, the image background can also be removed in order to get the main focus, the lungs.
TH-AB-BRA-04: Dosimetric Evaluation of MR-Guided HDR Brachytherapy Planning for Cervical Cancer
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kamio, Y; Barkati, M; Beliveau-Nadeau, D
2016-06-15
Purpose: To perform a retrospective study on 16 patients that had both CT and T2-weighted MR scans done at first fraction using the Utrecht CT/MR applicator (Elekta Brachytherapy) in order to evaluate uncertainties associated with an MR-only planning workflow. Methods: MR-workflow uncertainties were classified in three categories: reconstruction, registration and contouring. A systematic comparison of the CT and MR contouring, manual reconstruction and optimization process was performed to evaluate the impact of these uncertainties on the recommended GEC ESTRO DVH parameters: D90% and V100% for HR-CTV as well as D2cc for bladder, rectum, sigmoid colon and small bowel. This comparisonmore » was done using the following four steps: 1. Catheter reconstruction done on MR images with original CT-plan contours and dwell times. 2. OAR contours adjusted on MR images with original CT-plan reconstruction and dwell times. 3. Both reconstruction and contours done on MR images with original CT-plan dwell times. 4. Entire MR-based workflow optimized dwell times reimported to the original CT-plan. Results: The MR-based reconstruction process showed average D2cc deviations of 4.5 ± 3.0%, 1.5 ± 2.0%, 2.5 ± 2.0% and 2.0 ± 1.0% for the bladder, rectum, sigmoid colon and small bowels respectively with a maximum of 10%, 6%, 6% and 4%. The HR-CTV’s D90% and V100% average deviations was found to be 4.0 ± 3.0%, and 2.0 ± 2.0% respectively with a maximum of 10% and 6%. Adjusting contours on MR-images was found to have a similar impact. Finally, the optimized MR-based workflow dwell times were found to still give acceptable plans when re-imported to the original CT-plan which validated the entire workflow. Conclusion: This work illustrates a systematic validation method for centers wanting to move towards an MR-only workflow. This work will be expanded to model based reconstruction, PD-weighted images and other types of applicators.« less
3D temporal subtraction on multislice CT images using nonlinear warping technique
NASA Astrophysics Data System (ADS)
Ishida, Takayuki; Katsuragawa, Shigehiko; Kawashita, Ikuo; Kim, Hyounseop; Itai, Yoshinori; Awai, Kazuo; Li, Qiang; Doi, Kunio
2007-03-01
The detection of very subtle lesions and/or lesions overlapped with vessels on CT images is a time consuming and difficult task for radiologists. In this study, we have developed a 3D temporal subtraction method to enhance interval changes between previous and current multislice CT images based on a nonlinear image warping technique. Our method provides a subtraction CT image which is obtained by subtraction of a previous CT image from a current CT image. Reduction of misregistration artifacts is important in the temporal subtraction method. Therefore, our computerized method includes global and local image matching techniques for accurate registration of current and previous CT images. For global image matching, we selected the corresponding previous section image for each current section image by using 2D cross-correlation between a blurred low-resolution current CT image and a blurred previous CT image. For local image matching, we applied the 3D template matching technique with translation and rotation of volumes of interests (VOIs) which were selected in the current and the previous CT images. The local shift vector for each VOI pair was determined when the cross-correlation value became the maximum in the 3D template matching. The local shift vectors at all voxels were determined by interpolation of shift vectors of VOIs, and then the previous CT image was nonlinearly warped according to the shift vector for each voxel. Finally, the warped previous CT image was subtracted from the current CT image. The 3D temporal subtraction method was applied to 19 clinical cases. The normal background structures such as vessels, ribs, and heart were removed without large misregistration artifacts. Thus, interval changes due to lung diseases were clearly enhanced as white shadows on subtraction CT images.
[Mobile CT: technical aspects of prehospital stroke imaging before intravenous thrombolysis].
Gierhake, D; Weber, J E; Villringer, K; Ebinger, M; Audebert, H J; Fiebach, J B
2013-01-01
To reduce the time from symptom onset to treatment with tissue plasminogen activator (tPA) in ischemic stroke, an ambulance was equipped with a CT scanner. We analyzed process and image quality of CT scanning during the pilot study regarding image quality and safety issues. The pilot study of a stroke emergency mobile unit (STEMO) ran over a period of 12 weeks on 5 weekdays from 7a.m. to 6:30 p.m. A teleradiological service for the justifying indication and reporting was established. The radiographer was responsible for the performance of the CT scan on the ambulance. 64 cranial CT scans and 1 intracranial CT angiography were performed. We compared times from ambulance alarm to treatment decision (time of last brain scan) with a cohort of 50 consecutive tPA treatments before implementation of STEMO. 62 (95%) of the 65 scans performed had sufficient quality for reading. Technical quality was not optimal in 45 cases (69%) mainly caused by suboptimal positioning of patient or eye lens protection. Motion artefacts were observed in 8 exams (12%). No safety issues occurred for team or patients. 23 patients were treated with thrombolysis. Time from alarm to last CT scan was 18 minutes shorter than in the tPA cohort before STEMO implementation. A teleradiological support for primary stroke imaging by CT on-site is feasible, quality-wise of diagnostic value and has not raised safety issues. © Georg Thieme Verlag KG Stuttgart · New York.
Deep learning methods for CT image-domain metal artifact reduction
NASA Astrophysics Data System (ADS)
Gjesteby, Lars; Yang, Qingsong; Xi, Yan; Shan, Hongming; Claus, Bernhard; Jin, Yannan; De Man, Bruno; Wang, Ge
2017-09-01
Artifacts resulting from metal objects have been a persistent problem in CT images over the last four decades. A common approach to overcome their effects is to replace corrupt projection data with values synthesized from an interpolation scheme or by reprojection of a prior image. State-of-the-art correction methods, such as the interpolation- and normalization-based algorithm NMAR, often do not produce clinically satisfactory results. Residual image artifacts remain in challenging cases and even new artifacts can be introduced by the interpolation scheme. Metal artifacts continue to be a major impediment, particularly in radiation and proton therapy planning as well as orthopedic imaging. A new solution to the long-standing metal artifact reduction (MAR) problem is deep learning, which has been successfully applied to medical image processing and analysis tasks. In this study, we combine a convolutional neural network (CNN) with the state-of-the-art NMAR algorithm to reduce metal streaks in critical image regions. Training data was synthesized from CT simulation scans of a phantom derived from real patient images. The CNN is able to map metal-corrupted images to artifact-free monoenergetic images to achieve additional correction on top of NMAR for improved image quality. Our results indicate that deep learning is a novel tool to address CT reconstruction challenges, and may enable more accurate tumor volume estimation for radiation therapy planning.
Quantifying Three-Dimensional Morphology and RNA from Individual Embryos
Green, Rebecca M.; Leach, Courtney L.; Hoehn, Natasha; Marcucio, Ralph S.; Hallgrímsson, Benedikt
2017-01-01
Quantitative analysis of morphogenesis aids our understanding of developmental processes by providing a method to link changes in shape with cellular and molecular processes. Over the last decade many methods have been developed for 3D imaging of embryos using microCT scanning to quantify the shape of embryos during development. These methods generally involve a powerful, cross-linking fixative such as paraformaldehyde to limit shrinkage during the CT scan. However, the extended time frames that these embryos are incubated in such fixatives prevent use of the tissues for molecular analysis after microCT scanning. This is a significant problem because it limits the ability to correlate variation in molecular data with morphology at the level of individual embryos. Here, we outline a novel method that allows RNA, DNA or protein isolation following CT scan while also allowing imaging of different tissue layers within the developing embryo. We show shape differences early in craniofacial development (E11.5) between common mouse genetic backgrounds, and demonstrate that we are able to generate RNA from these embryos after CT scanning that is suitable for downstream RT-PCR and RNAseq analyses. PMID:28152580
CT to Cone-beam CT Deformable Registration With Simultaneous Intensity Correction
Zhen, Xin; Gu, Xuejun; Yan, Hao; Zhou, Linghong; Jia, Xun; Jiang, Steve B.
2012-01-01
Computed tomography (CT) to cone-beam computed tomography (CBCT) deformable image registration (DIR) is a crucial step in adaptive radiation therapy. Current intensity-based registration algorithms, such as demons, may fail in the context of CT-CBCT DIR because of inconsistent intensities between the two modalities. In this paper, we propose a variant of demons, called Deformation with Intensity Simultaneously Corrected (DISC), to deal with CT-CBCT DIR. DISC distinguishes itself from the original demons algorithm by performing an adaptive intensity correction step on the CBCT image at every iteration step of the demons registration. Specifically, the intensity correction of a voxel in CBCT is achieved by matching the first and the second moments of the voxel intensities inside a patch around the voxel with those on the CT image. It is expected that such a strategy can remove artifacts in the CBCT image, as well as ensuring the intensity consistency between the two modalities. DISC is implemented on computer graphics processing units (GPUs) in compute unified device architecture (CUDA) programming environment. The performance of DISC is evaluated on a simulated patient case and six clinical head-and-neck cancer patient data. It is found that DISC is robust against the CBCT artifacts and intensity inconsistency and significantly improves the registration accuracy when compared with the original demons. PMID:23032638
Geometric correction method for 3d in-line X-ray phase contrast image reconstruction
2014-01-01
Background Mechanical system with imperfect or misalignment of X-ray phase contrast imaging (XPCI) components causes projection data misplaced, and thus result in the reconstructed slice images of computed tomography (CT) blurred or with edge artifacts. So the features of biological microstructures to be investigated are destroyed unexpectedly, and the spatial resolution of XPCI image is decreased. It makes data correction an essential pre-processing step for CT reconstruction of XPCI. Methods To remove unexpected blurs and edge artifacts, a mathematics model for in-line XPCI is built by considering primary geometric parameters which include a rotation angle and a shift variant in this paper. Optimal geometric parameters are achieved by finding the solution of a maximization problem. And an iterative approach is employed to solve the maximization problem by using a two-step scheme which includes performing a composite geometric transformation and then following a linear regression process. After applying the geometric transformation with optimal parameters to projection data, standard filtered back-projection algorithm is used to reconstruct CT slice images. Results Numerical experiments were carried out on both synthetic and real in-line XPCI datasets. Experimental results demonstrate that the proposed method improves CT image quality by removing both blurring and edge artifacts at the same time compared to existing correction methods. Conclusions The method proposed in this paper provides an effective projection data correction scheme and significantly improves the image quality by removing both blurring and edge artifacts at the same time for in-line XPCI. It is easy to implement and can also be extended to other XPCI techniques. PMID:25069768
Aortic annulus sizing using watershed transform and morphological approach for CT images
NASA Astrophysics Data System (ADS)
Mohammad, Norhasmira; Omar, Zaid; Sahrim, Mus'ab
2018-02-01
Aortic valve disease occurs due to calcification deposits on the area of leaflets within the human heart. It is progressive over time where it can affect the mechanism of the heart valve. To avoid the risk of surgery for vulnerable patients especially senior citizens, a new method has been introduced: Transcatheter Aortic Valve Implantation (TAVI), which places a synthetic catheter within the patient's valve. This entails a procedure of aortic annulus sizing, which requires manual measurement of the scanned images acquired from Computed Tomographic (CT) by experts. The step requires intensive efforts, though human error may still eventually lead to false measurement. In this research, image processing techniques are implemented onto cardiac CT images to achieve an automated and accurate measurement of the heart annulus. The image is first put through pre-processing for noise filtration and image enhancement. Then, a marker image is computed using the combination of opening and closing operations where the foreground image is marked as a feature while the background image is set to zero. Marker image is used to control the watershed transformation and also to prevent oversegmentation. This transformation has the advantage of fast computational and oversegmentation problems, which usually appear with the watershed transform can be solved with the introduction of marker image. Finally, the measurement of aortic annulus from the image data is obtained through morphological operations. Results affirm the approach's ability to achieve accurate annulus measurements compared to conventional techniques.
The continual innovation of commercial PET/CT solutions in nuclear cardiology: Siemens Healthineers.
Bendriem, Bernard; Reed, Jessie; McCullough, Kathryn; Khan, Mohammad Raza; Smith, Anne M; Thomas, Damita; Long, Misty
2018-04-10
Cardiac PET/CT is an evolving, non-invasive imaging modality that impacts patient management in many clinical scenarios. Beyond offering the capability to assess myocardial perfusion, inflammatory cardiac pathologies, and myocardial viability, cardiac PET/CT also allows for the non-invasive quantitative assessment of myocardial blood flow (MBF) and myocardial flow reserve (MFR). Recognizing the need for an enhanced comprehension of coronary physiology, Siemens Healthineers implemented a sophisticated solution for the calculation of MBF and MFR in 2009. As a result, each aspect of their innovative scanner and image-processing technology seamlessly integrates into an efficient, easy-to-use workflow for everyday clinical use that maximizes the number of patients who potentially benefit from this imaging modality.
Image Processing Diagnostics: Emphysema
NASA Astrophysics Data System (ADS)
McKenzie, Alex
2009-10-01
Currently the computerized tomography (CT) scan can detect emphysema sooner than traditional x-rays, but other tests are required to measure more accurately the amount of affected lung. CT scan images show clearly if a patient has emphysema, but is unable by visual scan alone, to quantify the degree of the disease, as it appears merely as subtle, barely distinct, dark spots on the lung. Our goal is to create a software plug-in to interface with existing open source medical imaging software, to automate the process of accurately diagnosing and determining emphysema severity levels in patients. This will be accomplished by performing a number of statistical calculations using data taken from CT scan images of several patients representing a wide range of severity of the disease. These analyses include an examination of the deviation from a normal distribution curve to determine skewness, a commonly used statistical parameter. Our preliminary results show that this method of assessment appears to be more accurate and robust than currently utilized methods which involve looking at percentages of radiodensities in air passages of the lung.
al Mahbub, Asheque; Haque, Asadul
2016-01-01
This paper presents the results of X-ray CT imaging of the microstructure of sand particles subjected to high pressure one-dimensional compression leading to particle crushing. A high resolution X-ray CT machine capable of in situ imaging was employed to capture images of the whole volume of a sand sample subjected to compressive stresses up to 79.3 MPa. Images of the whole sample obtained at different load stages were analysed using a commercial image processing software (Avizo) to reveal various microstructural properties, such as pore and particle volume distributions, spatial distribution of void ratios, relative breakage, and anisotropy of particles. PMID:28774011
Al Mahbub, Asheque; Haque, Asadul
2016-11-03
This paper presents the results of X-ray CT imaging of the microstructure of sand particles subjected to high pressure one-dimensional compression leading to particle crushing. A high resolution X-ray CT machine capable of in situ imaging was employed to capture images of the whole volume of a sand sample subjected to compressive stresses up to 79.3 MPa. Images of the whole sample obtained at different load stages were analysed using a commercial image processing software (Avizo) to reveal various microstructural properties, such as pore and particle volume distributions, spatial distribution of void ratios, relative breakage, and anisotropy of particles.
Low dose reconstruction algorithm for differential phase contrast imaging.
Wang, Zhentian; Huang, Zhifeng; Zhang, Li; Chen, Zhiqiang; Kang, Kejun; Yin, Hongxia; Wang, Zhenchang; Marco, Stampanoni
2011-01-01
Differential phase contrast imaging computed tomography (DPCI-CT) is a novel x-ray inspection method to reconstruct the distribution of refraction index rather than the attenuation coefficient in weakly absorbing samples. In this paper, we propose an iterative reconstruction algorithm for DPCI-CT which benefits from the new compressed sensing theory. We first realize a differential algebraic reconstruction technique (DART) by discretizing the projection process of the differential phase contrast imaging into a linear partial derivative matrix. In this way the compressed sensing reconstruction problem of DPCI reconstruction can be transformed to a resolved problem in the transmission imaging CT. Our algorithm has the potential to reconstruct the refraction index distribution of the sample from highly undersampled projection data. Thus it can significantly reduce the dose and inspection time. The proposed algorithm has been validated by numerical simulations and actual experiments.
Tsai, I-Chen; Goo, Hyun Woo
2013-06-01
In the past 12 years, during the process of imaging congenital heart disease (CHD), Asian doctors have not only made every effort to adhere to established magnetic resonance imaging (MRI) protocols as in Western countries, but also have developed Computed tomography (CT) as an alternative problem-solving technique. Databases have shown that Asian doctors were more inclined to utilize CT than MRI in evaluating CHD. Articles in the literature focusing on CT have been cited more frequently than articles on MRI. Additionally, several repeatedly cited CT articles have become seminal papers in this field. The database reflects a trend suggesting that Asian doctors actively adapt to new techniques and flexibly develop unique strategies to overcome limitations caused by the relatively limited resources often available to them.
Improving Low-dose Cardiac CT Images based on 3D Sparse Representation
Shi, Luyao; Hu, Yining; Chen, Yang; Yin, Xindao; Shu, Huazhong; Luo, Limin; Coatrieux, Jean-Louis
2016-01-01
Cardiac computed tomography (CCT) is a reliable and accurate tool for diagnosis of coronary artery diseases and is also frequently used in surgery guidance. Low-dose scans should be considered in order to alleviate the harm to patients caused by X-ray radiation. However, low dose CT (LDCT) images tend to be degraded by quantum noise and streak artifacts. In order to improve the cardiac LDCT image quality, a 3D sparse representation-based processing (3D SR) is proposed by exploiting the sparsity and regularity of 3D anatomical features in CCT. The proposed method was evaluated by a clinical study of 14 patients. The performance of the proposed method was compared to the 2D spares representation-based processing (2D SR) and the state-of-the-art noise reduction algorithm BM4D. The visual assessment, quantitative assessment and qualitative assessment results show that the proposed approach can lead to effective noise/artifact suppression and detail preservation. Compared to the other two tested methods, 3D SR method can obtain results with image quality most close to the reference standard dose CT (SDCT) images. PMID:26980176
High-Resolution 4D Imaging of Technetium Transport in Porous Media using Preclinical SPECT-CT
NASA Astrophysics Data System (ADS)
Dogan, M.; DeVol, T. A.; Groen, H.; Moysey, S. M.; Ramakers, R.; Powell, B. A.
2015-12-01
Preclinical SPECT-CT (single-photon emission computed tomography with integrated X-ray computed tomography) offers the potential to quantitatively image the dynamic three-dimensional distribution of radioisotopes with sub-millimeter resolution, overlaid with structural CT images (20-200 micron resolution), making this an attractive method for studying transport in porous media. A preclinical SPECT-CT system (U-SPECT4CT, MILabs BV. Utrecht, The Netherlands) was evaluated for imaging flow and transport of 99mTc (t1/2=6hrs) using a 46,5mm by 156,4mm column packed with individual layers consisting of <0.2mm diameter silica gel, 0.2-0.25, 0.5, 1.0, 2.0, 3.0, and 4.0mm diameter glass beads, and a natural soil sample obtained from the Savannah River Site. The column was saturated with water prior to injecting the 99mTc solution. During the injection the flow was interrupted intermittently for 10 minute periods to allow for the acquisition of a SPECT image of the transport front. Non-uniformity of the front was clearly observed in the images as well as the retarded movement of 99mTc in the soil layer. The latter is suggesting good potential for monitoring transport processes occurring on the timescale of hours. After breakthrough of 99mTc was achieved, the flow was stopped and SPECT data were collected in one hour increments to evaluate the sensitivity of the instrument as the isotope decayed. Fused SPECT- CT images allowed for improved interpretation of 99mTc distributions within individual pore spaces. With ~3 MBq remaining in the column, the lowest activity imaged, it was not possible to clearly discriminate any of the pore spaces.
Renard, Yohann; Hossu, Gabriela; Chen, Bailiang; Krebs, Marine; Labrousse, Marc; Perez, Manuela
2018-01-01
The objective of this study was to develop a simple and useful injection protocol for imaging cadaveric vascularization and dissection. Mixtures of contrast agent and cast product should provide adequate contrast for two types of ex vivo imaging (MRI and CT) and should harden to allow gross dissection of the injected structures. We tested the most popular contrast agents and cast products, and selected the optimal mixture composition based on their availability and ease of use. All mixtures were first tested in vitro to adjust dilution parameters of each contrast agent and to fine-tune MR imaging acquisition sequences. Mixtures were then injected in 24 pig livers and one human pancreas for MR and computed tomography (CT) imaging before anatomical dissection. Colorized latex, gadobutrol and barite mixture met the above objective. Mixtures composed of copper sulfate (CuSO 4 ) gadoxetic acid (for MRI) and iodine (for CT) gave an inhomogeneous signal or extravasation of the contrast agent. Agar did not harden sufficiently for gross dissection but appears useful for CT and magnetic resonance imaging (MRI) studies without dissection. Silicone was very hard to inject but achieved the goals of the study. Resin is particularly difficult to use but could replace latex as an alternative for corrosion instead of dissection. This injection protocol allows CT and MRI images to be obtained of cadaveric vascularization and anatomical casts in the same anatomic specimen. Post-imaging processing software allow easy 3D reconstruction of complex anatomical structures using this technique. Applications are numerous, e.g. surgical training, teaching methods, postmortem anatomic studies, pathologic studies, and forensic diagnoses. © 2017 Anatomical Society.
Brunner, Stephen; Nett, Brian E; Tolakanahalli, Ranjini; Chen, Guang-Hong
2011-02-21
X-ray scatter is a significant problem in cone-beam computed tomography when thicker objects and larger cone angles are used, as scattered radiation can lead to reduced contrast and CT number inaccuracy. Advances have been made in x-ray computed tomography (CT) by incorporating a high quality prior image into the image reconstruction process. In this paper, we extend this idea to correct scatter-induced shading artifacts in cone-beam CT image-guided radiation therapy. Specifically, this paper presents a new scatter correction algorithm which uses a prior image with low scatter artifacts to reduce shading artifacts in cone-beam CT images acquired under conditions of high scatter. The proposed correction algorithm begins with an empirical hypothesis that the target image can be written as a weighted summation of a series of basis images that are generated by raising the raw cone-beam projection data to different powers, and then, reconstructing using the standard filtered backprojection algorithm. The weight for each basis image is calculated by minimizing the difference between the target image and the prior image. The performance of the scatter correction algorithm is qualitatively and quantitatively evaluated through phantom studies using a Varian 2100 EX System with an on-board imager. Results show that the proposed scatter correction algorithm using a prior image with low scatter artifacts can substantially mitigate scatter-induced shading artifacts in both full-fan and half-fan modes.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Schadewaldt, N; Schulz, H; Helle, M
2014-06-01
Purpose: To analyze the effect of computing radiation dose on automatically generated MR-based simulated CT images compared to true patient CTs. Methods: Six prostate cancer patients received a regular planning CT for RT planning as well as a conventional 3D fast-field dual-echo scan on a Philips 3.0T Achieva, adding approximately 2 min of scan time to the clinical protocol. Simulated CTs (simCT) where synthesized by assigning known average CT values to the tissue classes air, water, fat, cortical and cancellous bone. For this, Dixon reconstruction of the nearly out-of-phase (echo 1) and in-phase images (echo 2) allowed for water andmore » fat classification. Model based bone segmentation was performed on a combination of the DIXON images. A subsequent automatic threshold divides into cortical and cancellous bone. For validation, the simCT was registered to the true CT and clinical treatment plans were re-computed on the simCT in pinnacle{sup 3}. To differentiate effects related to the 5 tissue classes and changes in the patient anatomy not compensated by rigid registration, we also calculate the dose on a stratified CT, where HU values are sorted in to the same 5 tissue classes as the simCT. Results: Dose and volume parameters on PTV and risk organs as used for the clinical approval were compared. All deviations are below 1.1%, except the anal sphincter mean dose, which is at most 2.2%, but well below clinical acceptance threshold. Average deviations are below 0.4% for PTV and risk organs and 1.3% for the anal sphincter. The deviations of the stratifiedCT are in the same range as for the simCT. All plans would have passed clinical acceptance thresholds on the simulated CT images. Conclusion: This study demonstrated the clinical usability of MR based dose calculation with the presented Dixon acquisition and subsequent fully automatic image processing. N. Schadewaldt, H. Schulz, M. Helle and S. Renisch are employed by Phlips Technologie Innovative Techonologies, a subsidiary of Royal Philips NV.« less
Accuracy of UTE-MRI-based patient setup for brain cancer radiation therapy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Yingli; Cao, Minsong; Kaprealian, Tania
2016-01-15
Purpose: Radiation therapy simulations solely based on MRI have advantages compared to CT-based approaches. One feature readily available from computed tomography (CT) that would need to be reproduced with MR is the ability to compute digitally reconstructed radiographs (DRRs) for comparison against on-board radiographs commonly used for patient positioning. In this study, the authors generate MR-based bone images using a single ultrashort echo time (UTE) pulse sequence and quantify their 3D and 2D image registration accuracy to CT and radiographic images for treatments in the cranium. Methods: Seven brain cancer patients were scanned at 1.5 T using a radial UTEmore » sequence. The sequence acquired two images at two different echo times. The two images were processed using an in-house software to generate the UTE bone images. The resultant bone images were rigidly registered to simulation CT data and the registration error was determined using manually annotated landmarks as references. DRRs were created based on UTE-MRI and registered to simulated on-board images (OBIs) and actual clinical 2D oblique images from ExacTrac™. Results: UTE-MRI resulted in well visualized cranial, facial, and vertebral bones that quantitatively matched the bones in the CT images with geometric measurement errors of less than 1 mm. The registration error between DRRs generated from 3D UTE-MRI and the simulated 2D OBIs or the clinical oblique x-ray images was also less than 1 mm for all patients. Conclusions: UTE-MRI-based DRRs appear to be promising for daily patient setup of brain cancer radiotherapy with kV on-board imaging.« less
A biological phantom for evaluation of CT image reconstruction algorithms
NASA Astrophysics Data System (ADS)
Cammin, J.; Fung, G. S. K.; Fishman, E. K.; Siewerdsen, J. H.; Stayman, J. W.; Taguchi, K.
2014-03-01
In recent years, iterative algorithms have become popular in diagnostic CT imaging to reduce noise or radiation dose to the patient. The non-linear nature of these algorithms leads to non-linearities in the imaging chain. However, the methods to assess the performance of CT imaging systems were developed assuming the linear process of filtered backprojection (FBP). Those methods may not be suitable any longer when applied to non-linear systems. In order to evaluate the imaging performance, a phantom is typically scanned and the image quality is measured using various indices. For reasons of practicality, cost, and durability, those phantoms often consist of simple water containers with uniform cylinder inserts. However, these phantoms do not represent the rich structure and patterns of real tissue accurately. As a result, the measured image quality or detectability performance for lesions may not reflect the performance on clinical images. The discrepancy between estimated and real performance may be even larger for iterative methods which sometimes produce "plastic-like", patchy images with homogeneous patterns. Consequently, more realistic phantoms should be used to assess the performance of iterative algorithms. We designed and constructed a biological phantom consisting of porcine organs and tissue that models a human abdomen, including liver lesions. We scanned the phantom on a clinical CT scanner and compared basic image quality indices between filtered backprojection and an iterative reconstruction algorithm.
Generative Adversarial Networks for Noise Reduction in Low-Dose CT.
Wolterink, Jelmer M; Leiner, Tim; Viergever, Max A; Isgum, Ivana
2017-12-01
Noise is inherent to low-dose CT acquisition. We propose to train a convolutional neural network (CNN) jointly with an adversarial CNN to estimate routine-dose CT images from low-dose CT images and hence reduce noise. A generator CNN was trained to transform low-dose CT images into routine-dose CT images using voxelwise loss minimization. An adversarial discriminator CNN was simultaneously trained to distinguish the output of the generator from routine-dose CT images. The performance of this discriminator was used as an adversarial loss for the generator. Experiments were performed using CT images of an anthropomorphic phantom containing calcium inserts, as well as patient non-contrast-enhanced cardiac CT images. The phantom and patients were scanned at 20% and 100% routine clinical dose. Three training strategies were compared: the first used only voxelwise loss, the second combined voxelwise loss and adversarial loss, and the third used only adversarial loss. The results showed that training with only voxelwise loss resulted in the highest peak signal-to-noise ratio with respect to reference routine-dose images. However, CNNs trained with adversarial loss captured image statistics of routine-dose images better. Noise reduction improved quantification of low-density calcified inserts in phantom CT images and allowed coronary calcium scoring in low-dose patient CT images with high noise levels. Testing took less than 10 s per CT volume. CNN-based low-dose CT noise reduction in the image domain is feasible. Training with an adversarial network improves the CNNs ability to generate images with an appearance similar to that of reference routine-dose CT images.
Effect of film-based versus filmless operation on the productivity of CT technologists.
Reiner, B I; Siegel, E L; Hooper, F J; Glasser, D
1998-05-01
To determine the relative time required for a technologist to perform a computed tomographic (CT) examination in a "filmless" versus a film-based environment. Time-motion studies were performed in 204 consecutive CT examinations. Images from 96 examinations were electronically transferred to a picture archiving and communication system (PACS) without being printed to film, and 108 were printed to film. The time required to obtain and electronically transfer the images or print the images to film and make the current and previous studies available to the radiologists for interpretation was recorded. The time required for a technologist to complete a CT examination was reduced by 45% with direct image transfer to the PACS compared with the time required in the film-based mode. This reduction was due to the elimination of a number of steps in the filming process, such as the printing at multiple window or level settings. The use of a PACS can result in the elimination of multiple time-intensive tasks for the CT technologist, resulting in a marked reduction in examination time. This reduction can result in increased productivity, and, hence greater cost-effectiveness with filmless operation.
Boone, John M; Yang, Kai; Burkett, George W; Packard, Nathan J; Huang, Shih-ying; Bowen, Spencer; Badawi, Ramsey D; Lindfors, Karen K
2010-02-01
Mammography has served the population of women who are at-risk for breast cancer well over the past 30 years. While mammography has undergone a number of changes as digital detector technology has advanced, other modalities such as computed tomography have experienced technological sophistication over this same time frame as well. The advent of large field of view flat panel detector systems enable the development of breast CT and several other niche CT applications, which rely on cone beam geometry. The breast, it turns out, is well suited to cone beam CT imaging because the lack of bones reduces artifacts, and the natural tapering of the breast anteriorly reduces the x-ray path lengths through the breast at large cone angle, reducing cone beam artifacts as well. We are in the process of designing a third prototype system which will enable the use of breast CT for image guided interventional procedures. This system will have several copies fabricated so that several breast CT scanners can be used in a multi-institutional clinical trial to better understand the role that this technology can bring to breast imaging.
Computed Tomography Window Blending: Feasibility in Thoracic Trauma.
Mandell, Jacob C; Wortman, Jeremy R; Rocha, Tatiana C; Folio, Les R; Andriole, Katherine P; Khurana, Bharti
2018-02-07
This study aims to demonstrate the feasibility of processing computed tomography (CT) images with a custom window blending algorithm that combines soft-tissue, bone, and lung window settings into a single image; to compare the time for interpretation of chest CT for thoracic trauma with window blending and conventional window settings; and to assess diagnostic performance of both techniques. Adobe Photoshop was scripted to process axial DICOM images from retrospective contrast-enhanced chest CTs performed for trauma with a window-blending algorithm. Two emergency radiologists independently interpreted the axial images from 103 chest CTs with both blended and conventional windows. Interpretation time and diagnostic performance were compared with Wilcoxon signed-rank test and McNemar test, respectively. Agreement with Nexus CT Chest injury severity was assessed with the weighted kappa statistic. A total of 13,295 images were processed without error. Interpretation was faster with window blending, resulting in a 20.3% time saving (P < .001), with no difference in diagnostic performance, within the power of the study to detect a difference in sensitivity of 5% as determined by post hoc power analysis. The sensitivity of the window-blended cases was 82.7%, compared to 81.6% for conventional windows. The specificity of the window-blended cases was 93.1%, compared to 90.5% for conventional windows. All injuries of major clinical significance (per Nexus CT Chest criteria) were correctly identified in all reading sessions, and all negative cases were correctly classified. All readers demonstrated near-perfect agreement with injury severity classification with both window settings. In this pilot study utilizing retrospective data, window blending allows faster preliminary interpretation of axial chest CT performed for trauma, with no significant difference in diagnostic performance compared to conventional window settings. Future studies would be required to assess the utility of window blending in clinical practice. Copyright © 2018 The Association of University Radiologists. All rights reserved.
CT scan range estimation using multiple body parts detection: let PACS learn the CT image content.
Wang, Chunliang; Lundström, Claes
2016-02-01
The aim of this study was to develop an efficient CT scan range estimation method that is based on the analysis of image data itself instead of metadata analysis. This makes it possible to quantitatively compare the scan range of two studies. In our study, 3D stacks are first projected to 2D coronal images via a ray casting-like process. Trained 2D body part classifiers are then used to recognize different body parts in the projected image. The detected candidate regions go into a structure grouping process to eliminate false-positive detections. Finally, the scale and position of the patient relative to the projected figure are estimated based on the detected body parts via a structural voting. The start and end lines of the CT scan are projected to a standard human figure. The position readout is normalized so that the bottom of the feet represents 0.0, and the top of the head is 1.0. Classifiers for 18 body parts were trained using 184 CT scans. The final application was tested on 136 randomly selected heterogeneous CT scans. Ground truth was generated by asking two human observers to mark the start and end positions of each scan on the standard human figure. When compared with the human observers, the mean absolute error of the proposed method is 1.2% (max: 3.5%) and 1.6% (max: 5.4%) for the start and end positions, respectively. We proposed a scan range estimation method using multiple body parts detection and relative structure position analysis. In our preliminary tests, the proposed method delivered promising results.
Allred, Jonathan D; Niedbala, Jeremy; Mikell, Justin K; Owen, Dawn; Frey, Kirk A; Dewaraja, Yuni K
2018-06-15
A major toxicity concern in radioembolization therapy of hepatic malignancies is radiation-induced pneumonitis and sclerosis due to hepatopulmonary shunting of 90 Y microspheres. Currently, 99m Tc macroaggregated albumin ( 99m Tc-MAA) imaging is used to estimate the lung shunt fraction (LSF) prior to treatment. The aim of this study was to evaluate the accuracy/precision of LSF estimated from 99m Tc planar and SPECT/CT phantom imaging, and within this context, to compare the corresponding LSF and lung-absorbed dose values from 99m Tc-MAA patient studies. Additionally, LSFs from pre- and post-therapy imaging were compared. A liver/lung torso phantom filled with 99m Tc to achieve three lung shunt values was scanned by planar and SPECT/CT imaging with repeat acquisitions to assess accuracy and precision. To facilitate processing of patient data, a workflow that relies on SPECT and CT-based auto-contouring to define liver and lung volumes for the LSF calculation was implemented. Planar imaging-based LSF estimates for 40 patients, obtained from their medical records, were retrospectively compared with SPECT/CT imaging-based calculations with attenuation and scatter correction. Additionally, in a subset of 20 patients, the pre-therapy estimates were compared with 90 Y PET/CT-based measurements. In the phantom study, improved accuracy in LSF estimation was achieved using SPECT/CT with attenuation and scatter correction (within 13% of the true value) compared with planar imaging (up to 44% overestimation). The results in patients showed a similar trend with planar imaging significantly overestimating LSF compared to SPECT/CT. There was no correlation between lung shunt estimates and the delay between 99m Tc-MAA administration and scanning, but off-target extra hepatic uptake tended to be more likely in patients with a longer delay. The mean lung absorbed dose predictions for the 28 patients who underwent therapy was 9.3 Gy (range 1.3-29.4) for planar imaging and 3.2 Gy (range 0.4-13.4) for SPECT/CT. For the patients with post-therapy imaging, the mean LSF from 90 Y PET/CT was 1.0%, (range 0.3-2.8). This value was not significantly different from the mean LSF estimate from 99m Tc-MAA SPECT/CT (mean 1.0%, range 0.4-1.6; p = 0.968), but was significantly lower than the mean LSF estimate based on planar imaging (mean 4.1%, range 1.2-15.0; p = 0.0002). The improved accuracy demonstrated by the phantom study, agreement with 90 Y PET/CT in patient studies, and the practicality of using auto-contouring for liver/lung definition suggests that 99m Tc-MAA SPECT/CT with scatter and attenuation corrections should be used for lung shunt estimation prior to radioembolization.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Han, H; Xing, L; Liang, Z
Purpose: To investigate a novel low-dose CT (LdCT) image reconstruction strategy for lung CT imaging in radiation therapy. Methods: The proposed approach consists of four steps: (1) use the traditional filtered back-projection (FBP) method to reconstruct the LdCT image; (2) calculate structure similarity (SSIM) index between the FBP-reconstructed LdCT image and a set of normal-dose CT (NdCT) images, and select the NdCT image with the highest SSIM as the learning source; (3) segment the NdCT source image into lung and outside tissue regions via simple thresholding, and adopt multiple linear regression to learn high-order Markov random field (MRF) pattern formore » each tissue region in the NdCT source image; (4) segment the FBP-reconstructed LdCT image into lung and outside regions as well, and apply the learnt MRF prior in each tissue region for statistical iterative reconstruction of the LdCT image following the penalized weighted least squares (PWLS) framework. Quantitative evaluation of the reconstructed images was based on the signal-to-noise ratio (SNR), local binary pattern (LBP) and histogram of oriented gradients (HOG) metrics. Results: It was observed that lung and outside tissue regions have different MRF patterns predicted from the NdCT. Visual inspection showed that our method obviously outperformed the traditional FBP method. Comparing with the region-smoothing PWLS method, our method has, in average, 13% increase in SNR, 15% decrease in LBP difference, and 12% decrease in HOG difference from reference standard for all regions of interest, which indicated the superior performance of the proposed method in terms of image resolution and texture preservation. Conclusion: We proposed a novel LdCT image reconstruction method by learning similar image characteristics from a set of NdCT images, and the to-be-learnt NdCT image does not need to be scans from the same subject. This approach is particularly important for enhancing image quality in radiation therapy.« less
Examination of the dental cone-beam CT equipped with flat-panel-detector (FPD)
NASA Astrophysics Data System (ADS)
Ito, Rieko; Fujita, Naotoshi; Kodera, Yoshie
2011-03-01
In dentistry, computed tomography (CT) is essential for diagnosis. Recently, cone-beam CT has come into use. We used an "Alphard 3030" cone-beam CT equipped with an FPD system. This system can obtain fluoroscopic and CT images. Moreover, the Alphard has 4 exposure modes for CT, and each mode has a different field of view (FOV) and voxel size. We examined the image quality of kinetic and CT images obtained using the cone-beam CT system. To evaluate kinetic image quality, we calculated the Wiener spectrum (WS) and modulation transfer function (MTF). We then analyzed the lag images and exposed a phantom. To evaluate CT image quality, we calculated WS and MTF at various places in the FOV and examined the influence of extension of the cone beam X-ray on voxel size. Furthermore, we compared the WS and MTF values of cone-beam CT to those of another CT system. Evaluation of the kinetic images showed that cone-beam CT is sufficient for clinical diagnosis and provides better image quality than the other system tested. However, during exposure of a CT image, the distance from the center influences image quality (especially MTF). Further, differences in voxel size affect image quality. It is therefore necessary to carefully position the region of interest and select an appropriate mode.
TU-G-201-02: An MRI Simulator From Proposal to Operation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cao, Y.
2015-06-15
This session will update therapeutic physicists on technological advancements and radiation oncology features of commercial CT, MRI, and PET/CT imaging systems. Also described are physicists’ roles in every stage of equipment selection, purchasing, and operation, including defining specifications, evaluating vendors, making recommendations, and optimal and safe use of imaging equipment in radiation oncology environment. The first presentation defines important terminology of CT and PET/CT followed by a review of latest innovations, such as metal artifact reduction, statistical iterative reconstruction, radiation dose management, tissue classification by dual energy CT and spectral CT, improvement in spatial resolution and sensitivity in PET, andmore » potentials of PET/MR. We will also discuss important technical specifications and items in CT and PET/CT purchasing quotes and their impacts. The second presentation will focus on key components in the request for proposal for a MRI simulator and how to evaluate vendor proposals. MRI safety issues in radiation Oncology, including MRI scanner Zones (4-zone design), will be discussed. Basic MR terminologies, important functionalities, and advanced features, which are relevant to radiation therapy, will be discussed. In the third presentation, justification of imaging systems for radiation oncology, considerations in room design and construction in a RO department, shared use with diagnostic radiology, staffing needs and training, clinical/research use cases and implementation, will be discussed. The emphasis will be on understanding and bridging the differences between diagnostic and radiation oncology installations, building consensus amongst stakeholders for purchase and use, and integrating imaging technologies into the radiation oncology environment. Learning Objectives: Learn the latest innovations of major imaging systems relevant to radiation therapy Be able to describe important technical specifications of CT, MRI, and PET/CT Understand the process of budget request, equipment justification, comparisons of technical specifications, site visits, vendor selection, and contract development.« less
Strauss, Keith J
2014-10-01
The management of image quality and radiation dose during pediatric CT scanning is dependent on how well one manages the radiographic techniques as a function of the type of exam, type of CT scanner, and patient size. The CT scanner's display of expected CT dose index volume (CTDIvol) after the projection scan provides the operator with a powerful tool prior to the patient scan to identify and manage appropriate CT techniques, provided the department has established appropriate diagnostic reference levels (DRLs). This paper provides a step-by-step process that allows the development of DRLs as a function of type of exam, of actual patient size and of the individual radiation output of each CT scanner in a department. Abdomen, pelvis, thorax and head scans are addressed. Patient sizes from newborns to large adults are discussed. The method addresses every CT scanner regardless of vendor, model or vintage. We cover adjustments to techniques to manage the impact of iterative reconstruction and provide a method to handle all available voltages other than 120 kV. This level of management of CT techniques is necessary to properly monitor radiation dose and image quality during pediatric CT scans.
Three-dimensional contrasted visualization of pancreas in rats using clinical MRI and CT scanners.
Yin, Ting; Coudyzer, Walter; Peeters, Ronald; Liu, Yewei; Cona, Marlein Miranda; Feng, Yuanbo; Xia, Qian; Yu, Jie; Jiang, Yansheng; Dymarkowski, Steven; Huang, Gang; Chen, Feng; Oyen, Raymond; Ni, Yicheng
2015-01-01
The purpose of this work was to visualize the pancreas in post-mortem rats with local contrast medium infusion by three-dimensional (3D) magnetic resonance imaging (MRI) and computed tomography (CT) using clinical imagers. A total of 16 Sprague Dawley rats of about 300 g were used for the pancreas visualization. Following the baseline imaging, a mixed contrast medium dye called GadoIodo-EB containing optimized concentrations of Gd-DOTA, iomeprol and Evens blue was infused into the distally obstructed common bile duct (CBD) for post-contrast imaging with 3.0 T MRI and 128-slice CT scanners. Images were post-processed with the MeVisLab software package. MRI findings were co-registered with CT scans and validated with histomorphology, with relative contrast ratios quantified. Without contrast enhancement, the pancreas was indiscernible. After infusion of GadoIodo-EB solution, only the pancreatic region became outstandingly visible, as shown by 3D rendering MRI and CT and proven by colored dissection and histological examinations. The measured volume of the pancreas averaged 1.12 ± 0.04 cm(3) after standardization. Relative contrast ratios were 93.28 ± 34.61% and 26.45 ± 5.29% for MRI and CT respectively. We have developed a multifunctional contrast medium dye to help clearly visualize and delineate rat pancreas in situ using clinical MRI and CT scanners. The topographic landmarks thus created with 3D demonstration may help to provide guidelines for the next in vivo pancreatic MRI research in rodents. Copyright © 2015 John Wiley & Sons, Ltd.
Molecular Imaging of Influenza and Other Emerging Respiratory Viral Infections
Lawler, James; Paragas, Jason; Jahrling, Peter B.; Mollura, Daniel J.
2011-01-01
Research on the pathogenesis and therapy of influenza and other emerging respiratory viral infections would be aided by methods that directly visualize pathophysiologic processes in patients and laboratory animals. At present, imaging of diseases, such as swine-origin H1N1 influenza, is largely restricted to chest radiograph and computed tomography (CT), which can detect pulmonary structural changes in severely ill patients but are more limited in characterizing the early stages of illness, differentiating inflammation from infection or tracking immune responses. In contrast, imaging modalities, such as positron emission tomography, single photon emission CT, magnetic resonance imaging, and bioluminescence imaging, which have become useful tools for investigating the pathogenesis of a range of disease processes, could be used to advance in vivo studies of respiratory viral infections in patients and animals. Molecular techniques might also be used to identify novel biomarkers of disease progression and to evaluate new therapies. PMID:21422476
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zheng, Weili; Kim, Joshua P.; Kadbi, Mo
2015-11-01
Purpose: To incorporate a novel imaging sequence for robust air and tissue segmentation using ultrashort echo time (UTE) phase images and to implement an innovative synthetic CT (synCT) solution as a first step toward MR-only radiation therapy treatment planning for brain cancer. Methods and Materials: Ten brain cancer patients were scanned with a UTE/Dixon sequence and other clinical sequences on a 1.0 T open magnet with simulation capabilities. Bone-enhanced images were generated from a weighted combination of water/fat maps derived from Dixon images and inverted UTE images. Automated air segmentation was performed using unwrapped UTE phase maps. Segmentation accuracy was assessedmore » by calculating segmentation errors (true-positive rate, false-positive rate, and Dice similarity indices using CT simulation (CT-SIM) as ground truth. The synCTs were generated using a voxel-based, weighted summation method incorporating T2, fluid attenuated inversion recovery (FLAIR), UTE1, and bone-enhanced images. Mean absolute error (MAE) characterized Hounsfield unit (HU) differences between synCT and CT-SIM. A dosimetry study was conducted, and differences were quantified using γ-analysis and dose-volume histogram analysis. Results: On average, true-positive rate and false-positive rate for the CT and MR-derived air masks were 80.8% ± 5.5% and 25.7% ± 6.9%, respectively. Dice similarity indices values were 0.78 ± 0.04 (range, 0.70-0.83). Full field of view MAE between synCT and CT-SIM was 147.5 ± 8.3 HU (range, 138.3-166.2 HU), with the largest errors occurring at bone–air interfaces (MAE 422.5 ± 33.4 HU for bone and 294.53 ± 90.56 HU for air). Gamma analysis revealed pass rates of 99.4% ± 0.04%, with acceptable treatment plan quality for the cohort. Conclusions: A hybrid MRI phase/magnitude UTE image processing technique was introduced that significantly improved bone and air contrast in MRI. Segmented air masks and bone-enhanced images were integrated into our synCT pipeline for brain, and results agreed well with clinical CTs, thereby supporting MR-only radiation therapy treatment planning in the brain.« less
Zheng, Weili; Kim, Joshua P; Kadbi, Mo; Movsas, Benjamin; Chetty, Indrin J; Glide-Hurst, Carri K
2015-11-01
To incorporate a novel imaging sequence for robust air and tissue segmentation using ultrashort echo time (UTE) phase images and to implement an innovative synthetic CT (synCT) solution as a first step toward MR-only radiation therapy treatment planning for brain cancer. Ten brain cancer patients were scanned with a UTE/Dixon sequence and other clinical sequences on a 1.0 T open magnet with simulation capabilities. Bone-enhanced images were generated from a weighted combination of water/fat maps derived from Dixon images and inverted UTE images. Automated air segmentation was performed using unwrapped UTE phase maps. Segmentation accuracy was assessed by calculating segmentation errors (true-positive rate, false-positive rate, and Dice similarity indices using CT simulation (CT-SIM) as ground truth. The synCTs were generated using a voxel-based, weighted summation method incorporating T2, fluid attenuated inversion recovery (FLAIR), UTE1, and bone-enhanced images. Mean absolute error (MAE) characterized Hounsfield unit (HU) differences between synCT and CT-SIM. A dosimetry study was conducted, and differences were quantified using γ-analysis and dose-volume histogram analysis. On average, true-positive rate and false-positive rate for the CT and MR-derived air masks were 80.8% ± 5.5% and 25.7% ± 6.9%, respectively. Dice similarity indices values were 0.78 ± 0.04 (range, 0.70-0.83). Full field of view MAE between synCT and CT-SIM was 147.5 ± 8.3 HU (range, 138.3-166.2 HU), with the largest errors occurring at bone-air interfaces (MAE 422.5 ± 33.4 HU for bone and 294.53 ± 90.56 HU for air). Gamma analysis revealed pass rates of 99.4% ± 0.04%, with acceptable treatment plan quality for the cohort. A hybrid MRI phase/magnitude UTE image processing technique was introduced that significantly improved bone and air contrast in MRI. Segmented air masks and bone-enhanced images were integrated into our synCT pipeline for brain, and results agreed well with clinical CTs, thereby supporting MR-only radiation therapy treatment planning in the brain. Copyright © 2015 Elsevier Inc. All rights reserved.
Automatic bladder segmentation from CT images using deep CNN and 3D fully connected CRF-RNN.
Xu, Xuanang; Zhou, Fugen; Liu, Bo
2018-03-19
Automatic approach for bladder segmentation from computed tomography (CT) images is highly desirable in clinical practice. It is a challenging task since the bladder usually suffers large variations of appearance and low soft-tissue contrast in CT images. In this study, we present a deep learning-based approach which involves a convolutional neural network (CNN) and a 3D fully connected conditional random fields recurrent neural network (CRF-RNN) to perform accurate bladder segmentation. We also propose a novel preprocessing method, called dual-channel preprocessing, to further advance the segmentation performance of our approach. The presented approach works as following: first, we apply our proposed preprocessing method on the input CT image and obtain a dual-channel image which consists of the CT image and an enhanced bladder density map. Second, we exploit a CNN to predict a coarse voxel-wise bladder score map on this dual-channel image. Finally, a 3D fully connected CRF-RNN refines the coarse bladder score map and produce final fine-localized segmentation result. We compare our approach to the state-of-the-art V-net on a clinical dataset. Results show that our approach achieves superior segmentation accuracy, outperforming the V-net by a significant margin. The Dice Similarity Coefficient of our approach (92.24%) is 8.12% higher than that of the V-net. Moreover, the bladder probability maps performed by our approach present sharper boundaries and more accurate localizations compared with that of the V-net. Our approach achieves higher segmentation accuracy than the state-of-the-art method on clinical data. Both the dual-channel processing and the 3D fully connected CRF-RNN contribute to this improvement. The united deep network composed of the CNN and 3D CRF-RNN also outperforms a system where the CRF model acts as a post-processing method disconnected from the CNN.
Image fusion pitfalls for cranial radiosurgery
Jonker, Benjamin P.
2013-01-01
Stereotactic radiosurgery requires imaging to define both the stereotactic space in which the treatment is delivered and the target itself. Image fusion is the process of using rotation and translation to bring a second image set into alignment with the first image set. This allows the potential concurrent use of multiple image sets to define the target and stereotactic space. While a single magnetic resonance imaging (MRI) sequence alone can be used for delineation of the target and fiducials, there may be significant advantages to using additional imaging sets including other MRI sequences, computed tomography (CT) scans, and advanced imaging sets such as catheter-based angiography, diffusor tension imaging-based fiber tracking and positon emission tomography in order to more accurately define the target and surrounding critical structures. Stereotactic space is usually defined by detection of fiducials on the stereotactic head frame or mask system. Unfortunately MRI sequences are susceptible to geometric distortion, whereas CT scans do not face this problem (although they have poorer resolution of the target in most cases). Thus image fusion can allow the definition of stereotactic space to proceed from the geometrically accurate CT images at the same time as using MRI to define the target. The use of image fusion is associated with risk of error introduced by inaccuracies of the fusion process, as well as workflow changes that if not properly accounted for can mislead the treating clinician. The purpose of this review is to describe the uses of image fusion in stereotactic radiosurgery as well as its potential pitfalls. PMID:23682338
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hirose, K; Takai, Y; Southern Tohoku BNCT Research Center, Koriyama
2016-06-15
Purpose: The purpose of this study was to prospectively assess the reproducibility of positioning errors due to temporarily indwelled catheter in urethra-sparing image-guided (IG) IMRT. Methods: Ten patients received urethra-sparing prostate IG-IMRT with implanted fiducials. After the first CT scan was performed in supine position, 6-Fr catheter was indwelled into urethra, and the second CT images were taken for planning. While the PTV received 80 Gy, 5% dose reduction was applied for the urethral PRV along the catheter. Additional CT scans were also performed at 5th and 30th fraction. Positions of interests (POIs) were set on posterior edge of prostatemore » at beam isocenter level (POI1) and cranial and caudal edge of prostatic urethra on the post-indwelled CT images. POIs were copied into the pre-indwelled, 5th and 30th fraction’s CT images after fiducial matching on these CT images. The deviation of each POI between pre- and post-indwelled CT and the reproducibility of prostate displacement due to catheter were evaluated. Results: The deviation of POI1 caused by the indwelled catheter to the directions of RL/AP/SI (mm) was 0.20±0.27/−0.64±2.43/1.02±2.31, respectively, and the absolute distances (mm) were 3.15±1.41. The deviation tends to be larger if closer to the caudal edge of prostate. Compared with the pre-indwelled CT scan, a median displacement of all POIs (mm) were 0.3±0.2/2.2±1.1/2.0±2.6 in the post-indwelled, 0.4±0.4/3.4±2.1/2.3±2.6 in 5th, and 0.5±0.5/1.7±2.2/1.9±3.1 in 30th fraction’s CT scan with a similar data distribution. There were 6 patients with 5-mm-over displacement in AP and/or CC directions. Conclusion: Reproducibility of positioning errors due to temporarily indwelling catheter was observed. Especially in case of patients with unusually large shifts by indwelling catheter at the planning process, treatment planning should be performed by using the pre-indwelled CT images with transferred contour of the urethra identified by post-indwelled CT images.« less
Peripleural lung disease detection based on multi-slice CT images
NASA Astrophysics Data System (ADS)
Matsuhiro, M.; Suzuki, H.; Kawata, Y.; Niki, N.; Nakano, Y.; Ohmatsu, H.; Kusumoto, M.; Tsuchida, T.; Eguchi, K.; Kaneko, M.
2015-03-01
With the development of multi-slice CT technology, obtaining accurate 3D images of lung field in a short time become possible. To support that, a lot of image processing methods need to be developed. Detection peripleural lung disease is difficult due to its existence out of lung region, because lung extraction is often performed based on threshold processing. The proposed method uses thoracic inner region extracted by inner cavity of bone as well as air region, covers peripleural lung diseased cases such as lung nodule, calcification, pleural effusion and pleural plaque. We applied this method to 50 cases including 39 peripleural lung diseased cases. This method was able to detect 39 peripleural lung disease with 2.9 false positive per case.
Santos, Jonathan; Chaudhari, Abhijit J; Joshi, Anand A; Ferrero, Andrea; Yang, Kai; Boone, John M; Badawi, Ramsey D
2014-09-01
Dedicated breast CT and PET/CT scanners provide detailed 3D anatomical and functional imaging data sets and are currently being investigated for applications in breast cancer management such as diagnosis, monitoring response to therapy and radiation therapy planning. Our objective was to evaluate the performance of the diffeomorphic demons (DD) non-rigid image registration method to spatially align 3D serial (pre- and post-contrast) dedicated breast computed tomography (CT), and longitudinally-acquired dedicated 3D breast CT and positron emission tomography (PET)/CT images. The algorithmic parameters of the DD method were optimized for the alignment of dedicated breast CT images using training data and fixed. The performance of the method for image alignment was quantitatively evaluated using three separate data sets; (1) serial breast CT pre- and post-contrast images of 20 women, (2) breast CT images of 20 women acquired before and after repositioning the subject on the scanner, and (3) dedicated breast PET/CT images of 7 women undergoing neo-adjuvant chemotherapy acquired pre-treatment and after 1 cycle of therapy. The DD registration method outperformed no registration (p < 0.001) and conventional affine registration (p ≤ 0.002) for serial and longitudinal breast CT and PET/CT image alignment. In spite of the large size of the imaging data, the computational cost of the DD method was found to be reasonable (3-5 min). Co-registration of dedicated breast CT and PET/CT images can be performed rapidly and reliably using the DD method. This is the first study evaluating the DD registration method for the alignment of dedicated breast CT and PET/CT images. Copyright © 2014 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.
A comparison of hepatic segmental anatomy as revealed by cross-sections and MPR CT imaging.
Liu, Xue-Jing; Zhang, Jian-Fei; Sui, Hong-Jin; Yu, Sheng-Bo; Gong, Jin; Liu, Jie; Wu, Le-Bin; Liu, Cheng; Bai, Jian; Shi, Bing-Yi
2013-05-01
To compare the areas of human liver horizontal sections with computed tomography (CT) images and to evaluate whether the subsegments determined by CT are consistent with the actual anatomy. Six human cadaver livers were made into horizontal slices with multislice spiral CT three-dimensional (3D) reconstruction was used during infusion process. Each liver segment was displayed using different color, and 3D images of the portal and hepatic vein were reconstructed. Each segmental area was measured on CT-reconstructed images, which were compared with the actual area on the sections of the same liver. The measurements were performed at four key levels namely: (1) the three hepatic veins, (2) the left, and (3) the right branch of portal vein (PV), and (4) caudal to the bifurcation of the PV. By dividing the sum of these areas by the total area of the liver, the authors got the percentage of the incorrectly determined subsegmental areas. In addition to these percentage values, the maximum distances of the radiologically determined intersegmental boundaries from the true anatomic boundaries were measured. On the four key levels, an average of 28.64 ± 10.26% of the hepatic area of CT images was attributed to an incorrect segment. The mean-maximum error between artificial segments on images and actual anatomical segments was 3.81 ± 1.37 cm. The correlation between radiological segmenting method and actual anatomy was poor. The hepatic segments being divided strictly according to the branching point of the PV could be more informative during liver segmental resection. Copyright © 2012 Wiley Periodicals, Inc.
Cochlear anatomy using micro computed tomography (μCT) imaging
NASA Astrophysics Data System (ADS)
Kim, Namkeun; Yoon, Yongjin; Steele, Charles; Puria, Sunil
2008-02-01
A novel micro computed tomography (μCT) image processing method was implemented to measure anatomical features of the gerbil and chinchilla cochleas, taking into account the bent modailosis axis. Measurements were made of the scala vestibule (SV) area, the scala tympani (SV) area, and the basilar membrane (BM) width using prepared cadaveric temporal bones. 3-D cochlear structures were obtained from the scanned images using a process described in this study. It was necessary to consider the sharp curvature of mododailosis axis near the basal region. The SV and ST areas were calculated from the μCT reconstructions and compared with existing data obtained by Magnetic Resonance Microscopy (MRM), showing both qualitative and quantitative agreement. In addition to this, the width of the BM, which is the distance between the primary and secondary osseous spiral laminae, is calculated for the two animals and compared with previous data from the MRM method. For the gerbil cochlea, which does not have much cartilage in the osseous spiral lamina, the μCT-based BM width measurements show good agreement with previous data. The chinchilla BM, which contains more cartilage in the osseous spiral lamina than the gerbil, shows a large difference in the BM widths between the μCT and MRM methods. The SV area, ST area, and BM width measurements from this study can be used in building an anatomically based mathematical cochlear model.
Morimoto, Linda Nayeli; Kamaya, Aya; Boulay-Coletta, Isabelle; Fleischmann, Dominik; Molvin, Lior; Tian, Lu; Fisher, George; Wang, Jia; Willmann, Jürgen K
2017-09-01
To compare image quality and lesion conspicuity of reduced dose (RD) CT with model-based iterative reconstruction (MBIR) compared to standard dose (SD) CT in patients undergoing oncological follow-up imaging. Forty-four cancer patients who had a staging SD CT within 12 months were prospectively included to undergo a weight-based RD CT with MBIR. Radiation dose was recorded and tissue attenuation and image noise of four tissue types were measured. Reproducibility of target lesion size measurements of up to 5 target lesions per patient were analyzed. Subjective image quality was evaluated for three readers independently utilizing 4- or 5-point Likert scales. Median radiation dose reduction was 46% using RD CT (P < 0.01). Median image noise across all measured tissue types was lower (P < 0.01) in RD CT. Subjective image quality for RD CT was higher (P < 0.01) in regard to image noise and overall image quality; however, there was no statistically significant difference regarding image sharpness (P = 0.59). There were subjectively more artifacts on RD CT (P < 0.01). Lesion conspicuity was subjectively better in RD CT (P < 0.01). Repeated target lesion size measurements were highly reproducible both on SD CT (ICC = 0.987) and RD CT (ICC = 0.97). RD CT imaging with MBIR provides diagnostic imaging quality and comparable lesion conspicuity on follow-up exams while allowing dose reduction by a median of 46% compared to SD CT imaging.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Bin; Lyu, Qingwen; Ma, Jianhua
2016-04-15
Purpose: In computed tomography perfusion (CTP) imaging, an initial phase CT acquired with a high-dose protocol can be used to improve the image quality of later phase CT acquired with a low-dose protocol. For dynamic regions, signals in the later low-dose CT may not be completely recovered if the initial CT heavily regularizes the iterative reconstruction process. The authors propose a hybrid nonlocal means (hNLM) regularization model for iterative reconstruction of low-dose CTP to overcome the limitation of the conventional prior-image induced penalty. Methods: The hybrid penalty was constructed by combining the NLM of the initial phase high-dose CT inmore » the stationary region and later phase low-dose CT in the dynamic region. The stationary and dynamic regions were determined by the similarity between the initial high-dose scan and later low-dose scan. The similarity was defined as a Gaussian kernel-based distance between the patch-window of the same pixel in the two scans, and its measurement was then used to weigh the influence of the initial high-dose CT. For regions with high similarity (e.g., stationary region), initial high-dose CT played a dominant role for regularizing the solution. For regions with low similarity (e.g., dynamic region), the regularization relied on a low-dose scan itself. This new hNLM penalty was incorporated into the penalized weighted least-squares (PWLS) for CTP reconstruction. Digital and physical phantom studies were performed to evaluate the PWLS-hNLM algorithm. Results: Both phantom studies showed that the PWLS-hNLM algorithm is superior to the conventional prior-image induced penalty term without considering the signal changes within the dynamic region. In the dynamic region of the Catphan phantom, the reconstruction error measured by root mean square error was reduced by 42.9% in PWLS-hNLM reconstructed image. Conclusions: The PWLS-hNLM algorithm can effectively use the initial high-dose CT to reconstruct low-dose CTP in the stationary region while reducing its influence in the dynamic region.« less
Attenuation correction of emission PET images with average CT: Interpolation from breath-hold CT
NASA Astrophysics Data System (ADS)
Huang, Tzung-Chi; Zhang, Geoffrey; Chen, Chih-Hao; Yang, Bang-Hung; Wu, Nien-Yun; Wang, Shyh-Jen; Wu, Tung-Hsin
2011-05-01
Misregistration resulting from the difference of temporal resolution in PET and CT scans occur frequently in PET/CT imaging, which causes distortion in tumor quantification in PET. Respiration cine average CT (CACT) for PET attenuation correction has been reported to improve the misalignment effectively by several papers. However, the radiation dose to the patient from a four-dimensional CT scan is relatively high. In this study, we propose a method to interpolate respiratory CT images over a respiratory cycle from inhalation and exhalation breath-hold CT images, and use the average CT from the generated CT set for PET attenuation correction. The radiation dose to the patient is reduced using this method. Six cancer patients of various lesion sites underwent routine free-breath helical CT (HCT), respiration CACT, interpolated average CT (IACT), and 18F-FDG PET. Deformable image registration was used to interpolate the middle phases of a respiratory cycle based on the end-inspiration and end-expiration breath-hold CT scans. The average CT image was calculated from the eight interpolated CT image sets of middle respiratory phases and the two original inspiration and expiration CT images. Then the PET images were reconstructed by these three methods for attenuation correction using HCT, CACT, and IACT. Misalignment of PET image using either CACT or IACT for attenuation correction in PET/CT was improved. The difference in standard uptake value (SUV) from tumor in PET images was most significant between the use of HCT and CACT, while the least significant between the use of CACT and IACT. Besides the similar improvement in tumor quantification compared to the use of CACT, using IACT for PET attenuation correction reduces the radiation dose to the patient.
Tixier, Florent; Groves, Ashley M; Goh, Vicky; Hatt, Mathieu; Ingrand, Pierre; Le Rest, Catherine Cheze; Visvikis, Dimitris
2014-01-01
Thirty patients with proven colorectal cancer prospectively underwent integrated 18F-FDG PET/DCE-CT to assess the metabolic-flow phenotype. Both CT blood flow parametric maps and PET images were analyzed. Correlations between PET heterogeneity and perfusion CT were assessed by Spearman's rank correlation analysis. Blood flow visualization provided by DCE-CT images was significantly correlated with 18F-FDG PET metabolically active tumor volume as well as with uptake heterogeneity for patients with stage III/IV tumors (|ρ|:0.66 to 0.78; p-value<0.02). The positive correlation found with tumor blood flow indicates that intra-tumor heterogeneity of 18F-FDG PET accumulation reflects to some extent tracer distribution and consequently indicates that 18F-FDG PET intra-tumor heterogeneity may be associated with physiological processes such as tumor vascularization.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen Ting; Kim, Sung; Goyal, Sharad
2010-01-15
Purpose: High-speed nonrigid registration between the planning CT and the treatment CBCT data is critical for real time image guided radiotherapy (IGRT) to improve the dose distribution and to reduce the toxicity to adjacent organs. The authors propose a new fully automatic 3D registration framework that integrates object-based global and seed constraints with the grayscale-based ''demons'' algorithm. Methods: Clinical objects were segmented on the planning CT images and were utilized as meshless deformable models during the nonrigid registration process. The meshless models reinforced a global constraint in addition to the grayscale difference between CT and CBCT in order to maintainmore » the shape and the volume of geometrically complex 3D objects during the registration. To expedite the registration process, the framework was stratified into hierarchies, and the authors used a frequency domain formulation to diffuse the displacement between the reference and the target in each hierarchy. Also during the registration of pelvis images, they replaced the air region inside the rectum with estimated pixel values from the surrounding rectal wall and introduced an additional seed constraint to robustly track and match the seeds implanted into the prostate. The proposed registration framework and algorithm were evaluated on 15 real prostate cancer patients. For each patient, prostate gland, seminal vesicle, bladder, and rectum were first segmented by a radiation oncologist on planning CT images for radiotherapy planning purpose. The same radiation oncologist also manually delineated the tumor volumes and critical anatomical structures in the corresponding CBCT images acquired at treatment. These delineated structures on the CBCT were only used as the ground truth for the quantitative validation, while structures on the planning CT were used both as the input to the registration method and the ground truth in validation. By registering the planning CT to the CBCT, a displacement map was generated. Segmented volumes in the CT images deformed using the displacement field were compared against the manual segmentations in the CBCT images to quantitatively measure the convergence of the shape and the volume. Other image features were also used to evaluate the overall performance of the registration. Results: The algorithm was able to complete the segmentation and registration process within 1 min, and the superimposed clinical objects achieved a volumetric similarity measure of over 90% between the reference and the registered data. Validation results also showed that the proposed registration could accurately trace the deformation inside the target volume with average errors of less than 1 mm. The method had a solid performance in registering the simulated images with up to 20 Hounsfield unit white noise added. Also, the side by side comparison with the original demons algorithm demonstrated its improved registration performance over the local pixel-based registration approaches. Conclusions: Given the strength and efficiency of the algorithm, the proposed method has significant clinical potential to accelerate and to improve the CBCT delineation and targets tracking in online IGRT applications.« less
Kim, Bum-Joon; Hong, Ki-Sun; Park, Kyung-Jae; Park, Dong-Hyuk; Chung, Yong-Gu; Kang, Shin-Hyuk
2012-12-01
The prefabrication of customized cranioplastic implants has been introduced to overcome the difficulties of intra-operative implant molding. The authors present a new technique, which consists of the prefabrication of implant molds using three-dimensional (3D) printers and polymethyl-methacrylate (PMMA) casting. A total of 16 patients with large skull defects (>100 cm(2)) underwent cranioplasty between November 2009 and April 2011. For unilateral cranial defects, 3D images of the skull were obtained from preoperative axial 1-mm spiral computed tomography (CT) scans. The image of the implant was generated by a digital subtraction mirror-imaging process using the normal side of the cranium as a model. For bilateral cranial defects, precraniectomy routine spiral CT scan data were merged with postcraniectomy 3D CT images following a smoothing process. Prefabrication of the mold was performed by the 3D printer. Intraoperatively, the PMMA implant was created with the prefabricated mold, and fit into the cranial defect. The median operation time was 184.36±26.07 minutes. Postoperative CT scans showed excellent restoration of the symmetrical contours and curvature of the cranium in all cases. The median follow-up period was 23 months (range, 14-28 months). Postoperative infection was developed in one case (6.2%) who had an open wound defect previously. Customized cranioplasty PMMA implants using 3D printer may be a useful technique for the reconstruction of various cranial defects.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Q; Yan, D
2014-06-01
Purpose: Evaluate the accuracy of atlas-based auto segmentation of organs at risk (OARs) on both helical CT (HCT) and cone beam CT (CBCT) images in head and neck (HN) cancer adaptive radiotherapy (ART). Methods: Six HN patients treated in the ART process were included in this study. For each patient, three images were selected: pretreatment planning CT (PreTx-HCT), in treatment CT for replanning (InTx-HCT) and a CBCT acquired in the same day of the InTx-HCT. Three clinical procedures of auto segmentation and deformable registration performed in the ART process were evaluated: a) auto segmentation on PreTx-HCT using multi-subject atlases, b)more » intra-patient propagation of OARs from PreTx-HCT to InTx-HCT using deformable HCT-to-HCT image registration, and c) intra-patient propagation of OARs from PreTx-HCT to CBCT using deformable CBCT-to-HCT image registration. Seven OARs (brainstem, cord, L/R parotid, L/R submandibular gland and mandible) were manually contoured on PreTx-HCT and InTx-HCT for comparison. In addition, manual contours on InTx-CT were copied on the same day CBCT, and a local region rigid body registration was performed accordingly for each individual OAR. For procedures a) and b), auto contours were compared to manual contours, and for c) auto contours were compared to those rigidly transferred contours on CBCT. Dice similarity coefficients (DSC) and mean surface distances of agreement (MSDA) were calculated for evaluation. Results: For procedure a), the mean DSC/MSDA of most OARs are >80%/±2mm. For intra-patient HCT-to-HCT propagation, the Resultimproved to >85%/±1.5mm. Compared to HCT-to-HCT, the mean DSC for HCT-to-CBCT propagation drops ∼2–3% and MSDA increases ∼0.2mm. This Resultindicates that the inferior imaging quality of CBCT seems only degrade auto propagation performance slightly. Conclusion: Auto segmentation and deformable propagation can generate OAR structures on HCT and CBCT images with clinically acceptable accuracy. Therefore, they can be reliably implemented in the clinical HN ART process.« less
Athanasiou, Lambros S; Rigas, George A; Sakellarios, Antonis I; Exarchos, Themis P; Siogkas, Panagiotis K; Naka, Katerina K; Panetta, Daniele; Pelosi, Gualtiero; Vozzi, Federico; Michalis, Lampros K; Parodi, Oberdan; Fotiadis, Dimitrios I
2015-10-01
A framework for the inflation of micro-CT and histology data using intravascular ultrasound (IVUS) images, is presented. The proposed methodology consists of three steps. In the first step the micro-CT/histological images are manually co-registered with IVUS by experts using fiducial points as landmarks. In the second step the lumen of both the micro-CT/histological images and IVUS images are automatically segmented. Finally, in the third step the micro-CT/histological images are inflated by applying a transformation method on each image. The transformation method is based on the IVUS and micro-CT/histological contour difference. In order to validate the proposed image inflation methodology, plaque areas in the inflated micro-CT and histological images are compared with the ones in the IVUS images. The proposed methodology for inflating micro-CT/histological images increases the sensitivity of plaque area matching between the inflated and the IVUS images (7% and 22% in histological and micro-CT images, respectively). Copyright © 2015 Elsevier Ltd. All rights reserved.
Geometric artifacts reduction for cone-beam CT via L0-norm minimization without dedicated phantoms.
Gong, Changcheng; Cai, Yufang; Zeng, Li
2018-01-01
For cone-beam computed tomography (CBCT), transversal shifts of the rotation center exist inevitably, which will result in geometric artifacts in CT images. In this work, we propose a novel geometric calibration method for CBCT, which can also be used in micro-CT. The symmetry property of the sinogram is used for the first calibration, and then L0-norm of the gradient image from the reconstructed image is used as the cost function to be minimized for the second calibration. An iterative search method is adopted to pursue the local minimum of the L0-norm minimization problem. The transversal shift value is updated with affirmatory step size within a search range determined by the first calibration. In addition, graphic processing unit (GPU)-based FDK algorithm and acceleration techniques are designed to accelerate the calibration process of the presented new method. In simulation experiments, the mean absolute difference (MAD) and the standard deviation (SD) of the transversal shift value were less than 0.2 pixels between the noise-free and noisy projection images, which indicated highly accurate calibration applying the new calibration method. In real data experiments, the smaller entropies of the corrected images also indicated that higher resolution image was acquired using the corrected projection data and the textures were well protected. Study results also support the feasibility of applying the proposed method to other imaging modalities.
NASA Astrophysics Data System (ADS)
Rivest-Hénault, David; Dowson, Nicholas; Greer, Peter; Dowling, Jason
2014-03-01
MRI-alone treatment planning and adaptive MRI-based prostate radiation therapy are two promising techniques that could significantly increase the accuracy of the curative dose delivery processes while reducing the total radiation dose. State-of-the-art methods rely on the registration of a patient MRI with a MR-CT atlas for the estimation of pseudo-CT [5]. This atlas itself is generally created by registering many CT and MRI pairs. Most registration methods are not symmetric, but the order of the images influences the result [8]. The computed transformation is therefore biased, introducing unwanted variability. This work examines how much a symmetric algorithm improves the registration. Methods: A robust symmetric registration algorithm is proposed that simultaneously optimises a half space transform and its inverse. During the registration process, the two input volumetric images are transformed to a common position in space, therefore minimising any computational bias. An asymmetrical implementation of the same algorithm was used for comparison purposes. Results: Whole pelvis MRI and CT scans from 15 prostate patients were registered, as in the creation of MR-CT atlases. In each case, two registrations were performed, with different input image orders, and the transformation error quantified. Mean residuals of 0.63±0.26 mm (translation) and (8.7±7.3) × 10--3 rad (rotation) were found for the asymmetrical implementation with corresponding values of 0.038±0.039 mm and (1.6 ± 1.3) × 10--3 rad for the proposed symmetric algorithm, a substantial improvement. Conclusions: The increased registration precision will enhance the generation of pseudo-CT from MRI for atlas based MR planning methods.
Gee, Carole T
2013-11-01
As an alternative to conventional thin-sectioning, which destroys fossil material, high-resolution X-ray computed tomography (also called microtomography or microCT) integrated with scientific visualization, three-dimensional (3D) image segmentation, size analysis, and computer animation is explored as a nondestructive method of imaging the internal anatomy of 150-million-year-old conifer seed cones from the Late Jurassic Morrison Formation, USA, and of recent and other fossil cones. • MicroCT was carried out on cones using a General Electric phoenix v|tome|x s 240D, and resulting projections were processed with visualization software to produce image stacks of serial single sections for two-dimensional (2D) visualization, 3D segmented reconstructions with targeted structures in color, and computer animations. • If preserved in differing densities, microCT produced images of internal fossil tissues that showed important characters such as seed phyllotaxy or number of seeds per cone scale. Color segmentation of deeply embedded seeds highlighted the arrangement of seeds in spirals. MicroCT of recent cones was even more effective. • This is the first paper on microCT integrated with 3D segmentation and computer animation applied to silicified seed cones, which resulted in excellent 2D serial sections and segmented 3D reconstructions, revealing features requisite to cone identification and understanding of strobilus construction.
MO-DE-207-04: Imaging educational program on solutions to common pediatric imaging challenges
DOE Office of Scientific and Technical Information (OSTI.GOV)
Krishnamurthy, R.
This imaging educational program will focus on solutions to common pediatric imaging challenges. The speakers will present collective knowledge on best practices in pediatric imaging from their experience at dedicated children’s hospitals. The educational program will begin with a detailed discussion of the optimal configuration of fluoroscopes for general pediatric procedures. Following this introduction will be a focused discussion on the utility of Dual Energy CT for imaging children. The third lecture will address the substantial challenge of obtaining consistent image post -processing in pediatric digital radiography. The fourth and final lecture will address best practices in pediatric MRI includingmore » a discussion of ancillary methods to reduce sedation and anesthesia rates. Learning Objectives: To learn techniques for optimizing radiation dose and image quality in pediatric fluoroscopy To become familiar with the unique challenges and applications of Dual Energy CT in pediatric imaging To learn solutions for consistent post-processing quality in pediatric digital radiography To understand the key components of an effective MRI safety and quality program for the pediatric practice.« less
Connection method of separated luminal regions of intestine from CT volumes
NASA Astrophysics Data System (ADS)
Oda, Masahiro; Kitasaka, Takayuki; Furukawa, Kazuhiro; Watanabe, Osamu; Ando, Takafumi; Hirooka, Yoshiki; Goto, Hidemi; Mori, Kensaku
2015-03-01
This paper proposes a connection method of separated luminal regions of the intestine for Crohn's disease diagnosis. Crohn's disease is an inflammatory disease of the digestive tract. Capsule or conventional endoscopic diagnosis is performed for Crohn's disease diagnosis. However, parts of the intestines may not be observed in the endoscopic diagnosis if intestinal stenosis occurs. Endoscopes cannot pass through the stenosed parts. CT image-based diagnosis is developed as an alternative choice of the Crohn's disease. CT image-based diagnosis enables physicians to observe the entire intestines even if stenosed parts exist. CAD systems for Crohn's disease using CT volumes are recently developed. Such CAD systems need to reconstruct separated luminal regions of the intestines to analyze intestines. We propose a connection method of separated luminal regions of the intestines segmented from CT volumes. The luminal regions of the intestines are segmented from a CT volume. The centerlines of the luminal regions are calculated by using a thinning process. We enumerate all the possible sequences of the centerline segments. In this work, we newly introduce a condition using distance between connected ends points of the centerline segments. This condition eliminates unnatural connections of the centerline segments. Also, this condition reduces processing time. After generating a sequence list of the centerline segments, the correct sequence is obtained by using an evaluation function. We connect the luminal regions based on the correct sequence. Our experiments using four CT volumes showed that our method connected 6.5 out of 8.0 centerline segments per case. Processing times of the proposed method were reduced from the previous method.
Djan, Igor; Petrović, Borislava; Erak, Marko; Nikolić, Ivan; Lucić, Silvija
2013-08-01
Development of imaging techniques, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), made great impact on radiotherapy treatment planning by improving the localization of target volumes. Improved localization allows better local control of tumor volumes, but also minimizes geographical misses. Mutual information is obtained by registration and fusion of images achieved manually or automatically. The aim of this study was to validate the CT-MRI image fusion method and compare delineation obtained by CT versus CT-MRI image fusion. The image fusion software (XIO CMS 4.50.0) was applied to delineate 16 patients. The patients were scanned on CT and MRI in the treatment position within an immobilization device before the initial treatment. The gross tumor volume (GTV) and clinical target volume (CTV) were delineated on CT alone and on CT+MRI images consecutively and image fusion was obtained. Image fusion showed that CTV delineated on a CT image study set is mainly inadequate for treatment planning, in comparison with CTV delineated on CT-MRI fused image study set. Fusion of different modalities enables the most accurate target volume delineation. This study shows that registration and image fusion allows precise target localization in terms of GTV and CTV and local disease control.
Elhawary, Haytham; Oguro, Sota; Tuncali, Kemal; Morrison, Paul R.; Tatli, Servet; Shyn, Paul B.; Silverman, Stuart G.; Hata, Nobuhiko
2010-01-01
Rationale and Objectives To develop non-rigid image registration between pre-procedure contrast enhanced MR images and intra-procedure unenhanced CT images, to enhance tumor visualization and localization during CT-guided liver tumor cryoablation procedures. Materials and Methods After IRB approval, a non-rigid registration (NRR) technique was evaluated with different pre-processing steps and algorithm parameters and compared to a standard rigid registration (RR) approach. The Dice Similarity Coefficient (DSC), Target Registration Error (TRE), 95% Hausdorff distance (HD) and total registration time (minutes) were compared using a two-sided Student’s t-test. The entire registration method was then applied during five CT-guided liver cryoablation cases with the intra-procedural CT data transmitted directly from the CT scanner, with both accuracy and registration time evaluated. Results Selected optimal parameters for registration were section thickness of 5mm, cropping the field of view to 66% of its original size, manual segmentation of the liver, B-spline control grid of 5×5×5 and spatial sampling of 50,000 pixels. Mean 95% HD of 3.3mm (2.5x improvement compared to RR, p<0.05); mean DSC metric of 0.97 (13% increase); and mean TRE of 4.1mm (2.7x reduction) were measured. During the cryoablation procedure registration between the pre-procedure MR and the planning intra-procedure CT took a mean time of 10.6 minutes, the MR to targeting CT image took 4 minutes and MR to monitoring CT took 4.3 minutes. Mean registration accuracy was under 3.4mm. Conclusion Non-rigid registration allowed improved visualization of the tumor during interventional planning, targeting and evaluation of tumor coverage by the ice ball. Future work is focused on reducing segmentation time to make the method more clinically acceptable. PMID:20817574
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dong, Xue; Niu, Tianye; Zhu, Lei, E-mail: leizhu@gatech.edu
2014-05-15
Purpose: Dual-energy CT (DECT) is being increasingly used for its capability of material decomposition and energy-selective imaging. A generic problem of DECT, however, is that the decomposition process is unstable in the sense that the relative magnitude of decomposed signals is reduced due to signal cancellation while the image noise is accumulating from the two CT images of independent scans. Direct image decomposition, therefore, leads to severe degradation of signal-to-noise ratio on the resultant images. Existing noise suppression techniques are typically implemented in DECT with the procedures of reconstruction and decomposition performed independently, which do not explore the statistical propertiesmore » of decomposed images during the reconstruction for noise reduction. In this work, the authors propose an iterative approach that combines the reconstruction and the signal decomposition procedures to minimize the DECT image noise without noticeable loss of resolution. Methods: The proposed algorithm is formulated as an optimization problem, which balances the data fidelity and total variation of decomposed images in one framework, and the decomposition step is carried out iteratively together with reconstruction. The noise in the CT images from the proposed algorithm becomes well correlated even though the noise of the raw projections is independent on the two CT scans. Due to this feature, the proposed algorithm avoids noise accumulation during the decomposition process. The authors evaluate the method performance on noise suppression and spatial resolution using phantom studies and compare the algorithm with conventional denoising approaches as well as combined iterative reconstruction methods with different forms of regularization. Results: On the Catphan©600 phantom, the proposed method outperforms the existing denoising methods on preserving spatial resolution at the same level of noise suppression, i.e., a reduction of noise standard deviation by one order of magnitude. This improvement is mainly attributed to the high noise correlation in the CT images reconstructed by the proposed algorithm. Iterative reconstruction using different regularization, including quadratic orq-generalized Gaussian Markov random field regularization, achieves similar noise suppression from high noise correlation. However, the proposed TV regularization obtains a better edge preserving performance. Studies of electron density measurement also show that our method reduces the average estimation error from 9.5% to 7.1%. On the anthropomorphic head phantom, the proposed method suppresses the noise standard deviation of the decomposed images by a factor of ∼14 without blurring the fine structures in the sinus area. Conclusions: The authors propose a practical method for DECT imaging reconstruction, which combines the image reconstruction and material decomposition into one optimization framework. Compared to the existing approaches, our method achieves a superior performance on DECT imaging with respect to decomposition accuracy, noise reduction, and spatial resolution.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kazakia,G.; Burghardt, A.; Cheung, S.
2008-01-01
Assessment of bone tissue mineral density (TMD) may provide information critical to the understanding of mineralization processes and bone biomechanics. High-resolution three-dimensional assessment of TMD has recently been demonstrated using synchrotron radiation microcomputed tomography (SR{mu}CT); however, this imaging modality is relatively inaccessible due to the scarcity of SR facilities. Conventional desktop {mu}CT systems are widely available and have been used extensively to assess bone microarchitecture. However, the polychromatic source and cone-shaped beam geometry complicate assessment of TMD by conventional {mu}CT. The goal of this study was to evaluate {mu}CT-based measurement of degree and distribution of tissue mineralization in a quantitative,more » spatially resolved manner. Specifically, {mu}CT measures of bone mineral content (BMC) and TMD were compared to those obtained by SR{mu}CT and gravimetric methods. Cylinders of trabecular bone were machined from human femoral heads (n=5), vertebrae (n=5), and proximal tibiae (n=4). Cylinders were imaged in saline on a polychromatic {mu}CT system at an isotropic voxel size of 8 {mu}m. Volumes were reconstructed using beam hardening correction algorithms based on hydroxyapatite (HA)-resin wedge phantoms of 200 and 1200 mgHA/cm3. SR{mu}CT imaging was performed at an isotropic voxel size of 7.50 {mu}m at the National Synchrotron Light Source. Attenuation values were converted to HA concentration using a linear regression derived by imaging a calibration phantom. Architecture and mineralization parameters were calculated from the image data. Specimens were processed using gravimetric methods to determine ash mass and density. {mu}CT-based BMC values were not affected by altering the beam hardening correction. Volume-averaged TMD values calculated by the two corrections were significantly different (p=0.008) in high volume fraction specimens only, with the 1200 mgHA/cm3 correction resulting in a 4.7% higher TMD value. {mu}CT and SR{mu}CT provided significantly different measurements of both BMC and TMD (p<0.05). In high volume fraction specimens, {mu}CT with 1200 mgHA/cm3 correction resulted in BMC and TMD values 16.7% and 15.0% lower, respectively, than SR{mu}CT values. In low volume fraction specimens, {mu}CT with 1200 mgHA/cm3 correction resulted in BMC and TMD values 12.8% and 12.9% lower, respectively, than SR{mu}CT values. {mu}CT and SR{mu}CT values were well-correlated when volume fraction groups were considered individually (BMC R2=0.97-1.00; TMD R2=0.78-0.99). Ash mass and density were higher than the SR{mu}CT equivalents by 8.6% in high volume fraction specimens and 10.9% in low volume fraction specimens (p<0.05). BMC values calculated by tomography were highly correlated with ash mass (ash versus {mu}CT R2=0.96-1.00; ash versus SR{mu}CT R2=0.99-1.00). TMD values calculated by tomography were moderately correlated with ash density (ash versus {mu}CT R2=0.64-0.72; ash versus SR{mu}CT R2=0.64). Spatially resolved comparisons highlighted substantial geometric nonuniformity in the {mu}CT data, which were reduced (but not eliminated) using the 1200 mg HA/cm3 beam hardening correction, and did not exist in the SR{mu}CT data. This study represents the first quantitative comparison of {mu}CT mineralization evaluation against SR{mu}CT and gravimetry. Our results indicate that {mu}CT mineralization measures are underestimated but well-correlated with SR{mu}CT and gravimetric data, particularly when volume fraction groups are considered individually.« less
Kazakia, G. J.; Burghardt, A. J.; Cheung, S.; Majumdar, S.
2008-01-01
Assessment of bone tissue mineral density (TMD) may provide information critical to the understanding of mineralization processes and bone biomechanics. High-resolution three-dimensional assessment of TMD has recently been demonstrated using synchrotron radiation microcomputed tomography (SRμCT); however, this imaging modality is relatively inaccessible due to the scarcity of SR facilities. Conventional desktop μCT systems are widely available and have been used extensively to assess bone microarchitecture. However, the polychromatic source and cone-shaped beam geometry complicate assessment of TMD by conventional μCT. The goal of this study was to evaluate μCT-based measurement of degree and distribution of tissue mineralization in a quantitative, spatially resolved manner. Specifically, μCT measures of bone mineral content (BMC) and TMD were compared to those obtained by SRμCT and gravimetric methods. Cylinders of trabecular bone were machined from human femoral heads (n=5), vertebrae (n=5), and proximal tibiae (n=4). Cylinders were imaged in saline on a polychromatic μCT system at an isotropic voxel size of 8 μm. Volumes were reconstructed using beam hardening correction algorithms based on hydroxyapatite (HA)-resin wedge phantoms of 200 and 1200 mg HA∕cm3. SRμCT imaging was performed at an isotropic voxel size of 7.50 μm at the National Synchrotron Light Source. Attenuation values were converted to HA concentration using a linear regression derived by imaging a calibration phantom. Architecture and mineralization parameters were calculated from the image data. Specimens were processed using gravimetric methods to determine ash mass and density. μCT-based BMC values were not affected by altering the beam hardening correction. Volume-averaged TMD values calculated by the two corrections were significantly different (p=0.008) in high volume fraction specimens only, with the 1200 mg HA∕cm3 correction resulting in a 4.7% higher TMD value. μCT and SRμCT provided significantly different measurements of both BMC and TMD (p<0.05). In high volume fraction specimens, μCT with 1200 mg HA∕cm3 correction resulted in BMC and TMD values 16.7% and 15.0% lower, respectively, than SRμCT values. In low volume fraction specimens, μCT with 1200 mg HA∕cm3 correction resulted in BMC and TMD values 12.8% and 12.9% lower, respectively, than SRμCT values. μCT and SRμCT values were well-correlated when volume fraction groups were considered individually (BMC R2=0.97−1.00; TMD R2=0.78−0.99). Ash mass and density were higher than the SRμCT equivalents by 8.6% in high volume fraction specimens and 10.9% in low volume fraction specimens (p<0.05). BMC values calculated by tomography were highly correlated with ash mass (ash versus μCT R2=0.96−1.00; ash versus SRμCT R2=0.99−1.00). TMD values calculated by tomography were moderately correlated with ash density (ash versus μCT R2=0.64−0.72; ash versus SRμCT R2=0.64). Spatially resolved comparisons highlighted substantial geometric nonuniformity in the μCT data, which were reduced (but not eliminated) using the 1200 mg HA∕cm3 beam hardening correction, and did not exist in the SRμCT data. This study represents the first quantitative comparison of μCT mineralization evaluation against SRμCT and gravimetry. Our results indicate that μCT mineralization measures are underestimated but well-correlated with SRμCT and gravimetric data, particularly when volume fraction groups are considered individually. PMID:18697542
Advanced imaging in COPD: insights into pulmonary pathophysiology
Milne, Stephen
2014-01-01
Chronic obstructive pulmonary disease (COPD) involves a complex interaction of structural and functional abnormalities. The two have long been studied in isolation. However, advanced imaging techniques allow us to simultaneously assess pathological processes and their physiological consequences. This review gives a comprehensive account of the various advanced imaging modalities used to study COPD, including computed tomography (CT), magnetic resonance imaging (MRI), and the nuclear medicine techniques positron emission tomography (PET) and single-photon emission computed tomography (SPECT). Some more recent developments in imaging technology, including micro-CT, synchrotron imaging, optical coherence tomography (OCT) and electrical impedance tomography (EIT), are also described. The authors identify the pathophysiological insights gained from these techniques, and speculate on the future role of advanced imaging in both clinical and research settings. PMID:25478198
Volumetric CT-images improve testing of radiological image interpretation skills.
Ravesloot, Cécile J; van der Schaaf, Marieke F; van Schaik, Jan P J; ten Cate, Olle Th J; van der Gijp, Anouk; Mol, Christian P; Vincken, Koen L
2015-05-01
Current radiology practice increasingly involves interpretation of volumetric data sets. In contrast, most radiology tests still contain only 2D images. We introduced a new testing tool that allows for stack viewing of volumetric images in our undergraduate radiology program. We hypothesized that tests with volumetric CT-images enhance test quality, in comparison with traditional completely 2D image-based tests, because they might better reflect required skills for clinical practice. Two groups of medical students (n=139; n=143), trained with 2D and volumetric CT-images, took a digital radiology test in two versions (A and B), each containing both 2D and volumetric CT-image questions. In a questionnaire, they were asked to comment on the representativeness for clinical practice, difficulty and user-friendliness of the test questions and testing program. Students' test scores and reliabilities, measured with Cronbach's alpha, of 2D and volumetric CT-image tests were compared. Estimated reliabilities (Cronbach's alphas) were higher for volumetric CT-image scores (version A: .51 and version B: .54), than for 2D CT-image scores (version A: .24 and version B: .37). Participants found volumetric CT-image tests more representative of clinical practice, and considered them to be less difficult than volumetric CT-image questions. However, in one version (A), volumetric CT-image scores (M 80.9, SD 14.8) were significantly lower than 2D CT-image scores (M 88.4, SD 10.4) (p<.001). The volumetric CT-image testing program was considered user-friendly. This study shows that volumetric image questions can be successfully integrated in students' radiology testing. Results suggests that the inclusion of volumetric CT-images might improve the quality of radiology tests by positively impacting perceived representativeness for clinical practice and increasing reliability of the test. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
The CT image standardization based on the verified PSF
NASA Astrophysics Data System (ADS)
Wada, Shinichi; Ohkubo, Masaki; Kunii, Masayuki; Matsumoto, Toru; Murao, Kohei; Awai, Kazuo; Ikeda, Mitsuru
2007-03-01
This study discusses a method of CT image quality standardization that uses a point-spread function (PSF) in MDCT. CT image I(x,y,z) is represented by the following formula: I(x,y,z) = O(x,y,z)***PSF(x,y,z). Standardization was performed by measuring the three-dimensional (3-D) PSFs of two CT images with different image qualities. The image conversion method was constructed and tested using the 3-D PSFs and CT images of the CT scanners of three different manufacturers. The CT scanners used were Lightspeed QX/i, Somatom Volume Zoom, and Brilliance-40. To obtain the PSF(x,y) of these CT scanners, the line spread functions of the respective reconstruction kernels were measured using a phantom described by J.M. Boone. The kernels for each scanner were: soft, standard, lung, bone, and bone plus (GE); B20f, B40f, B41f, B50f, and B60f (Siemens); and B, C, D, E, and L (Philips). Slice sensitivity profile (SSP) were measured using a micro-disk phantom (50 μm* φ1 mm) with 5 mm slice thickness and beam pitch of 1.5 (GE, Siemens) and 0.626 (Philips). 3-D PSF was verified using an MDCT QA phantom. Real chest CT images were converted to images with contrasting standard image quality. Comparison between the converted CT image and the original standard image showed good agreement. The usefulness of the image conversion method is discussed using clinical CT images acquired by CT scanners produced by different manufacturers.
NASA Astrophysics Data System (ADS)
Mechlem, Korbinian; Ehn, Sebastian; Sellerer, Thorsten; Pfeiffer, Franz; Noël, Peter B.
2017-03-01
In spectral computed tomography (spectral CT), the additional information about the energy dependence of attenuation coefficients can be exploited to generate material selective images. These images have found applications in various areas such as artifact reduction, quantitative imaging or clinical diagnosis. However, significant noise amplification on material decomposed images remains a fundamental problem of spectral CT. Most spectral CT algorithms separate the process of material decomposition and image reconstruction. Separating these steps is suboptimal because the full statistical information contained in the spectral tomographic measurements cannot be exploited. Statistical iterative reconstruction (SIR) techniques provide an alternative, mathematically elegant approach to obtaining material selective images with improved tradeoffs between noise and resolution. Furthermore, image reconstruction and material decomposition can be performed jointly. This is accomplished by a forward model which directly connects the (expected) spectral projection measurements and the material selective images. To obtain this forward model, detailed knowledge of the different photon energy spectra and the detector response was assumed in previous work. However, accurately determining the spectrum is often difficult in practice. In this work, a new algorithm for statistical iterative material decomposition is presented. It uses a semi-empirical forward model which relies on simple calibration measurements. Furthermore, an efficient optimization algorithm based on separable surrogate functions is employed. This partially negates one of the major shortcomings of SIR, namely high computational cost and long reconstruction times. Numerical simulations and real experiments show strongly improved image quality and reduced statistical bias compared to projection-based material decomposition.
Zhang, Da; Mihai, Georgeta; Barbaras, Larry G; Brook, Olga R; Palmer, Matthew R
2018-05-10
Water equivalent diameter (Dw) reflects patient's attenuation and is a sound descriptor of patient size, and is used to determine size-specific dose estimator from a CT examination. Calculating Dw from CT localizer radiographs makes it possible to utilize Dw before actual scans and minimizes truncation errors due to limited reconstructed fields of view. One obstacle preventing the user community from implementing this useful tool is the necessity to calibrate localizer pixel values so as to represent water equivalent attenuation. We report a practical method to ease this calibration process. Dw is calculated from water equivalent area (Aw) which is deduced from the average localizer pixel value (LPV) of the line(s) in the localizer radiograph that correspond(s) to the axial image. The calibration process is conducted to establish the relationship between Aw and LPV. Localizer and axial images were acquired from phantoms of different total attenuation. We developed a program that automates the geometrical association between axial images and localizer lines and manages the measurements of Dw and average pixel values. We tested the calibration method on three CT scanners: a GE CT750HD, a Siemens Definition AS, and a Toshiba Acquilion Prime80, for both posterior-anterior (PA) and lateral (LAT) localizer directions (for all CTs) and with different localizer filters (for the Toshiba CT). The computer program was able to correctly perform the geometrical association between corresponding axial images and localizer lines. Linear relationships between Aw and LPV were observed (with R 2 all greater than 0.998) on all tested conditions, regardless of the direction and image filters used on the localizer radiographs. When comparing LAT and PA directions with the same image filter and for the same scanner, the slope values were close (maximum difference of 0.02 mm), and the intercept values showed larger deviations (maximum difference of 2.8 mm). Water equivalent diameter estimation on phantoms and patients demonstrated high accuracy of the calibration: percentage difference between Dw from axial images and localizers was below 2%. With five clinical chest examinations and five abdominal-pelvic examinations of varying patient sizes, the maximum percentage difference was approximately 5%. Our study showed that Aw and LPV are highly correlated, providing enough evidence to allow for the Dw determination once the experimental calibration process is established. © 2018 American Association of Physicists in Medicine.
Dependence of quantitative accuracy of CT perfusion imaging on system parameters
NASA Astrophysics Data System (ADS)
Li, Ke; Chen, Guang-Hong
2017-03-01
Deconvolution is a popular method to calculate parametric perfusion parameters from four dimensional CT perfusion (CTP) source images. During the deconvolution process, the four dimensional space is squeezed into three-dimensional space by removing the temporal dimension, and a prior knowledge is often used to suppress noise associated with the process. These additional complexities confound the understanding about deconvolution-based CTP imaging system and how its quantitative accuracy depends on parameters and sub-operations involved in the image formation process. Meanwhile, there has been a strong clinical need in answering this question, as physicians often rely heavily on the quantitative values of perfusion parameters to make diagnostic decisions, particularly during an emergent clinical situation (e.g. diagnosis of acute ischemic stroke). The purpose of this work was to develop a theoretical framework that quantitatively relates the quantification accuracy of parametric perfusion parameters with CTP acquisition and post-processing parameters. This goal was achieved with the help of a cascaded systems analysis for deconvolution-based CTP imaging systems. Based on the cascaded systems analysis, the quantitative relationship between regularization strength, source image noise, arterial input function, and the quantification accuracy of perfusion parameters was established. The theory could potentially be used to guide developments of CTP imaging technology for better quantification accuracy and lower radiation dose.
Development of proton CT imaging system using plastic scintillator and CCD camera
NASA Astrophysics Data System (ADS)
Tanaka, Sodai; Nishio, Teiji; Matsushita, Keiichiro; Tsuneda, Masato; Kabuki, Shigeto; Uesaka, Mitsuru
2016-06-01
A proton computed tomography (pCT) imaging system was constructed for evaluation of the error of an x-ray CT (xCT)-to-WEL (water-equivalent length) conversion in treatment planning for proton therapy. In this system, the scintillation light integrated along the beam direction is obtained by photography using the CCD camera, which enables fast and easy data acquisition. The light intensity is converted to the range of the proton beam using a light-to-range conversion table made beforehand, and a pCT image is reconstructed. An experiment for demonstration of the pCT system was performed using a 70 MeV proton beam provided by the AVF930 cyclotron at the National Institute of Radiological Sciences. Three-dimensional pCT images were reconstructed from the experimental data. A thin structure of approximately 1 mm was clearly observed, with spatial resolution of pCT images at the same level as that of xCT images. The pCT images of various substances were reconstructed to evaluate the pixel value of pCT images. The image quality was investigated with regard to deterioration including multiple Coulomb scattering.
Blind CT image quality assessment via deep learning strategy: initial study
NASA Astrophysics Data System (ADS)
Li, Sui; He, Ji; Wang, Yongbo; Liao, Yuting; Zeng, Dong; Bian, Zhaoying; Ma, Jianhua
2018-03-01
Computed Tomography (CT) is one of the most important medical imaging modality. CT images can be used to assist in the detection and diagnosis of lesions and to facilitate follow-up treatment. However, CT images are vulnerable to noise. Actually, there are two major source intrinsically causing the CT data noise, i.e., the X-ray photo statistics and the electronic noise background. Therefore, it is necessary to doing image quality assessment (IQA) in CT imaging before diagnosis and treatment. Most of existing CT images IQA methods are based on human observer study. However, these methods are impractical in clinical for their complex and time-consuming. In this paper, we presented a blind CT image quality assessment via deep learning strategy. A database of 1500 CT images is constructed, containing 300 high-quality images and 1200 corresponding noisy images. Specifically, the high-quality images were used to simulate the corresponding noisy images at four different doses. Then, the images are scored by the experienced radiologists by the following attributes: image noise, artifacts, edge and structure, overall image quality, and tumor size and boundary estimation with five-point scale. We trained a network for learning the non-liner map from CT images to subjective evaluation scores. Then, we load the pre-trained model to yield predicted score from the test image. To demonstrate the performance of the deep learning network in IQA, correlation coefficients: Pearson Linear Correlation Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) are utilized. And the experimental result demonstrate that the presented deep learning based IQA strategy can be used in the CT image quality assessment.
Wong, Ka-Kit; Gandhi, Arpit; Viglianti, Benjamin L; Fig, Lorraine M; Rubello, Domenico; Gross, Milton D
2016-01-01
AIM: To review the benefits of single photon emission computed tomography (SPECT)/computed tomography (CT) hybrid imaging for diagnosis of various endocrine disorders. METHODS: We performed MEDLINE and PubMed searches using the terms: “SPECT/CT”; “functional anatomic mapping”; “transmission emission tomography”; “parathyroid adenoma”; “thyroid cancer”; “neuroendocrine tumor”; “adrenal”; “pheochromocytoma”; “paraganglioma”; in order to identify relevant articles published in English during the years 2003 to 2015. Reference lists from the articles were reviewed to identify additional pertinent articles. Retrieved manuscripts (case reports, reviews, meta-analyses and abstracts) concerning the application of SPECT/CT to endocrine imaging were analyzed to provide a descriptive synthesis of the utility of this technology. RESULTS: The emergence of hybrid SPECT/CT camera technology now allows simultaneous acquisition of combined multi-modality imaging, with seamless fusion of three-dimensional volume datasets. The usefulness of combining functional information to depict the bio-distribution of radiotracers that map cellular processes of the endocrine system and tumors of endocrine origin, with anatomy derived from CT, has improved the diagnostic capability of scintigraphy for a range of disorders of endocrine gland function. The literature describes benefits of SPECT/CT for 99mTc-sestamibi parathyroid scintigraphy and 99mTc-pertechnetate thyroid scintigraphy, 123I- or 131I-radioiodine for staging of differentiated thyroid carcinoma, 111In- and 99mTc- labeled somatostatin receptor analogues for detection of neuroendocrine tumors, 131I-norcholesterol (NP-59) scans for assessment of adrenal cortical hyperfunction, and 123I- or 131I-metaiodobenzylguanidine imaging for evaluation of pheochromocytoma and paraganglioma. CONCLUSION: SPECT/CT exploits the synergism between the functional information from radiopharmaceutical imaging and anatomy from CT, translating to improved diagnostic accuracy and meaningful impact on patient care. PMID:27358692
Software Method for Computed Tomography Cylinder Data Unwrapping, Re-slicing, and Analysis
NASA Technical Reports Server (NTRS)
Roth, Don J.
2013-01-01
A software method has been developed that is applicable for analyzing cylindrical and partially cylindrical objects inspected using computed tomography (CT). This method involves unwrapping and re-slicing data so that the CT data from the cylindrical object can be viewed as a series of 2D sheets (or flattened onion skins ) in addition to a series of top view slices and 3D volume rendering. The advantages of viewing the data in this fashion are as follows: (1) the use of standard and specialized image processing and analysis methods is facilitated having 2D array data versus a volume rendering; (2) accurate lateral dimensional analysis of flaws is possible in the unwrapped sheets versus volume rendering; (3) flaws in the part jump out at the inspector with the proper contrast expansion settings in the unwrapped sheets; and (4) it is much easier for the inspector to locate flaws in the unwrapped sheets versus top view slices for very thin cylinders. The method is fully automated and requires no input from the user except proper voxel dimension from the CT experiment and wall thickness of the part. The software is available in 32-bit and 64-bit versions, and can be used with binary data (8- and 16-bit) and BMP type CT image sets. The software has memory (RAM) and hard-drive based modes. The advantage of the (64-bit) RAM-based mode is speed (and is very practical for users of 64-bit Windows operating systems and computers having 16 GB or more RAM). The advantage of the hard-drive based analysis is one can work with essentially unlimited-sized data sets. Separate windows are spawned for the unwrapped/re-sliced data view and any image processing interactive capability. Individual unwrapped images and un -wrapped image series can be saved in common image formats. More information is available at http://www.grc.nasa.gov/WWW/OptInstr/ NDE_CT_CylinderUnwrapper.html.
Microtomographic imaging in the process of bone modeling and simulation
NASA Astrophysics Data System (ADS)
Mueller, Ralph
1999-09-01
Micro-computed tomography ((mu) CT) is an emerging technique to nondestructively image and quantify trabecular bone in three dimensions. Where the early implementations of (mu) CT focused more on technical aspects of the systems and required equipment not normally available to the general public, a more recent development emphasized practical aspects of micro- tomographic imaging. That system is based on a compact fan- beam type of tomograph, also referred to as desktop (mu) CT. Desk-top (mu) CT has been used extensively for the investigation of osteoporosis related health problems gaining new insight into the organization of trabecular bone and the influence of osteoporotic bone loss on bone architecture and the competence of bone. Osteoporosis is a condition characterized by excessive bone loss and deterioration in bone architecture. The reduced quality of bone increases the risk of fracture. Current imaging technologies do not allow accurate in vivo measurements of bone structure over several decades or the investigation of the local remodeling stimuli at the tissue level. Therefore, computer simulations and new experimental modeling procedures are necessary for determining the long-term effects of age, menopause, and osteoporosis on bone. Microstructural bone models allow us to study not only the effects of osteoporosis on the skeleton but also to assess and monitor the effectiveness of new treatment regimens. The basis for such approaches are realistic models of bone and a sound understanding of the underlying biological and mechanical processes in bone physiology. In this article, strategies for new approaches to bone modeling and simulation in the study and treatment of osteoporosis and age-related bone loss are presented. The focus is on the bioengineering and imaging aspects of osteoporosis research. With the introduction of desk-top (mu) CT, a new generation of imaging instruments has entered the arena allowing easy and relatively inexpensive access to the three-dimensional microstructure of bone, thereby giving bone researchers a powerful tool for the exploration of age-related bone loss and osteoporosis.
NASA Astrophysics Data System (ADS)
Sun, Jidi; Dowling, Jason; Pichler, Peter; Menk, Fred; Rivest-Henault, David; Lambert, Jonathan; Parker, Joel; Arm, Jameen; Best, Leah; Martin, Jarad; Denham, James W.; Greer, Peter B.
2015-04-01
To clinically implement MRI simulation or MRI-alone treatment planning requires comprehensive end-to-end testing to ensure an accurate process. The purpose of this study was to design and build a geometric phantom simulating a human male pelvis that is suitable for both CT and MRI scanning and use it to test geometric and dosimetric aspects of MRI simulation including treatment planning and digitally reconstructed radiograph (DRR) generation. A liquid filled pelvic shaped phantom with simulated pelvic organs was scanned in a 3T MRI simulator with dedicated radiotherapy couch-top, laser bridge and pelvic coil mounts. A second phantom with the same external shape but with an internal distortion grid was used to quantify the distortion of the MR image. Both phantoms were also CT scanned as the gold-standard for both geometry and dosimetry. Deformable image registration was used to quantify the MR distortion. Dose comparison was made using a seven-field IMRT plan developed on the CT scan with the fluences copied to the MR image and recalculated using bulk electron densities. Without correction the maximum distortion of the MR compared with the CT scan was 7.5 mm across the pelvis, while this was reduced to 2.6 and 1.7 mm by the vendor’s 2D and 3D correction algorithms, respectively. Within the locations of the internal organs of interest, the distortion was <1.5 and <1 mm with 2D and 3D correction algorithms, respectively. The dose at the prostate isocentre calculated on CT and MRI images differed by 0.01% (1.1 cGy). Positioning shifts were within 1 mm when setup was performed using MRI generated DRRs compared to setup using CT DRRs. The MRI pelvic phantom allows end-to-end testing of the MRI simulation workflow with comparison to the gold-standard CT based process. MRI simulation was found to be geometrically accurate with organ dimensions, dose distributions and DRR based setup within acceptable limits compared to CT.
Pettinato, C; Nanni, C; Farsad, M; Castellucci, P; Sarnelli, A; Civollani, S; Franchi, R; Fanti, S; Marengo, M; Bergamini, C
2006-01-01
Positron emission tomography (PET) is a non-invasive imaging modality, which is clinically widely used both for diagnosis and accessing therapy response in oncology, cardiology and neurology. Fusing PET and CT images in a single dataset would be useful for physicians who could read the functional and the anatomical aspects of a disease in a single shot. The use of fusion software has been replaced in the last few years by integrated PET/CT systems, which combine a PET and a CT scanner in the same gantry. CT images have the double function to correct PET images for attenuation and can fuse with PET for a better visualization and localization of lesions. The use of CT for attenuation correction yields several advantages in terms of accuracy and patient comfort, but can also introduce several artefacts on PET-corrected images. PET/CT image artefacts are due primarily to metallic implants, respiratory motion, use of contrast media and image truncation. This paper reviews different types artefacts and their correction methods. PET/CT improves image quality and image accuracy. However, to avoid possible pitfalls the simultaneous display of both Computed Tomography Attenuation Corrected (CTAC) and non corrected PET images, side by side with CT images is strongly recommended. PMID:21614340
SU-C-207A-03: Development of Proton CT Imaging System Using Thick Scintillator and CCD Camera
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tanaka, S; Uesaka, M; Nishio, T
2016-06-15
Purpose: In the treatment planning of proton therapy, Water Equivalent Length (WEL), which is the parameter for the calculation of dose and the range of proton, is derived by X-ray CT (xCT) image and xCT-WEL conversion. However, about a few percent error in the accuracy of proton range calculation through this conversion has been reported. The purpose of this study is to construct a proton CT (pCT) imaging system for an evaluation of the error. Methods: The pCT imaging system was constructed with a thick scintillator and a cooled CCD camera, which acquires the two-dimensional image of integrated value ofmore » the scintillation light toward the beam direction. The pCT image is reconstructed by FBP method using a correction between the light intensity and residual range of proton beam. An experiment for the demonstration of this system was performed with 70-MeV proton beam provided by NIRS cyclotron. The pCT image of several objects reconstructed from the experimental data was evaluated quantitatively. Results: Three-dimensional pCT images of several objects were reconstructed experimentally. A finestructure of approximately 1 mm was clearly observed. The position resolution of pCT image was almost the same as that of xCT image. And the error of proton CT pixel value was up to 4%. The deterioration of image quality was caused mainly by the effect of multiple Coulomb scattering. Conclusion: We designed and constructed the pCT imaging system using a thick scintillator and a CCD camera. And the system was evaluated with the experiment by use of 70-MeV proton beam. Three-dimensional pCT images of several objects were acquired by the system. This work was supported by JST SENTAN Grant Number 13A1101 and JSPS KAKENHI Grant Number 15H04912.« less
Imaging technologies for preclinical models of bone and joint disorders
2011-01-01
Preclinical models for musculoskeletal disorders are critical for understanding the pathogenesis of bone and joint disorders in humans and the development of effective therapies. The assessment of these models primarily relies on morphological analysis which remains time consuming and costly, requiring large numbers of animals to be tested through different stages of the disease. The implementation of preclinical imaging represents a keystone in the refinement of animal models allowing longitudinal studies and enabling a powerful, non-invasive and clinically translatable way for monitoring disease progression in real time. Our aim is to highlight examples that demonstrate the advantages and limitations of different imaging modalities including magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), single-photon emission computed tomography (SPECT) and optical imaging. All of which are in current use in preclinical skeletal research. MRI can provide high resolution of soft tissue structures, but imaging requires comparatively long acquisition times; hence, animals require long-term anaesthesia. CT is extensively used in bone and joint disorders providing excellent spatial resolution and good contrast for bone imaging. Despite its excellent structural assessment of mineralized structures, CT does not provide in vivo functional information of ongoing biological processes. Nuclear medicine is a very promising tool for investigating functional and molecular processes in vivo with new tracers becoming available as biomarkers. The combined use of imaging modalities also holds significant potential for the assessment of disease pathogenesis in animal models of musculoskeletal disorders, minimising the use of conventional invasive methods and animal redundancy. PMID:22214535
DOE Office of Scientific and Technical Information (OSTI.GOV)
Meer, Skadi van der; Camps, Saskia M.; Oncology Solutions Department, Philips Research, High Tech Campus 34, Eindhoven 5656 AE
Purpose: Imaging of patient anatomy during treatment is a necessity for position verification and for adaptive radiotherapy based on daily dose recalculation. Ultrasound (US) image guided radiotherapy systems are currently available to collect US images at the simulation stage (US{sub sim}), coregistered with the simulation computed tomography (CT), and during all treatment fractions. The authors hypothesize that a deformation field derived from US-based deformable image registration can be used to create a daily pseudo-CT (CT{sub ps}) image that is more representative of the patients’ geometry during treatment than the CT acquired at simulation stage (CT{sub sim}). Methods: The three prostatemore » patients, considered to evaluate this hypothesis, had coregistered CT and US scans on various days. In particular, two patients had two US–CT datasets each and the third one had five US–CT datasets. Deformation fields were computed between pairs of US images of the same patient and then applied to the corresponding US{sub sim} scan to yield a new deformed CT{sub ps} scan. The original treatment plans were used to recalculate dose distributions in the simulation, deformed and ground truth CT (CT{sub gt}) images to compare dice similarity coefficients, maximum absolute distance, and mean absolute distance on CT delineations and gamma index (γ) evaluations on both the Hounsfield units (HUs) and the dose. Results: In the majority, deformation did improve the results for all three evaluation methods. The change in gamma failure for dose (γ{sub Dose}, 3%, 3 mm) ranged from an improvement of 11.2% in the prostate volume to a deterioration of 1.3% in the prostate and bladder. The change in gamma failure for the CT images (γ{sub CT}, 50 HU, 3 mm) ranged from an improvement of 20.5% in the anus and rectum to a deterioration of 3.2% in the prostate. Conclusions: This new technique may generate CT{sub ps} images that are more representative of the actual patient anatomy than the CT{sub sim} scan.« less
Material Separation Using Dual-Energy CT: Current and Emerging Applications.
Patino, Manuel; Prochowski, Andrea; Agrawal, Mukta D; Simeone, Frank J; Gupta, Rajiv; Hahn, Peter F; Sahani, Dushyant V
2016-01-01
Dual-energy (DE) computed tomography (CT) offers the opportunity to generate material-specific images on the basis of the atomic number Z and the unique mass attenuation coefficient of a particular material at different x-ray energies. Material-specific images provide qualitative and quantitative information about tissue composition and contrast media distribution. The most significant contribution of DE CT-based material characterization comes from the capability to assess iodine distribution through the creation of an image that exclusively shows iodine. These iodine-specific images increase tissue contrast and amplify subtle differences in attenuation between normal and abnormal tissues, improving lesion detection and characterization in the abdomen. In addition, DE CT enables computational removal of iodine influence from a CT image, generating virtual noncontrast images. Several additional materials, including calcium, fat, and uric acid, can be separated, permitting imaging assessment of metabolic imbalances, elemental deficiencies, and abnormal deposition of materials within tissues. The ability to obtain material-specific images from a single, contrast-enhanced CT acquisition can complement the anatomic knowledge with functional information, and may be used to reduce the radiation dose by decreasing the number of phases in a multiphasic CT examination. DE CT also enables generation of energy-specific and virtual monochromatic images. Clinical applications of DE CT leverage both material-specific images and virtual monochromatic images to expand the current role of CT and overcome several limitations of single-energy CT. (©)RSNA, 2016.
Imaging of the meninges and the extra-axial spaces.
Kirmi, Olga; Sheerin, Fintan; Patel, Neel
2009-12-01
The separate meningeal layers and extraaxial spaces are complex and can only be differentiated by pathologic processes on imaging. Differentiation of the location of such processes can be achieved using different imaging modalities. In this pictorial review we address the imaging techniques, enhancement and location patterns, and disease spread that will promote accurate localization of the pathology, thus improving accuracy of diagnosis. Typical and unusual magnetic resonance (MR), computed tomography (CT), and ultrasound imaging findings of many conditions affecting these layers and spaces are described.
Optical imaging: new tools for arthritis.
Chamberland, David; Jiang, Yebin; Wang, Xueding
2010-10-01
Conventional radiography, ultrasound, CT, MRI, and nuclear imaging are the current imaging modalities used for clinical evaluation of arthritis which is highly prevalent and a leading cause of disability. Some of these types of imaging are also used for monitoring disease progression and treatment response of arthritis. However, their disadvantages limit their utilities, such as ionizing radiation for radiography, CT, and nuclear imaging; suboptimal tissue contrast resolution for radiography, CT, ultrasound, and nuclear imaging; high cost for CT and MRI and nuclear imaging; and long data-acquisition time with ensuing patient discomfort for MRI. Recently, there have been considerable advances in nonionizing noninvasive optical imaging which has demonstrated promise for early diagnosis, monitoring therapeutic interventions and disease progression of arthritis. Optical based molecular imaging modalities such as fluorescence imaging have shown high sensitivity in detection of optical contrast agents and can aid early diagnosis and ongoing evaluation of chronic inflammatory arthritis. Optical transillumination imaging or diffuse optical tomography may differentiate normal joint clear synovial fluid from turbid and pink medium early in the inflammatory process. Fourier transform infrared spectroscopy has been used to evaluate fluid composition from joints affected by arthritis. Hemodynamic changes such as angiogenesis, hypervascularization, and hypoxia in arthritic articular tissue can potentially be observed by diffuse optical tomography and photoacoustic tomography. Optical measurements could also facilitate quantification of hemodynamic properties such as blood volume and oxygenation levels at early stages of inflammatory arthritis. Optical imaging provides methodologies which should contribute to detection of early changes and monitoring of progression in pathological characteristics of arthritis, with relatively simple instrumentation.
Assessment of angiogenesis in osseointegration of a silica-collagen biomaterial using 3D-nano-CT.
Alt, Volker; Kögelmaier, Daniela Vera; Lips, Katrin S; Witt, Vera; Pacholke, Sabine; Heiss, Christian; Kampschulte, Marian; Heinemann, Sascha; Hanke, Thomas; Thormann, Ulrich; Schnettler, Reinhard; Langheinrich, Alexander C
2011-10-01
Bony integration of biomaterials is a complex process in which angiogenesis plays a crucial role. We evaluated micro- and nano-CT imaging to demonstrate and quantify neovascularization in bony integration of a biomaterial and to give an image based estimation for the needed resolution for imaging angiogenesis in an animal model of femora defect healing. In 8 rats 5mm full-size defects were created at the left femur that was filled with silica-collagen bone substitute material and internally fixed with plate osteosynthesis. After 6 weeks the femora were infused in situ with Microfil, harvested and scanned for micro-CT (9 μm)(3) and nano-CT (3 μm)(3) imaging. Using those 3D images, the newly formed blood vessels in the area of the biomaterial were assessed and the total vascular volume fraction, the volume of the bone substitute material and the volume of the bone defect were quantitatively characterized. Results were complemented by histology. Differences were statistically assessed using (ANOVA). High-resolution nano-CT demonstrated new blood vessel formation surrounding the biomaterial in all animals at capillary level. Immunohistochemistry confirmed the newly formed blood vessels surrounding the bone substitute material. The mean vascular volume fraction (VVF) around the implant was calculated to be 3.01 ± 0.4%. The VVF was inversely correlated with the volume of the bone substitute material (r=0.8) but not with the dimension of the fracture zone (r=0.3). Nano-CT imaging is feasible for quantitative analysis of angiogenesis during bony integration of biomaterials and a promising tool in this context for the future. Copyright © 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.
Larsson, Anne; Johansson, Adam; Axelsson, Jan; Nyholm, Tufve; Asklund, Thomas; Riklund, Katrine; Karlsson, Mikael
2013-02-01
The aim of this study was to evaluate MR-based attenuation correction of PET emission data of the head, based on a previously described technique that calculates substitute CT (sCT) images from a set of MR images. Images from eight patients, examined with (18)F-FLT PET/CT and MRI, were included. sCT images were calculated and co-registered to the corresponding CT images, and transferred to the PET/CT scanner for reconstruction. The new reconstructions were then compared with the originals. The effect of replacing bone with soft tissue in the sCT-images was also evaluated. The average relative difference between the sCT-corrected PET images and the CT-corrected PET images was 1.6% for the head and 1.9% for the brain. The average standard deviations of the relative differences within the head were relatively high, at 13.2%, primarily because of large differences in the nasal septa region. For the brain, the average standard deviation was lower, 4.1%. The global average difference in the head when replacing bone with soft tissue was 11%. The method presented here has a high rate of accuracy, but high-precision quantitative imaging of the nasal septa region is not possible at the moment.
Ogata, Yuji; Nakahara, Tadaki; Ode, Kenichi; Matsusaka, Yohji; Katagiri, Mari; Iwabuchi, Yu; Itoh, Kazunari; Ichimura, Akira; Jinzaki, Masahiro
2017-05-01
We developed a method of image data projection of bone SPECT into 3D volume-rendered CT images for 3D SPECT/CT fusion. The aims of our study were to evaluate its feasibility and clinical usefulness. Whole-body bone scintigraphy (WB) and SPECT/CT scans were performed in 318 cancer patients using a dedicated SPECT/CT systems. Volume data of bone SPECT and CT were fused to obtain 2D SPECT/CT images. To generate our 3D SPECT/CT images, colored voxel data of bone SPECT were projected onto the corresponding location of the volume-rendered CT data after a semi-automatic bone extraction. Then, the resultant 3D images were blended with conventional volume-rendered CT images, allowing to grasp the three-dimensional relationship between bone metabolism and anatomy. WB and SPECT (WB + SPECT), 2D SPECT/CT fusion, and 3D SPECT/CT fusion were evaluated by two independent reviewers in the diagnosis of bone metastasis. The inter-observer variability and diagnostic accuracy in these three image sets were investigated using a four-point diagnostic scale. Increased bone metabolism was found in 744 metastatic sites and 1002 benign changes. On a per-lesion basis, inter-observer agreements in the diagnosis of bone metastasis were 0.72 for WB + SPECT, 0.90 for 2D SPECT/CT, and 0.89 for 3D SPECT/CT. Receiver operating characteristic analyses for the diagnostic accuracy of bone metastasis showed that WB + SPECT, 2D SPECT/CT, and 3D SPECT/CT had an area under the curve of 0.800, 0.983, and 0.983 for reader 1, 0.865, 0.992, and 0.993 for reader 2, respectively (WB + SPECT vs. 2D or 3D SPECT/CT, p < 0.001; 2D vs. 3D SPECT/CT, n.s.). The durations of interpretation of WB + SPECT, 2D SPECT/CT, and 3D SPECT/CT images were 241 ± 75, 225 ± 73, and 182 ± 71 s for reader 1 and 207 ± 72, 190 ± 73, and 179 ± 73 s for reader 2, respectively. As a result, it took shorter time to read 3D SPECT/CT images than 2D SPECT/CT (p < 0.0001) or WB + SPECT images (p < 0.0001). 3D SPECT/CT fusion offers comparable diagnostic accuracy to 2D SPECT/CT fusion. The visual effect of 3D SPECT/CT fusion facilitates reduction of reading time compared to 2D SPECT/CT fusion.
Correlative CT and anatomic study of the sciatic nerve
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pech, P.; Haughton, V.
1985-05-01
Sciatica can be caused by numerous processes affecting the sciatic nerve or its components within the pelvis including tumors, infectious diseases, aneurysms, fractures, and endometriosis. The CT diagnosis of these causes of sciatica has not been emphasized. This study identified the course and appearance of the normal sciatic nerve in the pelvis by correlating CT and anatomic slices in cadavers. For purposes of discussion, the sciatic nerve complex is conveniently divided into three parts: presacral, muscular, and ischial. Each part is illustrated here by two cryosections with corresponding CT images.
Dynamic updating atlas for heart segmentation with a nonlinear field-based model.
Cai, Ken; Yang, Rongqian; Yue, Hongwei; Li, Lihua; Ou, Shanxing; Liu, Feng
2017-09-01
Segmentation of cardiac computed tomography (CT) images is an effective method for assessing the dynamic function of the heart and lungs. In the atlas-based heart segmentation approach, the quality of segmentation usually relies upon atlas images, and the selection of those reference images is a key step. The optimal goal in this selection process is to have the reference images as close to the target image as possible. This study proposes an atlas dynamic update algorithm using a scheme of nonlinear deformation field. The proposed method is based on the features among double-source CT (DSCT) slices. The extraction of these features will form a base to construct an average model and the created reference atlas image is updated during the registration process. A nonlinear field-based model was used to effectively implement a 4D cardiac segmentation. The proposed segmentation framework was validated with 14 4D cardiac CT sequences. The algorithm achieved an acceptable accuracy (1.0-2.8 mm). Our proposed method that combines a nonlinear field-based model and dynamic updating atlas strategies can provide an effective and accurate way for whole heart segmentation. The success of the proposed method largely relies on the effective use of the prior knowledge of the atlas and the similarity explored among the to-be-segmented DSCT sequences. Copyright © 2016 John Wiley & Sons, Ltd.
Iğdem, S; Alço, G; Ercan, T; Unalan, B; Kara, B; Geceer, G; Akman, C; Zengin, F O; Atilla, S; Okkan, S
2010-04-01
To analyse the effect of the use of molecular imaging on gross target volume (GTV) definition and treatment management. Fifty patients with various solid tumours who underwent positron emission tomography (PET)/computed tomography (CT) simulation for radiotherapy planning from 2006 to 2008 were enrolled in this study. First, F-18 fluorodeoxyglucose (FDG)-PET and CT scans of the treatment site in the treatment position and then a whole body scan were carried out with a dedicated PET/CT scanner and fused thereafter. FDG-avid primary tumour and lymph nodes were included into the GTV. A multidisciplinary team defined the target volume, and contouring was carried out by a radiation oncologist using visual methods. To compare the PET/CT-based volumes with CT-based volumes, contours were drawn on CT-only data with the help of site-specific radiologists who were blind to the PET/CT results after a median time of 7 months. In general, our PET/CT volumes were larger than our CT-based volumes. This difference was significant in patients with head and neck cancers. Major changes (> or =25%) in GTV delineation were observed in 44% of patients. In 16% of cases, PET/CT detected incidental second primaries and metastatic disease, changing the treatment strategy from curative to palliative. Integrating functional imaging with FDG-PET/CT into the radiotherapy planning process resulted in major changes in a significant proportion of our patients. An interdisciplinary approach between imaging and radiation oncology departments is essential in defining the target volumes. Copyright 2010 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
Simulation of spatiotemporal CT data sets using a 4D MRI-based lung motion model.
Marx, Mirko; Ehrhardt, Jan; Werner, René; Schlemmer, Heinz-Peter; Handels, Heinz
2014-05-01
Four-dimensional CT imaging is widely used to account for motion-related effects during radiotherapy planning of lung cancer patients. However, 4D CT often contains motion artifacts, cannot be used to measure motion variability, and leads to higher dose exposure. In this article, we propose using 4D MRI to acquire motion information for the radiotherapy planning process. From the 4D MRI images, we derive a time-continuous model of the average patient-specific respiratory motion, which is then applied to simulate 4D CT data based on a static 3D CT. The idea of the motion model is to represent the average lung motion over a respiratory cycle by cyclic B-spline curves. The model generation consists of motion field estimation in the 4D MRI data by nonlinear registration, assigning respiratory phases to the motion fields, and applying a B-spline approximation on a voxel-by-voxel basis to describe the average voxel motion over a breathing cycle. To simulate a patient-specific 4D CT based on a static CT of the patient, a multi-modal registration strategy is introduced to transfer the motion model from MRI to the static CT coordinates. Differences between model-based estimated and measured motion vectors are on average 1.39 mm for amplitude-based binning of the 4D MRI data of three patients. In addition, the MRI-to-CT registration strategy is shown to be suitable for the model transformation. The application of our 4D MRI-based motion model for simulating 4D CT images provides advantages over standard 4D CT (less motion artifacts, radiation-free). This makes it interesting for radiotherapy planning.
Inpainting approaches to fill in detector gaps in phase contrast computed tomography
NASA Astrophysics Data System (ADS)
Brun, F.; Delogu, P.; Longo, R.; Dreossi, D.; Rigon, L.
2018-01-01
Photon counting semiconductor detectors in radiation imaging present attractive properties, such as high efficiency, low noise, and energy sensitivity. The very complex electronics limits the sensitive area of current devices to a few square cm. This disadvantage is often compensated by tiling a larger matrix with an adequate number of detector units but this usually results in non-negligible insensitive gaps between two adjacent modules. When considering the case of Computed Tomography (CT), these gaps lead to degraded reconstructed images with severe streak and ring artifacts. This work presents two digital image processing solutions to fill in these gaps when considering the specific case of synchrotron radiation x-ray parallel beam phase contrast CT. While not discussed with experimental data, other CT modalities, such as spectral, cone beam and other geometries might benefit from the presented approaches.
Naumovich, S S; Naumovich, S A; Goncharenko, V G
2015-01-01
The objective of the present study was the development and clinical testing of a three-dimensional (3D) reconstruction method of teeth and a bone tissue of the jaw on the basis of CT images of the maxillofacial region. 3D reconstruction was performed using the specially designed original software based on watershed transformation. Computed tomograms in digital imaging and communications in medicine format obtained on multispiral CT and CBCT scanners were used for creation of 3D models of teeth and the jaws. The processing algorithm is realized in the stepwise threshold image segmentation with the placement of markers in the mode of a multiplanar projection in areas relating to the teeth and a bone tissue. The developed software initially creates coarse 3D models of the entire dentition and the jaw. Then, certain procedures specify the model of the jaw and cut the dentition into separate teeth. The proper selection of the segmentation threshold is very important for CBCT images having a low contrast and high noise level. The developed semi-automatic algorithm of multispiral and cone beam computed tomogram processing allows 3D models of teeth to be created separating them from a bone tissue of the jaws. The software is easy to install in a dentist's workplace, has an intuitive interface and takes little time in processing. The obtained 3D models can be used for solving a wide range of scientific and clinical tasks.
A review of automated image understanding within 3D baggage computed tomography security screening.
Mouton, Andre; Breckon, Toby P
2015-01-01
Baggage inspection is the principal safeguard against the transportation of prohibited and potentially dangerous materials at airport security checkpoints. Although traditionally performed by 2D X-ray based scanning, increasingly stringent security regulations have led to a growing demand for more advanced imaging technologies. The role of X-ray Computed Tomography is thus rapidly expanding beyond the traditional materials-based detection of explosives. The development of computer vision and image processing techniques for the automated understanding of 3D baggage-CT imagery is however, complicated by poor image resolutions, image clutter and high levels of noise and artefacts. We discuss the recent and most pertinent advancements and identify topics for future research within the challenging domain of automated image understanding for baggage security screening CT.
Slice-thickness evaluation in CT and MRI: an alternative computerised procedure.
Acri, G; Tripepi, M G; Causa, F; Testagrossa, B; Novario, R; Vermiglio, G
2012-04-01
The efficient use of computed tomography (CT) and magnetic resonance imaging (MRI) equipment necessitates establishing adequate quality-control (QC) procedures. In particular, the accuracy of slice thickness (ST) requires scan exploration of phantoms containing test objects (plane, cone or spiral). To simplify such procedures, a novel phantom and a computerised LabView-based procedure have been devised, enabling determination of full width at half maximum (FWHM) in real time. The phantom consists of a polymethyl methacrylate (PMMA) box, diagonally crossed by a PMMA septum dividing the box into two sections. The phantom images were acquired and processed using the LabView-based procedure. The LabView (LV) results were compared with those obtained by processing the same phantom images with commercial software, and the Fisher exact test (F test) was conducted on the resulting data sets to validate the proposed methodology. In all cases, there was no statistically significant variation between the two different procedures and the LV procedure, which can therefore be proposed as a valuable alternative to other commonly used procedures and be reliably used on any CT and MRI scanner.
Minami, Yasunori; Kitai, Satoshi; Kudo, Masatoshi
2012-03-01
Virtual CT sonography using magnetic navigation provides cross sectional images of CT volume data corresponding to the angle of the transducer in the magnetic field in real-time. The purpose of this study was to clarify the value of this virtual CT sonography for treatment response of radiofrequency ablation for hepatocellular carcinoma. Sixty-one patients with 88 HCCs measuring 0.5-1.3 cm (mean±SD, 1.0±0.3 cm) were treated by radiofrequency ablation. For early treatment response, dynamic CT was performed 1-5 days (median, 2 days). We compared early treatment response between axial CT images and multi-angle CT images using virtual CT sonography. Residual tumor stains on axial CT images and multi-angle CT images were detected in 11.4% (10/88) and 13.6% (12/88) after the first session of RFA, respectively (P=0.65). Two patients were diagnosed as showing hyperemia enhancement after the initial radiofrequency ablation on axial CT images and showed local tumor progression shortly because of unnoticed residual tumors. Only virtual CT sonography with magnetic navigation retrospectively showed the residual tumor as circular enhancement. In safety margin analysis, 10 patients were excluded because of residual tumors. The safety margin more than 5 mm by virtual CT sonographic images and transverse CT images were determined in 71.8% (56/78) and 82.1% (64/78), respectively (P=0.13). The safety margin should be overestimated on axial CT images in 8 nodules. Virtual CT sonography with magnetic navigation was useful in evaluating the treatment response of radiofrequency ablation therapy for hepatocellular carcinoma. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Wenz, Holger; Maros, Máté E; Meyer, Mathias; Gawlitza, Joshua; Förster, Alex; Haubenreisser, Holger; Kurth, Stefan; Schoenberg, Stefan O; Groden, Christoph; Henzler, Thomas
2016-01-01
To prospectively evaluate image quality and organ-specific-radiation dose of spiral cranial CT (cCT) combined with automated tube current modulation (ATCM) and iterative image reconstruction (IR) in comparison to sequential tilted cCT reconstructed with filtered back projection (FBP) without ATCM. 31 patients with a previous performed tilted non-contrast enhanced sequential cCT aquisition on a 4-slice CT system with only FBP reconstruction and no ATCM were prospectively enrolled in this study for a clinical indicated cCT scan. All spiral cCT examinations were performed on a 3rd generation dual-source CT system using ATCM in z-axis direction. Images were reconstructed using both, FBP and IR (level 1-5). A Monte-Carlo-simulation-based analysis was used to compare organ-specific-radiation dose. Subjective image quality for various anatomic structures was evaluated using a 4-point Likert-scale and objective image quality was evaluated by comparing signal-to-noise ratios (SNR). Spiral cCT led to a significantly lower (p < 0.05) organ-specific-radiation dose in all targets including eye lense. Subjective image quality of spiral cCT datasets with an IR reconstruction level 5 was rated significantly higher compared to the sequential cCT acquisitions (p < 0.0001). Consecutive mean SNR was significantly higher in all spiral datasets (FBP, IR 1-5) when compared to sequential cCT with a mean SNR improvement of 44.77% (p < 0.0001). Spiral cCT combined with ATCM and IR allows for significant-radiation dose reduction including a reduce eye lens organ-dose when compared to a tilted sequential cCT while improving subjective and objective image quality.
Automated segmentation of murine lung tumors in x-ray micro-CT images
NASA Astrophysics Data System (ADS)
Swee, Joshua K. Y.; Sheridan, Clare; de Bruin, Elza; Downward, Julian; Lassailly, Francois; Pizarro, Luis
2014-03-01
Recent years have seen micro-CT emerge as a means of providing imaging analysis in pre-clinical study, with in-vivo micro-CT having been shown to be particularly applicable to the examination of murine lung tumors. Despite this, existing studies have involved substantial human intervention during the image analysis process, with the use of fully-automated aids found to be almost non-existent. We present a new approach to automate the segmentation of murine lung tumors designed specifically for in-vivo micro-CT-based pre-clinical lung cancer studies that addresses the specific requirements of such study, as well as the limitations human-centric segmentation approaches experience when applied to such micro-CT data. Our approach consists of three distinct stages, and begins by utilizing edge enhancing and vessel enhancing non-linear anisotropic diffusion filters to extract anatomy masks (lung/vessel structure) in a pre-processing stage. Initial candidate detection is then performed through ROI reduction utilizing obtained masks and a two-step automated segmentation approach that aims to extract all disconnected objects within the ROI, and consists of Otsu thresholding, mathematical morphology and marker-driven watershed. False positive reduction is finally performed on initial candidates through random-forest-driven classification using the shape, intensity, and spatial features of candidates. We provide validation of our approach using data from an associated lung cancer study, showing favorable results both in terms of detection (sensitivity=86%, specificity=89%) and structural recovery (Dice Similarity=0.88) when compared against manual specialist annotation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Moriya, S; National Cancer Center, Kashiwa, Chiba; Tachibana, H
Purpose: Daily CT-based three-dimensional image-guided and adaptive (CTIGRT-ART) proton therapy system was designed and developed. We also evaluated the effectiveness of the CTIGRT-ART. Methods: Retrospective analysis was performed in three lung cancer patients: Proton treatment planning was performed using CT image datasets acquired by Toshiba Aquilion ONE. Planning target volume and surrounding organs were contoured by a well-trained radiation oncologist. Dose distribution was optimized using 180-deg. and 270-deg. two fields in passive scattering proton therapy. Well commissioned Simplified Monte Carlo algorithm was used as dose calculation engine. Daily consecutive CT image datasets was acquired by an in-room CT (Toshiba Aquilionmore » LB). In our in-house program, two image registrations for bone and tumor were performed to shift the isocenter using treatment CT image dataset. Subsequently, dose recalculation was performed after the shift of the isocenter. When the dose distribution after the tumor registration exhibits change of dosimetric parameter of CTV D90% compared to the initial plan, an additional process of was performed that the range shifter thickness was optimized. Dose distribution with CTV D90% for the bone registration, the tumor registration only and adaptive plan with the tumor registration was compared to the initial plan. Results: In the bone registration, tumor dose coverage was decreased by 16% on average (Maximum: 56%). The tumor registration shows better coverage than the bone registration, however the coverage was also decreased by 9% (Maximum: 22%) The adaptive plan shows similar dose coverage of the tumor (Average: 2%, Maximum: 7%). Conclusion: There is a high possibility that only image registration for bone and tumor may reduce tumor coverage. Thus, our proposed methodology of image guidance and adaptive planning using the range adaptation after tumor registration would be effective for proton therapy. This research is partially supported by Japan Agency for Medical Research and Development (AMED).« less
Li, Kai; Su, Zhongzhen; Xu, Erjiao; Huang, Qiannan; Zeng, Qingjing; Zheng, Rongqin
2017-01-19
To assess the accuracy of contrast-enhanced ultrasound (CEUS)-CT/MR image fusion in evaluating the radiofrequency ablative margin (AM) of hepatocellular carcinoma (HCC) based on a custom-made phantom model and in HCC patients. Twenty-four phantoms were randomly divided into a complete ablation group (n = 6) and an incomplete ablation group (n = 18). After radiofrequency ablation (RFA), the AM was evaluated using ultrasound (US)-CT image fusion, and the results were compared with the AM results that were directly measured in a gross specimen. CEUS-CT/MR image fusion and CT-CT / MR-MR image fusion were used to evaluate the AM in 37 tumors from 33 HCC patients who underwent RFA. The sensitivity, specificity, and accuracy of US-CT image fusion for evaluating AM in the phantom model were 93.8, 85.7 and 91.3%, respectively. The maximal thicknesses of the residual AM were 3.5 ± 2.0 mm and 3.2 ± 2.0 mm in the US-CT image fusion and gross specimen, respectively. No significant difference was observed between the US-CT image fusion and direct measurements of the AM of HCC. In the clinical study, the success rate of the AM evaluation was 100% for both CEUS-CT/MR and CT-CT/MR-MR, and the duration was 8.5 ± 2.8 min (range: 4-12 min) and 13.5 ± 4.5 min (range: 8-16 min) for CEUS-CT/MR and CT-CT/MR-MR, respectively. The sensitivity, specificity, and accuracy of CEUS-CT/MR imaging for evaluating the AM were 100.0, 80.0, and 90.0%, respectively. A phantom model composed of carrageenan gel and additives was suitable for the evaluation of HCC AM. CEUS-CT/MR image fusion can be used to evaluate HCC AM with high accuracy.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ushizima, Daniela M.; Bianchi, Andrea G. C.; DeBianchi, Christina
We introduce a computational analysis workflow to access properties of solid objects using nondestructive imaging techniques that rely on X-ray imaging. The goal is to process and quantify structures from material science sample cross sections. The algorithms can differentiate the porous media (high density material) from the void (background, low density media) using a Boolean classifier, so that we can extract features, such as volume, surface area, granularity spectrum, porosity, among others. Our workflow, Quant-CT, leverages several algorithms from ImageJ, such as statistical region merging and 3D object counter. It also includes schemes for bilateral filtering that use a 3Dmore » kernel, for parallel processing of sub-stacks, and for handling over-segmentation using histogram similarities. The Quant-CT supports fast user interaction, providing the ability for the user to train the algorithm via subsamples to feed its core algorithms with automated parameterization. Quant-CT plugin is currently available for testing by personnel at the Advanced Light Source and Earth Sciences Divisions and Energy Frontier Research Center (EFRC), LBNL, as part of their research on porous materials. The goal is to understand the processes in fluid-rock systems for the geologic sequestration of CO2, and to develop technology for the safe storage of CO2 in deep subsurface rock formations. We describe our implementation, and demonstrate our plugin on porous material images. This paper targets end-users, with relevant information for developers to extend its current capabilities.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Krishnan, Kalpagam; Liu, Jeff; Kohli, Kirpal
Purpose: Fusion of electrical impedance tomography (EIT) with computed tomography (CT) can be useful as a clinical tool for providing additional physiological information about tissues, but requires suitable fusion algorithms and validation procedures. This work explores the feasibility of fusing EIT and CT images using an algorithm for coregistration. The imaging performance is validated through feature space assessment on phantom contrast targets. Methods: EIT data were acquired by scanning a phantom using a circuit, configured for injecting current through 16 electrodes, placed around the phantom. A conductivity image of the phantom was obtained from the data using electrical impedance andmore » diffuse optical tomography reconstruction software (EIDORS). A CT image of the phantom was also acquired. The EIT and CT images were fused using a region of interest (ROI) coregistration fusion algorithm. Phantom imaging experiments were carried out on objects of different contrasts, sizes, and positions. The conductive medium of the phantoms was made of a tissue-mimicking bolus material that is routinely used in clinical radiation therapy settings. To validate the imaging performance in detecting different contrasts, the ROI of the phantom was filled with distilled water and normal saline. Spatially separated cylindrical objects of different sizes were used for validating the imaging performance in multiple target detection. Analyses of the CT, EIT and the EIT/CT phantom images were carried out based on the variations of contrast, correlation, energy, and homogeneity, using a gray level co-occurrence matrix (GLCM). A reference image of the phantom was simulated using EIDORS, and the performances of the CT and EIT imaging systems were evaluated and compared against the performance of the EIT/CT system using various feature metrics, detectability, and structural similarity index measures. Results: In detecting distilled and normal saline water in bolus medium, EIT as a stand-alone imaging system showed contrast discrimination of 47%, while the CT imaging system showed a discrimination of only 1.5%. The structural similarity index measure showed a drop of 24% with EIT imaging compared to CT imaging. The average detectability measure for CT imaging was found to be 2.375 ± 0.19 before fusion. After complementing with EIT information, the detectability measure increased to 11.06 ± 2.04. Based on the feature metrics, the functional imaging quality of CT and EIT were found to be 2.29% and 86%, respectively, before fusion. Structural imaging quality was found to be 66% for CT and 16% for EIT. After fusion, functional imaging quality improved in CT imaging from 2.29% to 42% and the structural imaging quality of EIT imaging changed from 16% to 66%. The improvement in image quality was also observed in detecting objects of different sizes. Conclusions: The authors found a significant improvement in the contrast detectability performance of CT imaging when complemented with functional imaging information from EIT. Along with the feature assessment metrics, the concept of complementing CT with EIT imaging can lead to an EIT/CT imaging modality which might fully utilize the functional imaging abilities of EIT imaging, thereby enhancing the quality of care in the areas of cancer diagnosis and radiotherapy treatment planning.« less
An image-domain, contrast material extraction method for Dual-Energy CT
Lambert, Jack W.; Sun, Yuxin; Gould, Robert G.; Ohliger, Michael A.; Li, Zhixi; Yeh, Benjamin M.
2016-01-01
Objectives Conventional material decomposition techniques for dual-energy CT (DECT) assume mass or volume conservation, where the CT number of each voxel is fully assigned to predefined materials. We present an image-domain contrast material extraction process (CMEP) method that preferentially extracts contrast-producing materials while leaving the remaining image intact. Materials and Methods Image processing freeware (Fiji) is used to perform consecutive arithmetic operations on a dual-energy ratio map to generate masks, which are then applied to the original images to generate material-specific images. First, a low-energy image is divided by a high-energy image to generate a ratio map. The ratio map is then split into material-specific masks. Ratio intervals known to correspond to particular materials (e.g. iodine, calcium) are assigned a multiplier of 1, while ratio values in between these intervals are assigned linear gradients from 0 to 1. The masks are then multiplied by an original CT image to produce material-specific images. The method was tested quantitatively at Dual-Source (DSCT) and Rapid kVp-Switching CT (RSCT) with phantoms using pure and mixed formulations of tungsten, calcium and iodine. Errors were evaluated by comparing the known material concentrations with those derived from the CMEP material-specific images. Further qualitative evaluation was performed in vivo at RSCT with a rabbit model using identical CMEP parameters to the phantom. Orally administered tungsten, vascularly administered iodine, and skeletal calcium were used as the three contrast materials. Results All five material combinations; tungsten, iodine and calcium, and mixtures of tungsten-calcium and iodine-calcium, showed distinct dual-energy ratios, largely independent of material concentration at both DSCT and RSCT. The CMEP was successful in both phantoms and in vivo. For pure contrast materials in the phantom, the maximum error between the known and CMEP-derived material concentrations was 0.9 mg/mL, 24.9 mg/mL and 0.4 mg/mL for iodine, calcium and tungsten respectively. Mixtures of iodine and calcium showed the highest discrepancies, which reflected the sensitivity of iodine to the image-type chosen for the extraction of the final material-specific image. The rabbit model was able to clearly show the three extracted material phases, vascular iodine, oral tungsten and skeletal calcium. Some skeletal calcium was misassigned to the extracted iodine image, however this did not impede the depiction of the vasculature. Conclusions The CMEP is a straightforward, image domain approach to extract material signal at dual-energy CT. It has particular value for separation of experimental high-Z contrast elements from conventional iodine contrast or calcium, even when the exact attenuation coefficient profiles of desired contrast materials may be unknown. The CMEP is readily implemented in the image-domain within freeware, and can be adapted for use with images from multiple vendors. PMID:27875338
Sibille, Louis; Chambert, Benjamin; Alonso, Sandrine; Barrau, Corinne; D'Estanque, Emmanuel; Al Tabaa, Yassine; Collombier, Laurent; Demattei, Christophe; Kotzki, Pierre-Olivier; Boudousq, Vincent
2016-07-01
The purpose of this study was to compare a routine bone SPECT/CT protocol using CT reconstructed with filtered backprojection (FBP) with an optimized protocol using low-dose CT images reconstructed with adaptive statistical iterative reconstruction (ASiR). In this prospective study, enrolled patients underwent bone SPECT/CT, with 1 SPECT acquisition followed by 2 randomized CT acquisitions: FBP CT (FBP; noise index, 25) and ASiR CT (70% ASiR; noise index, 40). The image quality of both attenuation-corrected SPECT and CT images was visually (5-point Likert scale, 2 interpreters) and quantitatively (contrast ratio [CR] and signal-to-noise ratio [SNR]) estimated. The CT dose index volume, dose-length product, and effective dose were compared. Seventy-five patients were enrolled in the study. Quantitative attenuation-corrected SPECT evaluation showed no inferiority for contrast ratio and SNR issued from FBP CT or ASiR CT (respectively, 13.41 ± 7.83 vs. 13.45 ± 7.99 and 2.33 ± 0.83 vs. 2.32 ± 0.84). Qualitative image analysis showed no difference between attenuation-corrected SPECT images issued from FBP CT or ASiR CT for both interpreters (respectively, 3.5 ± 0.6 vs. 3.5 ± 0.6 and 3.6 ± 0.5 vs. 3.6 ± 0.5). Quantitative CT evaluation showed no inferiority for SNR between FBP and ASiR CT images (respectively, 0.93 ± 0.16 and 1.07 ± 0.17). Qualitative image analysis showed no quality difference between FBP and ASiR CT images for both interpreters (respectively, 3.8 ± 0.5 vs. 3.6 ± 0.5 and 4.0 ± 0.1 vs. 4.0 ± 0.2). Mean CT dose index volume, dose-length product, and effective dose for ASiR CT (3.0 ± 2.0 mGy, 148 ± 85 mGy⋅cm, and 2.2 ± 1.3 mSv) were significantly lower than for FBP CT (8.5 ± 3.7 mGy, 365 ± 160 mGy⋅cm, and 5.5 ± 2.4 mSv). The use of 70% ASiR blending in bone SPECT/CT can reduce the CT radiation dose by 60%, with no sacrifice in attenuation-corrected SPECT and CT image quality, compared with the conventional protocol using FBP CT reconstruction technique. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.
Erovic, Boban M; Chan, Harley H L; Daly, Michael J; Pothier, David D; Yu, Eugene; Coulson, Chris; Lai, Philip; Irish, Jonathan C
2014-01-01
Conventional computed tomography (CT) imaging is the standard imaging technique for temporal bone diseases, whereas cone-beam CT (CBCT) imaging is a very fast imaging tool with a significant less radiation dose compared with conventional CT. We hypothesize that a system for intraoperative cone-beam CT provides comparable image quality to diagnostic CT for identifying temporal bone anatomical landmarks in cadaveric specimens. Cross-sectional study. University tertiary care facility. Twenty cadaveric temporal bones were affixed into a head phantom and scanned with both a prototype cone-beam CT C-arm and multislice helical CT. Imaging performance was evaluated by 3 otologic surgeons and 1 head and neck radiologist. Participants were presented images in a randomized order and completed landmark identification questionnaires covering 21 structures. CBCT and multislice CT have comparable performance in identifying temporal structures. Three otologic surgeons indicated that CBCT provided statistically equivalent performance for 19 of 21 landmarks, with CBCT superior to CT for the chorda tympani and inferior for the crura of the stapes. Subgroup analysis showed that CBCT performed superiorly for temporal bone structures compared with CT. The radiologist rated CBCT and CT as statistically equivalent for 18 of 21 landmarks, with CT superior to CBCT for the crura of stapes, chorda tympani, and sigmoid sinus. CBCT provides comparable image quality to conventional CT for temporal bone anatomical sites in cadaveric specimens. Clinical applications of low-dose CBCT imaging in surgical planning, intraoperative guidance, and postoperative assessment are promising but require further investigation.
Shi, Bowen; Lin, Huimin; Zhang, Miao; Lu, Wei; Qu, Ying; Zhang, Huan
2018-01-22
Gastric cancer remains fourth in cancer incidence worldwide with a five-year survival of only 20%-30%. Peritoneal metastasis is the most frequent type of metastasis that accompanies unresectable gastric cancer and is a definitive determinant of prognosis. Preventing and controlling the development of peritoneal metastasis could play a role in helping to prolong the survival of gastric cancer patients. A non-invasive and efficient imaging technique will help us to identify the invasion and metastasis process of peritoneal metastasis and to monitor the changes in tumor nodules in response to treatments. This will enable us to obtain an accurate description of the development process and molecular mechanisms of gastric cancer. We have recently described experiment using dual energy CT (DECT) and positron emission tomography/computed tomography (PET/CT) platforms for the detection and monitoring of gastric tumor metastasis in nude mice models. We have shown that weekly continuous monitoring with DECT and PET/CT can identify dynamic changes in peritoneal metastasis. The sFRP1-overexpression in gastric cancer mice models showed positive radiological performance, a higher FDG uptake and increasing enhancement, and the SUVmax (standardized uptake value) of nodules demonstrated an obvious alteration trend in response to targeted therapy of TGF-β1 inhibitor. In this article, we described the detailed non-invasive imaging procedures to conduct more complex research on gastric cancer peritoneal metastasis using animal models and provided representative imaging results. The use of non-invasive imaging techniques should enable us to better understand the mechanisms of tumorigenesis, monitor tumor growth, and evaluate the effect of therapeutic interventions for gastric cancer.
X-ray cargo container inspection system with few-view projection imaging
NASA Astrophysics Data System (ADS)
Duan, Xinhui; Cheng, Jianping; Zhang, Li; Xing, Yuxiang; Chen, Zhiqiang; Zhao, Ziran
2009-01-01
An X-ray cargo inspection system with few-view projection imaging is developed for detecting contraband in air containers. This paper describes this developing inspection system, including its configuration and the process of inspection using three imaging modalities: digital radiography (DR), few view imaging and computed tomography (CT). The few-view imaging can provide 3D images with much faster scanning speed than CT and do great help to quickly locate suspicious cargo in a container. An algorithm to reconstruct tomographic images from severely sparse projection data of few-view imaging is discussed. A cooperative work manner of the three modalities is presented to make the inspection more convenient and effective. Numerous experiments of performance tests and modality comparison are performed on our system for inspecting air containers. Results demonstrate the effectiveness of our methods and implementation of few-view imaging in practical inspection systems.
Female pelvic synthetic CT generation based on joint intensity and shape analysis
NASA Astrophysics Data System (ADS)
Liu, Lianli; Jolly, Shruti; Cao, Yue; Vineberg, Karen; Fessler, Jeffrey A.; Balter, James M.
2017-04-01
Using MRI for radiotherapy treatment planning and image guidance is appealing as it provides superior soft tissue information over CT scans and avoids possible systematic errors introduced by aligning MR to CT images. This study presents a method that generates Synthetic CT (MRCT) volumes by performing probabilistic tissue classification of voxels from MRI data using a single imaging sequence (T1 Dixon). The intensity overlap between different tissues on MR images, a major challenge for voxel-based MRCT generation methods, is addressed by adding bone shape information to an intensity-based classification scheme. A simple pelvic bone shape model, built from principal component analysis of pelvis shape from 30 CT image volumes, is fitted to the MR volumes. The shape model generates a rough bone mask that excludes air and covers bone along with some surrounding soft tissues. Air regions are identified and masked out from the tissue classification process by intensity thresholding outside the bone mask. A regularization term is added to the fuzzy c-means classification scheme that constrains voxels outside the bone mask from being assigned memberships in the bone class. MRCT image volumes are generated by multiplying the probability of each voxel being represented in each class with assigned attenuation values of the corresponding class and summing the result across all classes. The MRCT images presented intensity distributions similar to CT images with a mean absolute error of 13.7 HU for muscle, 15.9 HU for fat, 49.1 HU for intra-pelvic soft tissues, 129.1 HU for marrow and 274.4 HU for bony tissues across 9 patients. Volumetric modulated arc therapy (VMAT) plans were optimized using MRCT-derived electron densities, and doses were recalculated using corresponding CT-derived density grids. Dose differences to planning target volumes were small with mean/standard deviation of 0.21/0.42 Gy for D0.5cc and 0.29/0.33 Gy for D99%. The results demonstrate the accuracy of the method and its potential in supporting MRI only radiotherapy treatment planning.
Cheon, Byunggyu; Moon, Sohyeon; Park, Seungjo; Lee, Sang-Kwon; Hong, Sunghwa; Cho, Hyun; Choi, Jihye
2016-11-01
OBJECTIVE To evaluate contrast agents for their ability to improve visualization of the colon wall and lumen during CT and ultrasonography. ANIMALS 10 healthy adult Beagles. PROCEDURES Food was withheld from dogs for 36 hours, after which dogs consumed 250 mL of polyethylene glycol solution. Dogs were then anesthetized, a contrast agent (tap water, diluted barium, or air; order randomly assigned) was administered rectally, iodine contrast medium (880 mg of I/kg) was administered IV, and CT and ultrasonography of the colon were performed. After a 1-week washout period, this process was repeated with a different contrast agent until all agents had been evaluated. Two investigators reviewed the CT and ultrasonographic images for colon wall thickness, conspicuity, artifacts, wall layering, and degree of lumen dilation at 4 sites. RESULTS Thickness of the colon wall was greatest in CT and ultrasonographic images with water used as contrast agent, followed by barium and then air. The CT images obtained after water administration had a smooth appearance that outlined the colonic mucosa and had the highest score of the 3 contrast agents for wall conspicuity. Although no substantial artifacts related to any of the contrast agents were identified on CT images, barium- and gas-induced shadowing and reverberation artifacts hindered wall evaluation during ultrasonography. For ultrasonography, the degree of conspicuity was highest with barium in the near-field wall and with water in the far-field wall. In contrast to CT, ultrasonography could be used to distinguish wall layering, and the mucosal and muscular layers were distinct with all contrast agents. CONCLUSIONS AND CLINICAL RELEVANCE Use of water as a contrast agent for both CT and ultrasonography of the colon in dogs compensated for each imaging modality's disadvantages and could be beneficial in the diagnosis of colon disease.
Kim, Bum-Joon; Hong, Ki-Sun; Park, Kyung-Jae; Park, Dong-Hyuk; Chung, Yong-Gu
2012-01-01
Objective The prefabrication of customized cranioplastic implants has been introduced to overcome the difficulties of intra-operative implant molding. The authors present a new technique, which consists of the prefabrication of implant molds using three-dimensional (3D) printers and polymethyl-methacrylate (PMMA) casting. Methods A total of 16 patients with large skull defects (>100 cm2) underwent cranioplasty between November 2009 and April 2011. For unilateral cranial defects, 3D images of the skull were obtained from preoperative axial 1-mm spiral computed tomography (CT) scans. The image of the implant was generated by a digital subtraction mirror-imaging process using the normal side of the cranium as a model. For bilateral cranial defects, precraniectomy routine spiral CT scan data were merged with postcraniectomy 3D CT images following a smoothing process. Prefabrication of the mold was performed by the 3D printer. Intraoperatively, the PMMA implant was created with the prefabricated mold, and fit into the cranial defect. Results The median operation time was 184.36±26.07 minutes. Postoperative CT scans showed excellent restoration of the symmetrical contours and curvature of the cranium in all cases. The median follow-up period was 23 months (range, 14-28 months). Postoperative infection was developed in one case (6.2%) who had an open wound defect previously. Conclusion Customized cranioplasty PMMA implants using 3D printer may be a useful technique for the reconstruction of various cranial defects. PMID:23346326
Solid models for CT/MR image display: accuracy and utility in surgical planning
NASA Astrophysics Data System (ADS)
Mankovich, Nicholas J.; Yue, Alvin; Ammirati, Mario; Kioumehr, Farhad; Turner, Scott
1991-05-01
Medical imaging can now take wider advantage of Computer-Aided-Manufacturing through rapid prototyping technologies (RPT) such as stereolithography, laser sintering, and laminated object manufacturing to directly produce solid models of patient anatomy from processed CT and MR images. While conventional surgical planning relies on consultation with the radiologist combined with direct reading and measurement of CT and MR studies, 3-D surface and volumetric display workstations are providing a more easily interpretable view of patient anatomy. RPT can provide the surgeon with a life size model of patient anatomy constructed layer by layer with full internal detail. Although this life-size anatomic model is more easily understandable by the surgeon, its accuracy and true surgical utility remain untested. We have developed a prototype image processing and model fabrication system based on stereolithography, which provides the neurosurgeon with models of the skull base. Parallel comparison of the model with the original thresholded CT data and with a CRT displayed surface rendering showed that both have an accuracy of 99.6 percent. Because of the ease of exact voxel localization on the model, its precision was high with the standard deviation of measurement of 0.71 percent. The measurements on the surface rendered display proved more difficult to exactly locate and yielded a standard deviation of 2.37 percent. This paper presents our accuracy study and discussed ways of assessing the quality of neurosurgical plans when 3-D models a made available as planning tools.
NASA Astrophysics Data System (ADS)
Gong, Ren Hui; Jenkins, Brad; Sze, Raymond W.; Yaniv, Ziv
2014-03-01
The skills required for obtaining informative x-ray fluoroscopy images are currently acquired while trainees provide clinical care. As a consequence, trainees and patients are exposed to higher doses of radiation. Use of simulation has the potential to reduce this radiation exposure by enabling trainees to improve their skills in a safe environment prior to treating patients. We describe a low cost, high fidelity, fluoroscopy simulation system. Our system enables operators to practice their skills using the clinical device and simulated x-rays of a virtual patient. The patient is represented using a set of temporal Computed Tomography (CT) images, corresponding to the underlying dynamic processes. Simulated x-ray images, digitally reconstructed radiographs (DRRs), are generated from the CTs using ray-casting with customizable machine specific imaging parameters. To establish the spatial relationship between the CT and the fluoroscopy device, the CT is virtually attached to a patient phantom and a web camera is used to track the phantom's pose. The camera is mounted on the fluoroscope's intensifier and the relationship between it and the x-ray source is obtained via calibration. To control image acquisition the operator moves the fluoroscope as in normal operation mode. Control of zoom, collimation and image save is done using a keypad mounted alongside the device's control panel. Implementation is based on the Image-Guided Surgery Toolkit (IGSTK), and the use of the graphics processing unit (GPU) for accelerated image generation. Our system was evaluated by 11 clinicians and was found to be sufficiently realistic for training purposes.
X-ray CT analysis of pore structure in sand
NASA Astrophysics Data System (ADS)
Mukunoki, Toshifumi; Miyata, Yoshihisa; Mikami, Kazuaki; Shiota, Erika
2016-06-01
The development of microfocused X-ray computed tomography (CT) devices enables digital imaging analysis at the pore scale. The applications of these devices are diverse in soil mechanics, geotechnical and geoenvironmental engineering, petroleum engineering, and agricultural engineering. In particular, the imaging of the pore space in porous media has contributed to numerical simulations for single-phase and multiphase flows or contaminant transport through the pore structure as three-dimensional image data. These obtained results are affected by the pore diameter; therefore, it is necessary to verify the image preprocessing for the image analysis and to validate the pore diameters obtained from the CT image data. Moreover, it is meaningful to produce the physical parameters in a representative element volume (REV) and significant to define the dimension of the REV. This paper describes the underlying method of image processing and analysis and discusses the physical properties of Toyoura sand for the verification of the image analysis based on the definition of the REV. On the basis of the obtained verification results, a pore-diameter analysis can be conducted and validated by a comparison with the experimental work and image analysis. The pore diameter is deduced from Young-Laplace's law and a water retention test for the drainage process. The results from previous study and perforated-pore diameter originally proposed in this study, called the voxel-percolation method (VPM), are compared in this paper. In addition, the limitations of the REV, the definition of the pore diameter, and the effectiveness of the VPM for an assessment of the pore diameter are discussed.
Physics of cardiac imaging with multiple-row detector CT.
Mahesh, Mahadevappa; Cody, Dianna D
2007-01-01
Cardiac imaging with multiple-row detector computed tomography (CT) has become possible due to rapid advances in CT technologies. Images with high temporal and spatial resolution can be obtained with multiple-row detector CT scanners; however, the radiation dose associated with cardiac imaging is high. Understanding the physics of cardiac imaging with multiple-row detector CT scanners allows optimization of cardiac CT protocols in terms of image quality and radiation dose. Knowledge of the trade-offs between various scan parameters that affect image quality--such as temporal resolution, spatial resolution, and pitch--is the key to optimized cardiac CT protocols, which can minimize the radiation risks associated with these studies. Factors affecting temporal resolution include gantry rotation time, acquisition mode, and reconstruction method; factors affecting spatial resolution include detector size and reconstruction interval. Cardiac CT has the potential to become a reliable tool for noninvasive diagnosis and prevention of cardiac and coronary artery disease. (c) RSNA, 2007.
Gee, Carole T.
2013-01-01
• Premise of the study: As an alternative to conventional thin-sectioning, which destroys fossil material, high-resolution X-ray computed tomography (also called microtomography or microCT) integrated with scientific visualization, three-dimensional (3D) image segmentation, size analysis, and computer animation is explored as a nondestructive method of imaging the internal anatomy of 150-million-year-old conifer seed cones from the Late Jurassic Morrison Formation, USA, and of recent and other fossil cones. • Methods: MicroCT was carried out on cones using a General Electric phoenix v|tome|x s 240D, and resulting projections were processed with visualization software to produce image stacks of serial single sections for two-dimensional (2D) visualization, 3D segmented reconstructions with targeted structures in color, and computer animations. • Results: If preserved in differing densities, microCT produced images of internal fossil tissues that showed important characters such as seed phyllotaxy or number of seeds per cone scale. Color segmentation of deeply embedded seeds highlighted the arrangement of seeds in spirals. MicroCT of recent cones was even more effective. • Conclusions: This is the first paper on microCT integrated with 3D segmentation and computer animation applied to silicified seed cones, which resulted in excellent 2D serial sections and segmented 3D reconstructions, revealing features requisite to cone identification and understanding of strobilus construction. PMID:25202495
An iterative reconstruction method for high-pitch helical luggage CT
NASA Astrophysics Data System (ADS)
Xue, Hui; Zhang, Li; Chen, Zhiqiang; Jin, Xin
2012-10-01
X-ray luggage CT is widely used in airports and railway stations for the purpose of detecting contrabands and dangerous goods that may be potential threaten to public safety, playing an important role in homeland security. An X-ray luggage CT is usually in a helical trajectory with a high pitch for achieving a high passing speed of the luggage. The disadvantage of high pitch is that conventional filtered back-projection (FBP) requires a very large slice thickness, leading to bad axial resolution and helical artifacts. Especially when severe data inconsistencies are present in the z-direction, like the ends of a scanning object, the partial volume effect leads to inaccuracy value and may cause a wrong identification. In this paper, an iterative reconstruction method is developed to improve the image quality and accuracy for a large-spacing multi-detector high-pitch helical luggage CT system. In this method, the slice thickness is set to be much smaller than the pitch. Each slice involves projection data collected in a rather small angular range, being an ill-conditioned limited-angle problem. Firstly a low-resolution reconstruction is employed to obtain images, which are used as prior images in the following process. Then iterative reconstruction is performed to obtain high-resolution images. This method enables a high volume coverage speed and a thin reconstruction slice for the helical luggage CT. We validate this method with data collected in a commercial X-ray luggage CT.
CT artifact recognition for the nuclear technologist.
Popilock, Robert; Sandrasagaren, Kumar; Harris, Lowell; Kaser, Keith A
2008-06-01
The goal of this article is to make the PET/CT and SPECT/CT operator aware of common artifacts found in CT. In diagnostic imaging, the ability to render an accurate diagnosis requires the technologist to take steps to optimize image quality and recognize when image quality has been compromised-that is, when there is an image artifact. One way these artifacts occur is through the inability of the CT linear attenuation image to precisely represent the linear attenuation map of a 2-dimensional section through the body. The reasons for this inability are multifold. First, CT is subject to the laws of x-ray quantum physics resulting in noise in all CT images. Moreover, all current CT x-ray systems generate a spectrum of energies. Also, CT scanners use detectors of finite dimension, as are the x-ray focal spots; reconstruct images from a finite number of samples distributed over a finite number of views; and acquire the data for each reconstruction over a finite period.
Dose calculation with respiration-averaged CT processed from cine CT without a respiratory surrogate
DOE Office of Scientific and Technical Information (OSTI.GOV)
Riegel, Adam C.; Ahmad, Moiz; Sun Xiaojun
2008-12-15
Dose calculation for thoracic radiotherapy is commonly performed on a free-breathing helical CT despite artifacts caused by respiratory motion. Four-dimensional computed tomography (4D-CT) is one method to incorporate motion information into the treatment planning process. Some centers now use the respiration-averaged CT (RACT), the pixel-by-pixel average of the ten phases of 4D-CT, for dose calculation. This method, while sparing the tedious task of 4D dose calculation, still requires 4D-CT technology. The authors have recently developed a means to reconstruct RACT directly from unsorted cine CT data from which 4D-CT is formed, bypassing the need for a respiratory surrogate. Using RACTmore » from cine CT for dose calculation may be a means to incorporate motion information into dose calculation without performing 4D-CT. The purpose of this study was to determine if RACT from cine CT can be substituted for RACT from 4D-CT for the purposes of dose calculation, and if increasing the cine duration can decrease differences between the dose distributions. Cine CT data and corresponding 4D-CT simulations for 23 patients with at least two breathing cycles per cine duration were retrieved. RACT was generated four ways: First from ten phases of 4D-CT, second, from 1 breathing cycle of images, third, from 1.5 breathing cycles of images, and fourth, from 2 breathing cycles of images. The clinical treatment plan was transferred to each RACT and dose was recalculated. Dose planes were exported at orthogonal planes through the isocenter (coronal, sagittal, and transverse orientations). The resulting dose distributions were compared using the gamma ({gamma}) index within the planning target volume (PTV). Failure criteria were set to 2%/1 mm. A follow-up study with 50 additional lung cancer patients was performed to increase sample size. The same dose recalculation and analysis was performed. In the primary patient group, 22 of 23 patients had 100% of points within the PTV pass {gamma} criteria. The average maximum and mean {gamma} indices were very low (well below 1), indicating good agreement between dose distributions. Increasing the cine duration generally increased the dose agreement. In the follow-up study, 49 of 50 patients had 100% of points within the PTV pass the {gamma} criteria. The average maximum and mean {gamma} indices were again well below 1, indicating good agreement. Dose calculation on RACT from cine CT is negligibly different from dose calculation on RACT from 4D-CT. Differences can be decreased further by increasing the cine duration of the cine CT scan.« less
Soukup, Jason W.; Drees, Randi; Koenig, Lisa J.; Snyder, Christopher J.; Hetzel, Scott; Miles, Chanda R.; Schwarz, Tobias
2016-01-01
Summary The objective of this blinded study was to validate the use of cone beam computed tomography (CT) for imaging of the canine maxillary dentoalveolar structures by comparing its diagnostic image quality with that of 64-multidetector row CT. Sagittal slices of a tooth-bearing segment of the maxilla of a commercially purchased dog skull embedded in methyl methacrylate were obtained along a line parallel with the dental arch using a commercial histology diamond saw. The slice of tooth-bearing bone that best depicted the dentoalveolar structures was chosen and photographed. The maxilla segment was imaged with cone beam CT and 64-multidetector row CT. Four blinded evaluators compared the cone beam CT and 64-multidetector row CT images and image quality was scored as it related to the anatomy of dentoalveolar structures. Trabecular bone, enamel, dentin, pulp cavity, periodontal ligament space, and lamina dura were scored. In addition, a score depicting the evaluators overall impression of the image was recorded. Images acquired with cone beam CT were found to be significantly superior in image quality to images acquired with 64-multidetector row CT overall, and in all scored categories. In our study setting, cone beam CT was found to be a valid and clinically superior imaging modality for the canine maxillary dentoalveolar structures when compared to 64-multidetector row CT. PMID:26415384
A convolutional neural network for intracranial hemorrhage detection in non-contrast CT
NASA Astrophysics Data System (ADS)
Patel, Ajay; Manniesing, Rashindra
2018-02-01
The assessment of the presence of intracranial hemorrhage is a crucial step in the work-up of patients requiring emergency care. Fast and accurate detection of intracranial hemorrhage can aid treating physicians by not only expediting and guiding diagnosis, but also supporting choices for secondary imaging, treatment and intervention. However, the automatic detection of intracranial hemorrhage is complicated by the variation in appearance on non-contrast CT images as a result of differences in etiology and location. We propose a method using a convolutional neural network (CNN) for the automatic detection of intracranial hemorrhage. The method is trained on a dataset comprised of cerebral CT studies for which the presence of hemorrhage has been labeled for each axial slice. A separate test dataset of 20 images is used for quantitative evaluation and shows a sensitivity of 0.87, specificity of 0.97 and accuracy of 0.95. The average processing time for a single three-dimensional (3D) CT volume was 2.7 seconds. The proposed method is capable of fast and automated detection of intracranial hemorrhages in non-contrast CT without being limited to a specific subtype of pathology.
SU-F-J-156: The Feasibility of MR-Only IMRT Planning for Prostate Anatomy
DOE Office of Scientific and Technical Information (OSTI.GOV)
Vaitheeswaran, R; Sivaramakrishnan, KR; Kumar, Prashant
Purpose: For prostate anatomy, previous investigations have shown that simulated CT (sCT) generated from MR images can be used for accurate dose computation. In this study, we demonstrate the feasibility of MR-only IMRT planning for prostate case. Methods: Regular CT (rCT) and MR images of the same patient were acquired for prostate anatomy. Regions-of-interest (ROIs) i.e. target and risk structures are delineated on the rCT. A simulated CT (sCT) is generated from the MR image using the method described by Schadewaldt N et al. Their work establishes the clinical acceptability of dose calculation results on the sCT when compared tomore » rCT. rCT and sCT are rigidly registered to ensure proper alignment between the two images. rCT and sCT are overlaid on each other and slice-wise visual inspection confirms excellent agreement between the two images. ROIs on the rCT are copied over to sCT. Philips AutoPlanning solution is used for generating treatment plans. The same treatment technique protocol (plan parameters and clinical goals) is used to generate AutoPlan-rCT and AutoPlan-sCT respectively for rCT and and sCT. DVH comparison on ROIs and slice-wise evaluation of dose is performed between AutoPlan-rCT and AutoPlan-sCT. Delivery parameters i.e. beam and corresponding segments from the AutoPlan-sCT are copied over to rCT and dose is computed to get AutoPlan-sCT-on-rCT. Results: Plan evaluation is done based on Dose Volume Histogram (DVH) of ROIs and manual slice-wise inspection of dose distribution. Both AutoPlan-rCT and AutoPlan-sCT provide a clinically acceptable plan. Also, AutoPlan-sCT-on-rCT shows excellent agreement with AutoPlan-sCT. Conclusion: The study demonstrates that it is feasible to do IMRT planning on the simulated CT image obtained from MR image for prostate anatomy. The research is supported by Philips India Ltd.« less
Synthetic Hounsfield units from spectral CT data
NASA Astrophysics Data System (ADS)
Bornefalk, Hans
2012-04-01
Beam-hardening-free synthetic images with absolute CT numbers that radiologists are used to can be constructed from spectral CT data by forming ‘dichromatic’ images after basis decomposition. The CT numbers are accurate for all tissues and the method does not require additional reconstruction. This method prevents radiologists from having to relearn new rules-of-thumb regarding absolute CT numbers for various organs and conditions as conventional CT is replaced by spectral CT. Displaying the synthetic Hounsfield unit images side-by-side with images reconstructed for optimal detectability for a certain task can ease the transition from conventional to spectral CT.
Application of fluence field modulation to proton computed tomography for proton therapy imaging.
Dedes, G; De Angelis, L; Rit, S; Hansen, D; Belka, C; Bashkirov, V; Johnson, R P; Coutrakon, G; Schubert, K E; Schulte, R W; Parodi, K; Landry, G
2017-07-12
This simulation study presents the application of fluence field modulated computed tomography, initially developed for x-ray CT, to proton computed tomography (pCT). By using pencil beam (PB) scanning, fluence modulated pCT (FMpCT) may achieve variable image quality in a pCT image and imaging dose reduction. Three virtual phantoms, a uniform cylinder and two patients, were studied using Monte Carlo simulations of an ideal list-mode pCT scanner. Regions of interest (ROI) were selected for high image quality and only PBs intercepting them preserved full fluence (FF). Image quality was investigated in terms of accuracy (mean) and noise (standard deviation) of the reconstructed proton relative stopping power compared to reference values. Dose calculation accuracy on FMpCT images was evaluated in terms of dose volume histograms (DVH), range difference (RD) for beam-eye-view (BEV) dose profiles and gamma evaluation. Pseudo FMpCT scans were created from broad beam experimental data acquired with a list-mode pCT prototype. FMpCT noise in ROIs was equivalent to FF images and accuracy better than -1.3%(-0.7%) by using 1% of FF for the cylinder (patients). Integral imaging dose reduction of 37% and 56% was achieved for the two patients for that level of modulation. Corresponding DVHs from proton dose calculation on FMpCT images agreed to those from reference images and 96% of BEV profiles had RD below 2 mm, compared to only 1% for uniform 1% of FF. Gamma pass rates (2%, 2 mm) were 98% for FMpCT while for uniform 1% of FF they were as low as 59%. Applying FMpCT to preliminary experimental data showed that low noise levels and accuracy could be preserved in a ROI, down to 30% modulation. We have shown, using both virtual and experimental pCT scans, that FMpCT is potentially feasible and may allow a means of imaging dose reduction for a pCT scanner operating in PB scanning mode. This may be of particular importance to proton therapy given the low integral dose found outside the target.
Temporal resolution and motion artifacts in single-source and dual-source cardiac CT.
Schöndube, Harald; Allmendinger, Thomas; Stierstorfer, Karl; Bruder, Herbert; Flohr, Thomas
2013-03-01
The temporal resolution of a given image in cardiac computed tomography (CT) has so far mostly been determined from the amount of CT data employed for the reconstruction of that image. The purpose of this paper is to examine the applicability of such measures to the newly introduced modality of dual-source CT as well as to methods aiming to provide improved temporal resolution by means of an advanced image reconstruction algorithm. To provide a solid base for the examinations described in this paper, an extensive review of temporal resolution in conventional single-source CT is given first. Two different measures for assessing temporal resolution with respect to the amount of data involved are introduced, namely, either taking the full width at half maximum of the respective data weighting function (FWHM-TR) or the total width of the weighting function (total TR) as a base of the assessment. Image reconstruction using both a direct fan-beam filtered backprojection with Parker weighting as well as using a parallel-beam rebinning step are considered. The theory of assessing temporal resolution by means of the data involved is then extended to dual-source CT. Finally, three different advanced iterative reconstruction methods that all use the same input data are compared with respect to the resulting motion artifact level. For brevity and simplicity, the examinations are limited to two-dimensional data acquisition and reconstruction. However, all results and conclusions presented in this paper are also directly applicable to both circular and helical cone-beam CT. While the concept of total TR can directly be applied to dual-source CT, the definition of the FWHM of a weighting function needs to be slightly extended to be applicable to this modality. The three different advanced iterative reconstruction methods examined in this paper result in significantly different images with respect to their motion artifact level, despite exactly the same amount of data being used in the reconstruction process. The concept of assessing temporal resolution by means of the data employed for reconstruction can nicely be extended from single-source to dual-source CT. However, for advanced (possibly nonlinear iterative) reconstruction algorithms the examined approach fails to deliver accurate results. New methods and measures to assess the temporal resolution of CT images need to be developed to be able to accurately compare the performance of such algorithms.
Baek, Jihye; Huh, Jangyoung; Kim, Myungsoo; Hyun An, So; Oh, Yoonjin; Kim, DongYoung; Chung, Kwangzoo; Cho, Sungho; Lee, Rena
2013-02-01
To evaluate the accuracy of measuring volumes using three-dimensional ultrasound (3D US), and to verify the feasibility of the replacement of CT-MR fusion images with CT-3D US in radiotherapy treatment planning. Phantoms, consisting of water, contrast agent, and agarose, were manufactured. The volume was measured using 3D US, CT, and MR devices. A CT-3D US and MR-3D US image fusion software was developed using the Insight Toolkit library in order to acquire three-dimensional fusion images. The quality of the image fusion was evaluated using metric value and fusion images. Volume measurement, using 3D US, shows a 2.8 ± 1.5% error, 4.4 ± 3.0% error for CT, and 3.1 ± 2.0% error for MR. The results imply that volume measurement using the 3D US devices has a similar accuracy level to that of CT and MR. Three-dimensional image fusion of CT-3D US and MR-3D US was successfully performed using phantom images. Moreover, MR-3D US image fusion was performed using human bladder images. 3D US could be used in the volume measurement of human bladders and prostates. CT-3D US image fusion could be used in monitoring the target position in each fraction of external beam radiation therapy. Moreover, the feasibility of replacing the CT-MR image fusion to the CT-3D US in radiotherapy treatment planning was verified.
Han, Guanghui; Liu, Xiabi; Han, Feifei; Santika, I Nyoman Tenaya; Zhao, Yanfeng; Zhao, Xinming; Zhou, Chunwu
2015-02-01
Lung computed tomography (CT) imaging signs play important roles in the diagnosis of lung diseases. In this paper, we review the significance of CT imaging signs in disease diagnosis and determine the inclusion criterion of CT scans and CT imaging signs of our database. We develop the software of abnormal regions annotation and design the storage scheme of CT images and annotation data. Then, we present a publicly available database of lung CT imaging signs, called LISS for short, which contains 271 CT scans and 677 abnormal regions in them. The 677 abnormal regions are divided into nine categories of common CT imaging signs of lung disease (CISLs). The ground truth of these CISLs regions and the corresponding categories are provided. Furthermore, to make the database publicly available, all private data in CT scans are eliminated or replaced with provisioned values. The main characteristic of our LISS database is that it is developed from a new perspective of CT imaging signs of lung diseases instead of commonly considered lung nodules. Thus, it is promising to apply to computer-aided detection and diagnosis research and medical education.
Dreizin, David; Nam, Arthur J; Hirsch, Jeffrey; Bernstein, Mark P
2018-06-20
This article reviews the conceptual framework, available evidence, and practical considerations pertaining to nascent and emerging advances in patient-centered CT-imaging and CT-guided surgery for maxillofacial trauma. These include cinematic rendering-a novel method for advanced 3D visualization, incorporation of quantitative CT imaging into the assessment of orbital fractures, low-dose CT imaging protocols made possible with contemporary scanners and reconstruction techniques, the rapidly growing use of cone-beam CT, virtual fracture reduction with design software for surgical pre-planning, the use of 3D printing for fabricating models and implants, and new avenues in CT-guided computer-aided surgery.
Diagnostic Performance of Ultrafast Brain MRI for Evaluation of Abusive Head Trauma.
Kralik, S F; Yasrebi, M; Supakul, N; Lin, C; Netter, L G; Hicks, R A; Hibbard, R A; Ackerman, L L; Harris, M L; Ho, C Y
2017-04-01
MR imaging with sedation is commonly used to detect intracranial traumatic pathology in the pediatric population. Our purpose was to compare nonsedated ultrafast MR imaging, noncontrast head CT, and standard MR imaging for the detection of intracranial trauma in patients with potential abusive head trauma. A prospective study was performed in 24 pediatric patients who were evaluated for potential abusive head trauma. All patients received noncontrast head CT, ultrafast brain MR imaging without sedation, and standard MR imaging with general anesthesia or an immobilizer, sequentially. Two pediatric neuroradiologists independently reviewed each technique blinded to other modalities for intracranial trauma. We performed interreader agreement and consensus interpretation for standard MR imaging as the criterion standard. Diagnostic accuracy was calculated for ultrafast MR imaging, noncontrast head CT, and combined ultrafast MR imaging and noncontrast head CT. Interreader agreement was moderate for ultrafast MR imaging (κ = 0.42), substantial for noncontrast head CT (κ = 0.63), and nearly perfect for standard MR imaging (κ = 0.86). Forty-two percent of patients had discrepancies between ultrafast MR imaging and standard MR imaging, which included detection of subarachnoid hemorrhage and subdural hemorrhage. Sensitivity, specificity, and positive and negative predictive values were obtained for any traumatic pathology for each examination: ultrafast MR imaging (50%, 100%, 100%, 31%), noncontrast head CT (25%, 100%, 100%, 21%), and a combination of ultrafast MR imaging and noncontrast head CT (60%, 100%, 100%, 33%). Ultrafast MR imaging was more sensitive than noncontrast head CT for the detection of intraparenchymal hemorrhage ( P = .03), and the combination of ultrafast MR imaging and noncontrast head CT was more sensitive than noncontrast head CT alone for intracranial trauma ( P = .02). In abusive head trauma, ultrafast MR imaging, even combined with noncontrast head CT, demonstrated low sensitivity compared with standard MR imaging for intracranial traumatic pathology, which may limit its utility in this patient population. © 2017 by American Journal of Neuroradiology.
NASA Astrophysics Data System (ADS)
Han, Hao; Zhang, Hao; Wei, Xinzhou; Moore, William; Liang, Zhengrong
2016-03-01
In this paper, we proposed a low-dose computed tomography (LdCT) image reconstruction method with the help of prior knowledge learning from previous high-quality or normal-dose CT (NdCT) scans. The well-established statistical penalized weighted least squares (PWLS) algorithm was adopted for image reconstruction, where the penalty term was formulated by a texture-based Gaussian Markov random field (gMRF) model. The NdCT scan was firstly segmented into different tissue types by a feature vector quantization (FVQ) approach. Then for each tissue type, a set of tissue-specific coefficients for the gMRF penalty was statistically learnt from the NdCT image via multiple-linear regression analysis. We also proposed a scheme to adaptively select the order of gMRF model for coefficients prediction. The tissue-specific gMRF patterns learnt from the NdCT image were finally used to form an adaptive MRF penalty for the PWLS reconstruction of LdCT image. The proposed texture-adaptive PWLS image reconstruction algorithm was shown to be more effective to preserve image textures than the conventional PWLS image reconstruction algorithm, and we further demonstrated the gain of high-order MRF modeling for texture-preserved LdCT PWLS image reconstruction.
Towards quantitative PET/MRI: a review of MR-based attenuation correction techniques.
Hofmann, Matthias; Pichler, Bernd; Schölkopf, Bernhard; Beyer, Thomas
2009-03-01
Positron emission tomography (PET) is a fully quantitative technology for imaging metabolic pathways and dynamic processes in vivo. Attenuation correction of raw PET data is a prerequisite for quantification and is typically based on separate transmission measurements. In PET/CT attenuation correction, however, is performed routinely based on the available CT transmission data. Recently, combined PET/magnetic resonance (MR) has been proposed as a viable alternative to PET/CT. Current concepts of PET/MRI do not include CT-like transmission sources and, therefore, alternative methods of PET attenuation correction must be found. This article reviews existing approaches to MR-based attenuation correction (MR-AC). Most groups have proposed MR-AC algorithms for brain PET studies and more recently also for torso PET/MR imaging. Most MR-AC strategies require the use of complementary MR and transmission images, or morphology templates generated from transmission images. We review and discuss these algorithms and point out challenges for using MR-AC in clinical routine. MR-AC is work-in-progress with potentially promising results from a template-based approach applicable to both brain and torso imaging. While efforts are ongoing in making clinically viable MR-AC fully automatic, further studies are required to realize the potential benefits of MR-based motion compensation and partial volume correction of the PET data.
Acar, Buket; Kamburoğlu, Kıvanç; Tatar, İlkan; Arıkan, Volkan; Çelik, Hakan Hamdi; Yüksel, Selcen; Özen, Tuncer
2015-12-01
This study was performed to compare the accuracy of micro-computed tomography (CT) and cone-beam computed tomography (CBCT) in detecting accessory canals in primary molars. Forty-one extracted human primary first and second molars were embedded in wax blocks and scanned using micro-CT and CBCT. After the images were taken, the samples were processed using a clearing technique and examined under a stereomicroscope in order to establish the gold standard for this study. The specimens were classified into three groups: maxillary molars, mandibular molars with three canals, and mandibular molars with four canals. Differences between the gold standard and the observations made using the imaging methods were calculated using Spearman's rho correlation coefficient test. The presence of accessory canals in micro-CT images of maxillary and mandibular root canals showed a statistically significant correlation with the stereomicroscopic images used as a gold standard. No statistically significant correlation was found between the CBCT findings and the stereomicroscopic images. Although micro-CT is not suitable for clinical use, it provides more detailed information about minor anatomical structures. However, CBCT is convenient for clinical use but may not be capable of adequately analyzing the internal anatomy of primary teeth.
High energy x-ray phase contrast CT using glancing-angle grating interferometers
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sarapata, A., E-mail: adrian.sarapata@tum.de; Stayman, J. W.; Siewerdsen, J. H.
Purpose: The authors present initial progress toward a clinically compatible x-ray phase contrast CT system, using glancing-angle x-ray grating interferometry to provide high contrast soft tissue images at estimated by computer simulation dose levels comparable to conventional absorption based CT. Methods: DPC-CT scans of a joint phantom and of soft tissues were performed in order to answer several important questions from a clinical setup point of view. A comparison between high and low fringe visibility systems is presented. The standard phase stepping method was compared with sliding window interlaced scanning. Using estimated dose values obtained with a Monte-Carlo code themore » authors studied the dependence of the phase image contrast on exposure time and dose. Results: Using a glancing angle interferometer at high x-ray energy (∼45 keV mean value) in combination with a conventional x-ray tube the authors achieved fringe visibility values of nearly 50%, never reported before. High fringe visibility is shown to be an indispensable parameter for a potential clinical scanner. Sliding window interlaced scanning proved to have higher SNRs and CNRs in a region of interest and to also be a crucial part of a low dose CT system. DPC-CT images of a soft tissue phantom at exposures in the range typical for absorption based CT of musculoskeletal extremities were obtained. Assuming a human knee as the CT target, good soft tissue phase contrast could be obtained at an estimated absorbed dose level around 8 mGy, similar to conventional CT. Conclusions: DPC-CT with glancing-angle interferometers provides improved soft tissue contrast over absorption CT even at clinically compatible dose levels (estimated by a Monte-Carlo computer simulation). Further steps in image processing, data reconstruction, and spectral matching could make the technique fully clinically compatible. Nevertheless, due to its increased scan time and complexity the technique should be thought of not as replacing, but as complimentary to conventional CT, to be used in specific applications.« less
In vivo 3D PIXE-micron-CT imaging of Drosophila melanogaster using a contrast agent
NASA Astrophysics Data System (ADS)
Matsuyama, Shigeo; Hamada, Naoki; Ishii, Keizo; Nozawa, Yuichiro; Ohkura, Satoru; Terakawa, Atsuki; Hatori, Yoshinobu; Fujiki, Kota; Fujiwara, Mitsuhiro; Toyama, Sho
2015-04-01
In this study, we developed a three-dimensional (3D) computed tomography (CT) in vivo imaging system for imaging small insects with micrometer resolution. The 3D CT imaging system, referred to as 3D PIXE-micron-CT (PIXEμCT), uses characteristic X-rays produced by ion microbeam bombardment of a metal target. PIXEμCT was used to observe the body organs and internal structure of a living Drosophila melanogaster. Although the organs of the thorax were clearly imaged, the digestive organs in the abdominal cavity could not be clearly discerned initially, with the exception of the rectum and the Malpighian tubule. To enhance the abdominal images, a barium sulfate powder radiocontrast agent was added. For the first time, 3D images of the ventriculus of a living D. melanogaster were obtained. Our results showed that PIXEμCT can provide in vivo 3D-CT images that reflect correctly the structure of individual living organs, which is expected to be very useful in biological research.
Development Of A Flash X-Ray Scanner For Stereoradiography And CT
NASA Astrophysics Data System (ADS)
Endorf, Robert J.; DiBianca, Frank A.; Fritsch, Daniel S.; Liu, Wen-Ching; Burns, Charles B.
1989-05-01
We are developing a flash x-ray scanner for stereoradiography and CT which will be able to produce a stereoradiograph in 30 to 70 ns and a complete CT scan in one microsecond. This type of imaging device will be valuable in studying high speed processes, high acceleration, and traumatic events. We have built a two channel flash x-ray system capable of producing stereo radiographs with stereo angles of from 15 to 165 degrees. The dynamic and static Miff 's for the flash x-ray system were measured and compared with similar MIT's measured for a conventional medical x-ray system. We have written and tested a stereo reconstruction algorithm to determine three dimensional space points from corresponding points in the two stereo images. To demonstrate the ability of the system to image traumatic events, a radiograph was obtained of a bone undergoing a fracture. The effects of accelerations of up to 600 g were examined on radiographs taken of human kidney tissue samples in a rapidly rotating centrifuge. Feasibility studies of CT reconstruction have been performed by making simulated Cr images of various phantoms for larger flash x-ray systems of from 8 to 29 flash x-ray tubes.
Variation of canine vertebral bone architecture in computed tomography
Cheon, Byunggyu; Park, Seungjo; Lee, Sang-kwon; Park, Jun-Gyu; Cho, Kyoung-Oh
2018-01-01
Focal vertebral bone density changes were assessed in vertebral computed tomography (CT) images obtained from clinically healthy dogs without diseases that affect bone density. The number, location, and density of lesions were determined. A total of 429 vertebral CT images from 20 dogs were reviewed, and 99 focal vertebral changes were identified in 14 dogs. Focal vertebral bone density changes were mainly found in thoracic vertebrae (29.6%) as hyperattenuating (86.9%) lesions. All focal vertebral changes were observed at the vertebral body, except for a single hyperattenuating change in one thoracic transverse process. Among the hyperattenuating changes, multifocal changes (53.5%) were more common than single changes (46.5%). Most of the hypoattenuating changes were single (92.3%). Eight dogs, 40% of the 20 dogs in the study and 61.6% of the 13 dogs showing focal vertebral changes in the thoracic vertebra, had hyperattenuating changes at the 7th or 8th thoracic vertebra. Our results indicate that focal changes in vertebral bone density are commonly identified on vertebral CT images in healthy dogs, and these changes should be taken into consideration on interpretation of CT images. PMID:28693309
Schad, L R; Boesecke, R; Schlegel, W; Hartmann, G H; Sturm, V; Strauss, L G; Lorenz, W J
1987-01-01
A treatment planning system for stereotactic convergent beam irradiation of deeply localized brain tumors is reported. The treatment technique consists of several moving field irradiations in noncoplanar planes at a linear accelerator facility. Using collimated narrow beams, a high concentration of dose within small volumes with a dose gradient of 10-15%/mm was obtained. The dose calculation was based on geometrical information of multiplanar CT or magnetic resonance (MR) imaging data. The patient's head was fixed in a stereotactic localization system, which is usable at CT, MR, and positron emission tomography (PET) installations. Special computer programs for correction of the geometrical MR distortions allowed a precise correlation of the different imaging modalities. The therapist can use combinations of CT, MR, and PET data for defining target volume. For instance, the superior soft tissue contrast of MR coupled with the metabolic features of PET may be a useful addition in the radiation treatment planning process. Furthermore, other features such as calculated dose distribution to critical structures can also be transferred from one set of imaging data to another and can be displayed as three-dimensional shaded structures.
Neural network fusion: a novel CT-MR aortic aneurysm image segmentation method
NASA Astrophysics Data System (ADS)
Wang, Duo; Zhang, Rui; Zhu, Jin; Teng, Zhongzhao; Huang, Yuan; Spiga, Filippo; Du, Michael Hong-Fei; Gillard, Jonathan H.; Lu, Qingsheng; Liò, Pietro
2018-03-01
Medical imaging examination on patients usually involves more than one imaging modalities, such as Computed Tomography (CT), Magnetic Resonance (MR) and Positron Emission Tomography(PET) imaging. Multimodal imaging allows examiners to benefit from the advantage of each modalities. For example, for Abdominal Aortic Aneurysm, CT imaging shows calcium deposits in the aorta clearly while MR imaging distinguishes thrombus and soft tissues better.1 Analysing and segmenting both CT and MR images to combine the results will greatly help radiologists and doctors to treat the disease. In this work, we present methods on using deep neural network models to perform such multi-modal medical image segmentation. As CT image and MR image of the abdominal area cannot be well registered due to non-affine deformations, a naive approach is to train CT and MR segmentation network separately. However, such approach is time-consuming and resource-inefficient. We propose a new approach to fuse the high-level part of the CT and MR network together, hypothesizing that neurons recognizing the high level concepts of Aortic Aneurysm can be shared across multiple modalities. Such network is able to be trained end-to-end with non-registered CT and MR image using shorter training time. Moreover network fusion allows a shared representation of Aorta in both CT and MR images to be learnt. Through experiments we discovered that for parts of Aorta showing similar aneurysm conditions, their neural presentations in neural network has shorter distances. Such distances on the feature level is helpful for registering CT and MR image.
Thoracic cavity definition for 3D PET/CT analysis and visualization.
Cheirsilp, Ronnarit; Bascom, Rebecca; Allen, Thomas W; Higgins, William E
2015-07-01
X-ray computed tomography (CT) and positron emission tomography (PET) serve as the standard imaging modalities for lung-cancer management. CT gives anatomical details on diagnostic regions of interest (ROIs), while PET gives highly specific functional information. During the lung-cancer management process, a patient receives a co-registered whole-body PET/CT scan pair and a dedicated high-resolution chest CT scan. With these data, multimodal PET/CT ROI information can be gleaned to facilitate disease management. Effective image segmentation of the thoracic cavity, however, is needed to focus attention on the central chest. We present an automatic method for thoracic cavity segmentation from 3D CT scans. We then demonstrate how the method facilitates 3D ROI localization and visualization in patient multimodal imaging studies. Our segmentation method draws upon digital topological and morphological operations, active-contour analysis, and key organ landmarks. Using a large patient database, the method showed high agreement to ground-truth regions, with a mean coverage=99.2% and leakage=0.52%. Furthermore, it enabled extremely fast computation. For PET/CT lesion analysis, the segmentation method reduced ROI search space by 97.7% for a whole-body scan, or nearly 3 times greater than that achieved by a lung mask. Despite this reduction, we achieved 100% true-positive ROI detection, while also reducing the false-positive (FP) detection rate by >5 times over that achieved with a lung mask. Finally, the method greatly improved PET/CT visualization by eliminating false PET-avid obscurations arising from the heart, bones, and liver. In particular, PET MIP views and fused PET/CT renderings depicted unprecedented clarity of the lesions and neighboring anatomical structures truly relevant to lung-cancer assessment. Copyright © 2015 Elsevier Ltd. All rights reserved.
Thoracic Cavity Definition for 3D PET/CT Analysis and Visualization
Cheirsilp, Ronnarit; Bascom, Rebecca; Allen, Thomas W.; Higgins, William E.
2015-01-01
X-ray computed tomography (CT) and positron emission tomography (PET) serve as the standard imaging modalities for lung-cancer management. CT gives anatomical detail on diagnostic regions of interest (ROIs), while PET gives highly specific functional information. During the lung-cancer management process, a patient receives a co-registered whole-body PET/CT scan pair and a dedicated high-resolution chest CT scan. With these data, multimodal PET/CT ROI information can be gleaned to facilitate disease management. Effective image segmentation of the thoracic cavity, however, is needed to focus attention on the central chest. We present an automatic method for thoracic cavity segmentation from 3D CT scans. We then demonstrate how the method facilitates 3D ROI localization and visualization in patient multimodal imaging studies. Our segmentation method draws upon digital topological and morphological operations, active-contour analysis, and key organ landmarks. Using a large patient database, the method showed high agreement to ground-truth regions, with a mean coverage = 99.2% and leakage = 0.52%. Furthermore, it enabled extremely fast computation. For PET/CT lesion analysis, the segmentation method reduced ROI search space by 97.7% for a whole-body scan, or nearly 3 times greater than that achieved by a lung mask. Despite this reduction, we achieved 100% true-positive ROI detection, while also reducing the false-positive (FP) detection rate by >5 times over that achieved with a lung mask. Finally, the method greatly improved PET/CT visualization by eliminating false PET-avid obscurations arising from the heart, bones, and liver. In particular, PET MIP views and fused PET/CT renderings depicted unprecedented clarity of the lesions and neighboring anatomical structures truly relevant to lung-cancer assessment. PMID:25957746
Application of oral contrast media in coregistered positron emission tomography-CT.
Dizendorf, Elena V; Treyer, Valerie; Von Schulthess, Gustav K; Hany, Thomas F
2002-08-01
Coregistration of positron emission tomography (PET) and CT images results in significantly improved localization of abnormal FDG uptake compared with PET images alone. For delineation of intestinal structures, application of oral contrast media is a standard procedure in CT. The influence of oral contrast agents in PET imaging using CT data for attenuation correction was evaluated in a comparative study on an in-line PET-CT system. Sixty patients referred for PET-CT were evaluated in two groups. One group of 30 patients received oral Gastrografin 45 min before data acquisition. The second group received no contrast medium. PET images were reconstructed, using CT data for attenuation correction. Image analysis was performed by two reviewers in consensus, using a 4-point scale comparing FDG-uptake in the gastrointestinal tract in PET images of both groups. Furthermore, correlation of FDG uptake and localization of contrast media in the intestinal tract in CT images were determined. No significant difference in FDG uptake in PET images in all regions of the gastrointestinal tract except the ascending colon was seen in both groups. No correlation was found in the location of increased FDG uptake and contrast media in the CT images. An oral contrast agent can be used for coregistered PET-CT without the introduction of artifacts in PET.
Lattanzi, J P; Fein, D A; McNeeley, S W; Shaer, A H; Movsas, B; Hanks, G E
1997-01-01
We describe our initial experience with the AcQSim (Picker International, St. David, PA) computed tomography-magnetic resonance imaging (CT-MRI) fusion software in eight patients with intracranial lesions. MRI data are electronically integrated into the CT-based treatment planning system. Since MRI is superior to CT in identifying intracranial abnormalities, we evaluated the precision and feasibility of this new localization method. Patients initially underwent CT simulation from C2 to the most superior portion of the scalp. T2 and post-contrast T1-weighted MRI of this area was then performed. Patient positioning was duplicated utilizing a head cup and bridge of nose to forehead angle measurements. First, a gross tumor volume (GTV) was identified utilizing the CT (CT/GTV). The CT and MRI scans were subsequently fused utilizing a point pair matching method and a second GTV (CT-MRI/GTV) was contoured with the aid of both studies. The fusion process was uncomplicated and completed in a timely manner. Volumetric analysis revealed the CT-MRI/GTV to be larger than the CT/GTV in all eight cases. The mean CT-MRI/GTV was 28.7 cm3 compared to 16.7 cm3 by CT alone. This translated into a 72% increase in the radiographic tumor volume by CT-MRI. A simulated dose-volume histogram in two patients revealed that marginal portions of the lesion, as identified by CT and MRI, were not included in the high dose treatment volume as contoured with the use of CT alone. Our initial experience with the fusion software demonstrated an improvement in tumor localization with this technique. Based on these patients the use of CT alone for treatment planning purposes in central nervous system (CNS) lesions is inadequate and would result in an unacceptable rate of marginal misses. The importation of MRI data into three-dimensional treatment planning is therefore crucial to accurate tumor localization. The fusion process simplifies and improves precision of this task.
Park, Sang Cheol; Leader, Joseph Ken; Tan, Jun; Lee, Guee Sang; Kim, Soo Hyung; Na, In Seop; Zheng, Bin
2011-01-01
Objective this article presents a new computerized scheme that aims to accurately and robustly separate left and right lungs on CT examinations. Methods we developed and tested a method to separate the left and right lungs using sequential CT information and a guided dynamic programming algorithm using adaptively and automatically selected start point and end point with especially severe and multiple connections. Results the scheme successfully identified and separated all 827 connections on the total 4034 CT images in an independent testing dataset of CT examinations. The proposed scheme separated multiple connections regardless of their locations, and the guided dynamic programming algorithm reduced the computation time to approximately 4.6% in comparison with the traditional dynamic programming and avoided the permeation of the separation boundary into normal lung tissue. Conclusions The proposed method is able to robustly and accurately disconnect all connections between left and right lungs and the guided dynamic programming algorithm is able to remove redundant processing. PMID:21412104
NASA Astrophysics Data System (ADS)
Choi, Yong-Seok; Cho, Jae-Hwan; Namgung, Jang-Sun; Kim, Hyo-Jin; Yoon, Dae-Young; Lee, Han-Joo
2013-05-01
This study performed a comparative analysis of cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT), and mean time-to-peak (TTP) obtained by changing the region of interest's (ROI) anatomical positions, during CT brain perfusion. We acquired axial source images of perfusion CT from 20 patients undergoing CT perfusion exams due to brain trauma. Subsequently, the CBV, CBF, MTT, and TTP values were calculated through data-processing of the perfusion CT images. The color scales for the CBV, CBF, MTT, and TTP maps were obtained using the image data. Anterior cerebral artery (ACA) was taken as the standard ROI for the calculations of the perfusion values. Differences in the hemodynamic average values were compared in a quantitative analysis by placing ROI and the dividing axial images into proximal, middle, and distal segments anatomically. By performing the qualitative analysis using a blind test, we observed changes in the sensory characteristics by using the color scales of the CBV, CBF, and MTT maps in the proximal, middle, and distal segments. According to the qualitative analysis, no differences were found in CBV, CBF, MTT, and TTP values of the proximal, middle, and distal segments and no changes were detected in the color scales of the the CBV, CBF, MTT, and TTP maps in the proximal, middle, and distal segments. We anticipate that the results of the study will useful in assessing brain trauma patients using by perfusion imaging.
Rebouças Filho, Pedro Pedrosa; Cortez, Paulo César; da Silva Barros, Antônio C; C Albuquerque, Victor Hugo; R S Tavares, João Manuel
2017-01-01
The World Health Organization estimates that 300 million people have asthma, 210 million people have Chronic Obstructive Pulmonary Disease (COPD), and, according to WHO, COPD will become the third major cause of death worldwide in 2030. Computational Vision systems are commonly used in pulmonology to address the task of image segmentation, which is essential for accurate medical diagnoses. Segmentation defines the regions of the lungs in CT images of the thorax that must be further analyzed by the system or by a specialist physician. This work proposes a novel and powerful technique named 3D Adaptive Crisp Active Contour Method (3D ACACM) for the segmentation of CT lung images. The method starts with a sphere within the lung to be segmented that is deformed by forces acting on it towards the lung borders. This process is performed iteratively in order to minimize an energy function associated with the 3D deformable model used. In the experimental assessment, the 3D ACACM is compared against three approaches commonly used in this field: the automatic 3D Region Growing, the level-set algorithm based on coherent propagation and the semi-automatic segmentation by an expert using the 3D OsiriX toolbox. When applied to 40 CT scans of the chest the 3D ACACM had an average F-measure of 99.22%, revealing its superiority and competency to segment lungs in CT images. Copyright © 2016 Elsevier B.V. All rights reserved.
In vivo spatial correlation between (18)F-BPA and (18)F-FDG uptakes in head and neck cancer.
Kobayashi, Kazuma; Kurihara, Hiroaki; Watanabe, Yoshiaki; Murakami, Naoya; Inaba, Koji; Nakamura, Satoshi; Wakita, Akihisa; Okamoto, Hiroyuki; Umezawa, Rei; Takahashi, Kana; Igaki, Hiroshi; Ito, Yoshinori; Yoshimoto, Seiichi; Shigematsu, Naoyuki; Itami, Jun
2016-09-01
Borono-2-(18)F-fluoro-phenylalanine ((18)F-BPA) has been used to estimate the therapeutic effects of boron neutron capture therapy (BNCT), while (18)F-fluorodeoxyglucose ((18)F-FDG) is the most commonly used positron emission tomography (PET) radiopharmaceutical in a routine clinical use. The aim of the present study was to evaluate spatial correlation between (18)F-BPA and (18)F-FDG uptakes using a deformable image registration-based technique. Ten patients with head and neck cancer were recruited from January 2014 to December 2014. All patients underwent whole-body (18)F-BPA PET/computed tomography (CT) and (18)F-FDG PET/CT within a 2-week period. For each patient, (18)F-BPA PET/CT and (18)F-FDG PET/CT images were aligned based on a deformable image registration framework. The voxel-by-voxel spatial correlation of standardized uptake value (SUV) within the tumor was analyzed. Our image processing framework achieved accurate and validated registration results for each PET/CT image. In 9/10 patients, the spatial distribution of SUVs between (18)F-BPA and (18)F-FDG showed a significant, positive correlation in the tumor volume. Deformable image registration-based voxel-wise analysis demonstrated a spatial correlation between (18)F-BPA and (18)F-FDG uptakes in the head and neck cancer. A tumor sub-volume with a high (18)F-FDG uptake may predict high accumulation of (18)F-BPA. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
Automated extraction of radiation dose information for CT examinations.
Cook, Tessa S; Zimmerman, Stefan; Maidment, Andrew D A; Kim, Woojin; Boonn, William W
2010-11-01
Exposure to radiation as a result of medical imaging is currently in the spotlight, receiving attention from Congress as well as the lay press. Although scanner manufacturers are moving toward including effective dose information in the Digital Imaging and Communications in Medicine headers of imaging studies, there is a vast repository of retrospective CT data at every imaging center that stores dose information in an image-based dose sheet. As such, it is difficult for imaging centers to participate in the ACR's Dose Index Registry. The authors have designed an automated extraction system to query their PACS archive and parse CT examinations to extract the dose information stored in each dose sheet. First, an open-source optical character recognition program processes each dose sheet and converts the information to American Standard Code for Information Interchange (ASCII) text. Each text file is parsed, and radiation dose information is extracted and stored in a database which can be queried using an existing pathology and radiology enterprise search tool. Using this automated extraction pipeline, it is possible to perform dose analysis on the >800,000 CT examinations in the PACS archive and generate dose reports for all of these patients. It is also possible to more effectively educate technologists, radiologists, and referring physicians about exposure to radiation from CT by generating report cards for interpreted and performed studies. The automated extraction pipeline enables compliance with the ACR's reporting guidelines and greater awareness of radiation dose to patients, thus resulting in improved patient care and management. Copyright © 2010 American College of Radiology. Published by Elsevier Inc. All rights reserved.
Chen, Song; Li, Xuena; Chen, Meijie; Yin, Yafu; Li, Na; Li, Yaming
2016-10-01
This study is aimed to compare the diagnostic power of using quantitative analysis or visual analysis with single time point imaging (STPI) PET/CT and dual time point imaging (DTPI) PET/CT for the classification of solitary pulmonary nodules (SPN) lesions in granuloma-endemic regions. SPN patients who received early and delayed (18)F-FDG PET/CT at 60min and 180min post-injection were retrospectively reviewed. Diagnoses are confirmed by pathological results or follow-ups. Three quantitative metrics, early SUVmax, delayed SUVmax and retention index(the percentage changes between the early SUVmax and delayed SUVmax), were measured for each lesion. Three 5-point scale score was given by blinded interpretations performed by physicians based on STPI PET/CT images, DTPI PET/CT images and CT images, respectively. ROC analysis was performed on three quantitative metrics and three visual interpretation scores. One-hundred-forty-nine patients were retrospectively included. The areas under curve (AUC) of the ROC curves of early SUVmax, delayed SUVmax, RI, STPI PET/CT score, DTPI PET/CT score and CT score are 0.73, 0.74, 0.61, 0.77 0.75 and 0.76, respectively. There were no significant differences between the AUCs in visual interpretation of STPI PET/CT images and DTPI PET/CT images, nor in early SUVmax and delayed SUVmax. The differences of sensitivity, specificity and accuracy between STPI PET/CT and DTPI PET/CT were not significantly different in either quantitative analysis or visual interpretation. In granuloma-endemic regions, DTPI PET/CT did not offer significant improvement over STPI PET/CT in differentiating malignant SPNs in both quantitative analysis and visual interpretation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
An improved method for pancreas segmentation using SLIC and interactive region merging
NASA Astrophysics Data System (ADS)
Zhang, Liyuan; Yang, Huamin; Shi, Weili; Miao, Yu; Li, Qingliang; He, Fei; He, Wei; Li, Yanfang; Zhang, Huimao; Mori, Kensaku; Jiang, Zhengang
2017-03-01
Considering the weak edges in pancreas segmentation, this paper proposes a new solution which integrates more features of CT images by combining SLIC superpixels and interactive region merging. In the proposed method, Mahalanobis distance is first utilized in SLIC method to generate better superpixel images. By extracting five texture features and one gray feature, the similarity measure between two superpixels becomes more reliable in interactive region merging. Furthermore, object edge blocks are accurately addressed by re-segmentation merging process. Applying the proposed method to four cases of abdominal CT images, we segment pancreatic tissues to verify the feasibility and effectiveness. The experimental results show that the proposed method can make segmentation accuracy increase to 92% on average. This study will boost the application process of pancreas segmentation for computer-aided diagnosis system.
Interactive brain shift compensation using GPU based programming
NASA Astrophysics Data System (ADS)
van der Steen, Sander; Noordmans, Herke Jan; Verdaasdonk, Rudolf
2009-02-01
Processing large images files or real-time video streams requires intense computational power. Driven by the gaming industry, the processing power of graphic process units (GPUs) has increased significantly. With the pixel shader model 4.0 the GPU can be used for image processing 10x faster than the CPU. Dedicated software was developed to deform 3D MR and CT image sets for real-time brain shift correction during navigated neurosurgery using landmarks or cortical surface traces defined by the navigation pointer. Feedback was given using orthogonal slices and an interactively raytraced 3D brain image. GPU based programming enables real-time processing of high definition image datasets and various applications can be developed in medicine, optics and image sciences.
Zhang, Shu-xu; Han, Peng-hui; Zhang, Guo-qian; Wang, Rui-hao; Ge, Yong-bin; Ren, Zhi-gang; Li, Jian-sheng; Fu, Wen-hai
2014-01-01
Early detection of skull base invasion in nasopharyngeal carcinoma (NPC) is crucial for correct staging, assessing treatment response and contouring the tumor target in radiotherapy planning, as well as improving the patient's prognosis. To compare the diagnostic efficacy of single photon emission computed tomography/computed tomography (SPECT/CT) imaging, magnetic resonance imaging (MRI) and computed tomography (CT) for the detection of skull base invasion in NPC. Sixty untreated patients with histologically proven NPC underwent SPECT/CT imaging, contrast-enhanced MRI and CT. Of the 60 patients, 30 had skull base invasion confirmed by the final results of contrast-enhanced MRI, CT and six-month follow-up imaging (MRI and CT). The diagnostic efficacy of the three imaging modalities in detecting skull base invasion was evaluated. The rates of positive findings of skull base invasion for SPECT/CT, MRI and CT were 53.3%, 48.3% and 33.3%, respectively. The sensitivity, specificity and accuracy were 93.3%, 86.7% and 90.0% for SPECT/CT fusion imaging, 96.7%, 100.0% and 98.3% for contrast-enhanced MRI, and 66.7%, 100.0% and 83.3% for contrast-enhanced CT. MRI showed the best performance for the diagnosis of skull base invasion in nasopharyngeal carcinoma, followed closely by SPECT/CT. SPECT/CT had poorer specificity than that of both MRI and CT, while CT had the lowest sensitivity.
Computed Tomography 3-D Imaging of the Metal Deformation Flow Path in Friction Stir Welding
NASA Technical Reports Server (NTRS)
Schneider, Judy; Beshears, Ronald; Nunes, Arthur C., Jr.
2005-01-01
In friction stir welding (FSW), a rotating threaded pin tool is inserted into a weld seam and literally stirs the edges of the seam together. To determine optimal processing parameters for producing a defect free weld, a better understanding of the resulting metal deformation flow path is required. Marker studies are the principal method of studying the metal deformation flow path around the FSW pin tool. In our study, we have used computed tomography (CT) scans to reveal the flow pattern of a lead wire embedded in a FSW weld seam. At the welding temperature of aluminum, the lead becomes molten and is carried with the macro-flow of the weld metal. By using CT images, a 3-dimensional (3D) image of the lead flow pattern can be reconstructed. CT imaging was found to be a convenient and comprehensive way of collecting and displaying tracer data. It marks an advance over previous more tedious and ambiguous radiographic/metallographic data collection methods.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Park, P; Schreibmann, E; Fox, T
2014-06-15
Purpose: Severe CT artifacts can impair our ability to accurately calculate proton range thereby resulting in a clinically unacceptable treatment plan. In this work, we investigated a novel CT artifact correction method based on a coregistered MRI and investigated its ability to estimate CT HU and proton range in the presence of severe CT artifacts. Methods: The proposed method corrects corrupted CT data using a coregistered MRI to guide the mapping of CT values from a nearby artifact-free region. First patient MRI and CT images were registered using 3D deformable image registration software based on B-spline and mutual information. Themore » CT slice with severe artifacts was selected as well as a nearby slice free of artifacts (e.g. 1cm away from the artifact). The two sets of paired MRI and CT images at different slice locations were further registered by applying 2D deformable image registration. Based on the artifact free paired MRI and CT images, a comprehensive geospatial analysis was performed to predict the correct CT HU of the CT image with severe artifact. For a proof of concept, a known artifact was introduced that changed the ground truth CT HU value up to 30% and up to 5cm error in proton range. The ability of the proposed method to recover the ground truth was quantified using a selected head and neck case. Results: A significant improvement in image quality was observed visually. Our proof of concept study showed that 90% of area that had 30% errors in CT HU was corrected to 3% of its ground truth value. Furthermore, the maximum proton range error up to 5cm was reduced to 4mm error. Conclusion: MRI based CT artifact correction method can improve CT image quality and proton range calculation for patients with severe CT artifacts.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
De Angelis, L; Landry, G; Dedes, G
Purpose: Proton CT (pCT) is a promising imaging modality for reducing range uncertainty in image-guided proton therapy. Range uncertainties partially originate from X-ray CT number conversion to stopping power ratio (SPR) and are limiting the exploitation of the full potential of proton therapy. In this study we explore the concept of spatially dependent fluence modulated proton CT (FMpCT), for achieving optimal image quality in a clinical region of interest (ROI), while reducing significantly the imaging dose to the patient. Methods: The study was based on simulated ideal pCT using pencil beam (PB) scanning. A set of 250 MeV protons PBsmore » was used to create 360 projections of a cylindrical water phantom and a head and neck cancer patient. The tomographic images were reconstructed using a filtered backprojection (FBP) as well as an iterative algorithm (ITR). Different fluence modulation levels were investigated and their impact on the image was quantified in terms of SPR accuracy as well as noise within and outside selected ROIs, as a function of imaging dose. The unmodulated image served as reference. Results: Both FBP reconstruction and ITR without total variation (TV) yielded image quality in the ROIs similar to the reference images, for modulation down to 0.1 of the full proton fluence. The average dose was reduced by 75% for the water phantom and by 40% for the patient. FMpCT does not improve the noise for ITR with TV and modulation 0.1. Conclusion: This is the first work proposing and investigating FMpCT for producing optimal image quality for treatment planning and image guidance, while simultaneously reducing imaging dose. Future work will address spatial resolution effects and the impact of FMpCT on the quality of proton treatment plans for a prototype pCT scanner capable of list mode data acquisition. Acknowledgement: DFG-MAP DFG - Munich-Centre for Advanced Photonics (MAP)« less
Mennecke, Angelika; Svergun, Stanislav; Scholz, Bernhard; Royalty, Kevin; Dörfler, Arnd; Struffert, Tobias
2017-01-01
Metal artefacts can impair accurate diagnosis of haemorrhage using flat detector CT (FD-CT), especially after aneurysm coiling. Within this work we evaluate a prototype metal artefact reduction algorithm by comparison of the artefact-reduced and the non-artefact-reduced FD-CT images to pre-treatment FD-CT and multi-slice CT images. Twenty-five patients with acute aneurysmal subarachnoid haemorrhage (SAH) were selected retrospectively. FD-CT and multi-slice CT before endovascular treatment as well as FD-CT data sets after treatment were available for all patients. The algorithm was applied to post-treatment FD-CT. The effect of the algorithm was evaluated utilizing the pre-post concordance of a modified Fisher score, a subjective image quality assessment, the range of the Hounsfield units within three ROIs, and the pre-post slice-wise Pearson correlation. The pre-post concordance of the modified Fisher score, the subjective image quality, and the pre-post correlation of the ranges of the Hounsfield units were significantly higher for artefact-reduced than for non-artefact-reduced images. Within the metal-affected slices, the pre-post slice-wise Pearson correlation coefficient was higher for artefact-reduced than for non-artefact-reduced images. The overall diagnostic quality of the artefact-reduced images was improved and reached the level of the pre-interventional FD-CT images. The metal-unaffected parts of the image were not modified. • After coiling subarachnoid haemorrhage, metal artefacts seriously reduce FD-CT image quality. • This new metal artefact reduction algorithm is feasible for flat-detector CT. • After coiling, MAR is necessary for diagnostic quality of affected slices. • Slice-wise Pearson correlation is introduced to evaluate improvement of MAR in future studies. • Metal-unaffected parts of image are not modified by this MAR algorithm.
Almatani, Turki; Hugtenburg, Richard P; Lewis, Ryan D; Barley, Susan E; Edwards, Mark A
2016-10-01
Cone beam CT (CBCT) images contain more scatter than a conventional CT image and therefore provide inaccurate Hounsfield units (HUs). Consequently, CBCT images cannot be used directly for radiotherapy dose calculation. The aim of this study is to enable dose calculations to be performed with the use of CBCT images taken during radiotherapy and evaluate the necessity of replanning. A patient with prostate cancer with bilateral metallic prosthetic hip replacements was imaged using both CT and CBCT. The multilevel threshold (MLT) algorithm was used to categorize pixel values in the CBCT images into segments of homogeneous HU. The variation in HU with position in the CBCT images was taken into consideration. This segmentation method relies on the operator dividing the CBCT data into a set of volumes where the variation in the relationship between pixel values and HUs is small. An automated MLT algorithm was developed to reduce the operator time associated with the process. An intensity-modulated radiation therapy plan was generated from CT images of the patient. The plan was then copied to the segmented CBCT (sCBCT) data sets with identical settings, and the doses were recalculated and compared. Gamma evaluation showed that the percentage of points in the rectum with γ < 1 (3%/3 mm) were 98.7% and 97.7% in the sCBCT using MLT and the automated MLT algorithms, respectively. Compared with the planning CT (pCT) plan, the MLT algorithm showed -0.46% dose difference with 8 h operator time while the automated MLT algorithm showed -1.3%, which are both considered to be clinically acceptable, when using collapsed cone algorithm. The segmentation of CBCT images using the method in this study can be used for dose calculation. For a patient with prostate cancer with bilateral hip prostheses and the associated issues with CT imaging, the MLT algorithms achieved a sufficient dose calculation accuracy that is clinically acceptable. The automated MLT algorithm reduced the operator time associated with implementing the MLT algorithm to achieve clinically acceptable accuracy. This saved time makes the automated MLT algorithm superior and easier to implement in the clinical setting. The MLT algorithm has been extended to the complex example of a patient with bilateral hip prostheses, which with the introduction of automation is feasible for use in adaptive radiotherapy, as an alternative to obtaining a new pCT and reoutlining the structures.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ito, K; Kadoya, N; Chiba, M
2016-06-15
Purpose: The aim of this study is to develop radiation treatment planning using magnetic susceptibility obtained from quantitative susceptibility mapping (QSM) via MR imaging. This study demonstrates the feasibility of a method for generating a substitute for a CT image from an MRI. Methods: The head of a healthy volunteer was scanned using a CT scanner and a 3.0 T MRI scanner. The CT imaging was performed with a slice thickness of 2.5 mm at 80 and 120 kV (dual-energy scan). These CT images were converted to relative electron density (rED) using the CT-rED conversion table generated by a previousmore » dual-energy CT scan. The CT-rED conversion table was generated using the conversion of the energy-subtracted CT number to rED via a single linear relationship. One T2 star-weighted 3D gradient echo-based sequence with four different echo times images was acquired using the MRI scanner. These T2 star-weighted images were used to estimate the phase data. To estimate the local field map, a Laplacian unwrapping of the phase and background field removal algorithm were implemented to process phase data. To generate a magnetic susceptibility map from the local field map, we used morphology enabled dipole inversion method. The rED map was resampled to the same resolution as magnetic susceptibility, and the magnetic susceptibility-rED conversion table was obtained via voxel-by-voxel mapping between the magnetic susceptibility and rED maps. Results: A correlation between magnetic susceptibility and rED is not observed through our method. Conclusion: Our results show that the correlation between magnetic susceptibility and rED is not observed. As the next step, we assume that the voxel of the magnetic susceptibility map comprises two materials, such as water (0 ppm) and bone (-2.2 ppm) or water and marrow (0.81ppm). The elements of each voxel were estimated from the ratio of the two materials.« less
Sequentially reweighted TV minimization for CT metal artifact reduction.
Zhang, Xiaomeng; Xing, Lei
2013-07-01
Metal artifact reduction has long been an important topic in x-ray CT image reconstruction. In this work, the authors propose an iterative method that sequentially minimizes a reweighted total variation (TV) of the image and produces substantially artifact-reduced reconstructions. A sequentially reweighted TV minimization algorithm is proposed to fully exploit the sparseness of image gradients (IG). The authors first formulate a constrained optimization model that minimizes a weighted TV of the image, subject to the constraint that the estimated projection data are within a specified tolerance of the available projection measurements, with image non-negativity enforced. The authors then solve a sequence of weighted TV minimization problems where weights used for the next iteration are computed from the current solution. Using the complete projection data, the algorithm first reconstructs an image from which a binary metal image can be extracted. Forward projection of the binary image identifies metal traces in the projection space. The metal-free background image is then reconstructed from the metal-trace-excluded projection data by employing a different set of weights. Each minimization problem is solved using a gradient method that alternates projection-onto-convex-sets and steepest descent. A series of simulation and experimental studies are performed to evaluate the proposed approach. Our study shows that the sequentially reweighted scheme, by altering a single parameter in the weighting function, flexibly controls the sparsity of the IG and reconstructs artifacts-free images in a two-stage process. It successfully produces images with significantly reduced streak artifacts, suppressed noise and well-preserved contrast and edge properties. The sequentially reweighed TV minimization provides a systematic approach for suppressing CT metal artifacts. The technique can also be generalized to other "missing data" problems in CT image reconstruction.
X-ray CT core imaging of Oman Drilling Project on D/V CHIKYU
NASA Astrophysics Data System (ADS)
Michibayashi, K.; Okazaki, K.; Leong, J. A. M.; Kelemen, P. B.; Johnson, K. T. M.; Greenberger, R. N.; Manning, C. E.; Harris, M.; de Obeso, J. C.; Abe, N.; Hatakeyama, K.; Ildefonse, B.; Takazawa, E.; Teagle, D. A. H.; Coggon, J. A.
2017-12-01
We obtained X-ray computed tomography (X-ray CT) images for all cores (GT1A, GT2A, GT3A and BT1A) in Oman Drilling Project Phase 1 (OmanDP cores), since X-ray CT scanning is a routine measurement of the IODP measurement plan onboard Chikyu, which enables the non-destructive observation of the internal structure of core samples. X-ray CT images provide information about chemical compositions and densities of the cores and is useful for assessing sample locations and the quality of the whole-round samples. The X-ray CT scanner (Discovery CT 750HD, GE Medical Systems) on Chikyu scans and reconstructs the image of a 1.4 m section in 10 minutes and produces a series of scan images, each 0.625 mm thick. The X-ray tube (as an X-ray source) and the X-ray detector are installed inside of the gantry at an opposing position to each other. The core sample is scanned in the gantry with the scanning rate of 20 mm/sec. The distribution of attenuation values mapped to an individual slice comprises the raw data that are used for subsequent image processing. Successive two-dimensional (2-D) slices of 512 x 512 pixels yield a representation of attenuation values in three-dimensional (3-D) voxels of 512 x 512 by 1600 in length. Data generated for each core consist of core-axis-normal planes (XY planes) of X-ray attenuation values with dimensions of 512 × 512 pixels in 9 cm × 9 cm cross-section, meaning at the dimensions of a core section, the resolution is 0.176 mm/pixel. X-ray intensity varies as a function of X-ray path length and the linear attenuation coefficient (LAC) of the target material is a function of the chemical composition and density of the target material. The basic measure of attenuation, or radiodensity, is the CT number given in Hounsfield units (HU). CT numbers of air and water are -1000 and 0, respectively. Our preliminary results show that CT numbers of OmanDP cores are well correlated to gamma ray attenuation density (GRA density) as a function of chemical composition and mineral density, so that their profiles with respect to the core depth provide quick lithological information such as mineral identification and phase boundary etc. Moreover, X-ray CT images can be used for 3-D fabric analyses of the whole core even after core cutting into halves for individual analyses.
Low-dose quantitative phase contrast medical CT
NASA Astrophysics Data System (ADS)
Mittone, A.; Bravin, A.; Coan, P.
2018-02-01
X-ray computed tomography (CT) is a powerful and routinely used clinical diagnostic technique, which is well tolerated by patients, and which provides high-resolution images and volumetric information about the body. However, two important limitations still affect this examination procedure: (1) its low sensitivity with respect to soft tissues, and (2) the hazards associated with x-ray exposure. Conventional radiology is based on the detection of the different photon absorption properties that characterize biological tissues, and thus the obtainable image contrast from soft and/or similar tissues is intrinsically limited. In this scenario, x-ray phase contrast imaging (XPCI) has been extensively tested and proven to overcome some of the main issues surrounding standard x-ray imaging. In addition to the absorption signal, XPCI relies on detecting the phase shifts induced by an object. Interestingly, as the order of magnitude of the phase contrast is higher than that of absorption, XPCI can, in principle, offer higher sensitivity at lower radiation doses. However, other technical aspects may counterbalance this gain, and an optimized setup and image processing solutions need to be implemented. The work presented here describes the strategies and developments we have realized, with the aim of controlling the radiation dose for the highly sensitive and quantitative XPCI-CT. Different algorithms for the phase retrieval and CT reconstruction of the XPCI data are presented. The CT algorithms we have implemented, namely the equally sloped tomography and the dictionary learning method, allow the image quality to be preserved while reducing the number of angular projections required by a factor of five. The results applied to breast imaging report accurate reconstructions at clinically compatible doses of the 3D distribution of the refractive properties of full human organs obtained by using three different phase retrieval methods. The described methodologies and the presented results have been validated by a team of clinical radiologists and represent an important step in the exploitation of XPCI-CT for in vivo and possible clinical applications.
Phase-contrast x-ray computed tomography for observing biological specimens and organic materials
NASA Astrophysics Data System (ADS)
Momose, Atsushi; Takeda, Tohoru; Itai, Yuji
1995-02-01
A novel three-dimensional x-ray imaging method has been developed by combining a phase-contrast x-ray imaging technique with x-ray computed tomography. This phase-contrast x-ray computed tomography (PCX-CT) provides sectional images of organic specimens that would produce absorption-contrast x-ray CT images with little contrast. Comparing PCX-CT images of rat cerebellum and cancerous rabbit liver specimens with corresponding absorption-contrast CT images shows that PCX-CT is much more sensitive to the internal structure of organic specimens.
CT and MRI slice separation evaluation by LabView developed software.
Acri, Giuseppe; Testagrossa, Barbara; Sestito, Angela; Bonanno, Lilla; Vermiglio, Giuseppe
2018-02-01
The efficient use of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) equipment necessitates establishing adequate quality-control (QC) procedures. In particular, the accuracy of slice separation, during multislices acquisition, requires scan exploration of phantoms containing test objects. To simplify such procedures, a novel phantom and a computerised LabView-based procedure have been devised, enabling determination the midpoint of full width at half maximum (FWHM) in real time while the distance from the profile midpoint of two progressive images is evaluated and measured. The results were compared with those obtained by processing the same phantom images with commercial software. To validate the proposed methodology the Fisher test was conducted on the resulting data sets. In all cases, there was no statistically significant variation between the commercial procedure and the LabView one, which can be used on any CT and MRI diagnostic devices. Copyright © 2017. Published by Elsevier GmbH.
Automated movement correction for dynamic PET/CT images: evaluation with phantom and patient data.
Ye, Hu; Wong, Koon-Pong; Wardak, Mirwais; Dahlbom, Magnus; Kepe, Vladimir; Barrio, Jorge R; Nelson, Linda D; Small, Gary W; Huang, Sung-Cheng
2014-01-01
Head movement during a dynamic brain PET/CT imaging results in mismatch between CT and dynamic PET images. It can cause artifacts in CT-based attenuation corrected PET images, thus affecting both the qualitative and quantitative aspects of the dynamic PET images and the derived parametric images. In this study, we developed an automated retrospective image-based movement correction (MC) procedure. The MC method first registered the CT image to each dynamic PET frames, then re-reconstructed the PET frames with CT-based attenuation correction, and finally re-aligned all the PET frames to the same position. We evaluated the MC method's performance on the Hoffman phantom and dynamic FDDNP and FDG PET/CT images of patients with neurodegenerative disease or with poor compliance. Dynamic FDDNP PET/CT images (65 min) were obtained from 12 patients and dynamic FDG PET/CT images (60 min) were obtained from 6 patients. Logan analysis with cerebellum as the reference region was used to generate regional distribution volume ratio (DVR) for FDDNP scan before and after MC. For FDG studies, the image derived input function was used to generate parametric image of FDG uptake constant (Ki) before and after MC. Phantom study showed high accuracy of registration between PET and CT and improved PET images after MC. In patient study, head movement was observed in all subjects, especially in late PET frames with an average displacement of 6.92 mm. The z-direction translation (average maximum = 5.32 mm) and x-axis rotation (average maximum = 5.19 degrees) occurred most frequently. Image artifacts were significantly diminished after MC. There were significant differences (P<0.05) in the FDDNP DVR and FDG Ki values in the parietal and temporal regions after MC. In conclusion, MC applied to dynamic brain FDDNP and FDG PET/CT scans could improve the qualitative and quantitative aspects of images of both tracers.
Automated Movement Correction for Dynamic PET/CT Images: Evaluation with Phantom and Patient Data
Ye, Hu; Wong, Koon-Pong; Wardak, Mirwais; Dahlbom, Magnus; Kepe, Vladimir; Barrio, Jorge R.; Nelson, Linda D.; Small, Gary W.; Huang, Sung-Cheng
2014-01-01
Head movement during a dynamic brain PET/CT imaging results in mismatch between CT and dynamic PET images. It can cause artifacts in CT-based attenuation corrected PET images, thus affecting both the qualitative and quantitative aspects of the dynamic PET images and the derived parametric images. In this study, we developed an automated retrospective image-based movement correction (MC) procedure. The MC method first registered the CT image to each dynamic PET frames, then re-reconstructed the PET frames with CT-based attenuation correction, and finally re-aligned all the PET frames to the same position. We evaluated the MC method's performance on the Hoffman phantom and dynamic FDDNP and FDG PET/CT images of patients with neurodegenerative disease or with poor compliance. Dynamic FDDNP PET/CT images (65 min) were obtained from 12 patients and dynamic FDG PET/CT images (60 min) were obtained from 6 patients. Logan analysis with cerebellum as the reference region was used to generate regional distribution volume ratio (DVR) for FDDNP scan before and after MC. For FDG studies, the image derived input function was used to generate parametric image of FDG uptake constant (Ki) before and after MC. Phantom study showed high accuracy of registration between PET and CT and improved PET images after MC. In patient study, head movement was observed in all subjects, especially in late PET frames with an average displacement of 6.92 mm. The z-direction translation (average maximum = 5.32 mm) and x-axis rotation (average maximum = 5.19 degrees) occurred most frequently. Image artifacts were significantly diminished after MC. There were significant differences (P<0.05) in the FDDNP DVR and FDG Ki values in the parietal and temporal regions after MC. In conclusion, MC applied to dynamic brain FDDNP and FDG PET/CT scans could improve the qualitative and quantitative aspects of images of both tracers. PMID:25111700
DOE Office of Scientific and Technical Information (OSTI.GOV)
Noid, G; Tai, A; Li, X
2016-06-15
Purpose: Advanced image post-processing techniques which enhance soft-tissue contrast in CT have not been widely employed for RT planning or delivery guidance. The purpose of this work is to assess the soft-tissue contrast enhancement from non-linear contrast enhancing filters and its impact in RT. The contrast enhancement reduces patient alignment uncertainties. Methods: Non-linear contrast enhancing methods, such as Best Contrast (Siemens), amplify small differences in X-ray attenuation between two adjacent structure without significantly increasing noise. Best Contrast (BC) separates a CT into two frequency bands. The low frequency band is modified by a non-linear scaling function before recombination with themore » high frequency band. CT data collected using a CT-on-rails (Definition AS Open, Siemens) during daily CT-guided RT for 6 prostate cancer patients and an image quality phantom (The Phantom Laboratory) were analyzed. Images acquired with a standard protocol (120 kVp, 0.6 pitch, 18 mGy CTDIvol) were processed before comparison to the unaltered images. Contrast and noise were measured in the the phantom. Inter-observer variation was assessed by placing prostate contours on the 12 CT study sets, 6 enhanced and 6 unaltered, in a blinded study involving 8 observers. Results: The phantom data demonstrate that BC increased the contrast between the 1.0% supra-slice element and the background substrate by 46.5 HU while noise increased by only 2.3 HU. Thus the contrast to noise ratio increased from 1.28 to 6.71. Furthermore, the variation in centroid position of the prostate contours was decreased from 1.3±0.4 mm to 0.8±0.3 mm. Thus the CTV-to-PTV margin was reduced by 1.1 mm. The uncertainty in delineation of the prostate/rectum edge decreased by 0.5 mm. Conclusion: As demonstrated in phantom and patient scans the BC filter accentuates soft-tissue contrast. This enhancement leads to reduced inter-observer variation, which should improve RT planning and delivery. Supported by Siemens.« less
Automatic segmentation of lumbar vertebrae in CT images
NASA Astrophysics Data System (ADS)
Kulkarni, Amruta; Raina, Akshita; Sharifi Sarabi, Mona; Ahn, Christine S.; Babayan, Diana; Gaonkar, Bilwaj; Macyszyn, Luke; Raghavendra, Cauligi
2017-03-01
Lower back pain is one of the most prevalent disorders in the developed/developing world. However, its etiology is poorly understood and treatment is often determined subjectively. In order to quantitatively study the emergence and evolution of back pain, it is necessary to develop consistently measurable markers for pathology. Imaging based measures offer one solution to this problem. The development of imaging based on quantitative biomarkers for the lower back necessitates automated techniques to acquire this data. While the problem of segmenting lumbar vertebrae has been addressed repeatedly in literature, the associated problem of computing relevant biomarkers on the basis of the segmentation has not been addressed thoroughly. In this paper, we propose a Random-Forest based approach that learns to segment vertebral bodies in CT images followed by a biomarker evaluation framework that extracts vertebral heights and widths from the segmentations obtained. Our dataset consists of 15 CT sagittal scans obtained from General Electric Healthcare. Our main approach is divided into three parts: the first stage is image pre-processing which is used to correct for variations in illumination across all the images followed by preparing the foreground and background objects from images; the next stage is Machine Learning using Random-Forests, which distinguishes the interest-point vectors between foreground or background; and the last step is image post-processing, which is crucial to refine the results of classifier. The Dice coefficient was used as a statistical validation metric to evaluate the performance of our segmentations with an average value of 0.725 for our dataset.
Fu, Jian; Hu, Xinhua; Velroyen, Astrid; Bech, Martin; Jiang, Ming; Pfeiffer, Franz
2015-01-01
Due to the potential of compact imaging systems with magnified spatial resolution and contrast, cone-beam x-ray differential phase-contrast computed tomography (DPC-CT) has attracted significant interest. The current proposed FDK reconstruction algorithm with the Hilbert imaginary filter will induce severe cone-beam artifacts when the cone-beam angle becomes large. In this paper, we propose an algebraic iterative reconstruction (AIR) method for cone-beam DPC-CT and report its experiment results. This approach considers the reconstruction process as the optimization of a discrete representation of the object function to satisfy a system of equations that describes the cone-beam DPC-CT imaging modality. Unlike the conventional iterative algorithms for absorption-based CT, it involves the derivative operation to the forward projections of the reconstructed intermediate image to take into account the differential nature of the DPC projections. This method is based on the algebraic reconstruction technique, reconstructs the image ray by ray, and is expected to provide better derivative estimates in iterations. This work comprises a numerical study of the algorithm and its experimental verification using a dataset measured with a three-grating interferometer and a mini-focus x-ray tube source. It is shown that the proposed method can reduce the cone-beam artifacts and performs better than FDK under large cone-beam angles. This algorithm is of interest for future cone-beam DPC-CT applications.
Noninvasive imaging of experimental lung fibrosis.
Zhou, Yong; Chen, Huaping; Ambalavanan, Namasivayam; Liu, Gang; Antony, Veena B; Ding, Qiang; Nath, Hrudaya; Eary, Janet F; Thannickal, Victor J
2015-07-01
Small animal models of lung fibrosis are essential for unraveling the molecular mechanisms underlying human fibrotic lung diseases; additionally, they are useful for preclinical testing of candidate antifibrotic agents. The current end-point measures of experimental lung fibrosis involve labor-intensive histological and biochemical analyses. These measures fail to account for dynamic changes in the disease process in individual animals and are limited by the need for large numbers of animals for longitudinal studies. The emergence of noninvasive imaging technologies provides exciting opportunities to image lung fibrosis in live animals as often as needed and to longitudinally track the efficacy of novel antifibrotic compounds. Data obtained by noninvasive imaging provide complementary information to histological and biochemical measurements. In addition, the use of noninvasive imaging in animal studies reduces animal usage, thus satisfying animal welfare concerns. In this article, we review these new imaging modalities with the potential for evaluation of lung fibrosis in small animal models. Such techniques include micro-computed tomography (micro-CT), magnetic resonance imaging, positron emission tomography (PET), single photon emission computed tomography (SPECT), and multimodal imaging systems including PET/CT and SPECT/CT. It is anticipated that noninvasive imaging will be increasingly used in animal models of fibrosis to gain insights into disease pathogenesis and as preclinical tools to assess drug efficacy.
Evaluation of image registration in PET/CT of the liver and recommendations for optimized imaging.
Vogel, Wouter V; van Dalen, Jorn A; Wiering, Bas; Huisman, Henkjan; Corstens, Frans H M; Ruers, Theo J M; Oyen, Wim J G
2007-06-01
Multimodality PET/CT of the liver can be performed with an integrated (hybrid) PET/CT scanner or with software fusion of dedicated PET and CT. Accurate anatomic correlation and good image quality of both modalities are important prerequisites, regardless of the applied method. Registration accuracy is influenced by breathing motion differences on PET and CT, which may also have impact on (attenuation correction-related) artifacts, especially in the upper abdomen. The impact of these issues was evaluated for both hybrid PET/CT and software fusion, focused on imaging of the liver. Thirty patients underwent hybrid PET/CT, 20 with CT during expiration breath-hold (EB) and 10 with CT during free breathing (FB). Ten additional patients underwent software fusion of dedicated PET and dedicated expiration breath-hold CT (SF). The image registration accuracy was evaluated at the location of liver borders on CT and uncorrected PET images and at the location of liver lesions. Attenuation-correction artifacts were evaluated by comparison of liver borders on uncorrected and attenuation-corrected PET images. CT images were evaluated for the presence of breathing artifacts. In EB, 40% of patients had an absolute registration error of the diaphragm in the craniocaudal direction of >1 cm (range, -16 to 44 mm), and 45% of lesions were mispositioned >1 cm. In 50% of cases, attenuation-correction artifacts caused a deformation of the liver dome on PET of >1 cm. Poor compliance to breath-hold instructions caused CT artifacts in 55% of cases. In FB, 30% had registration errors of >1 cm (range, -4 to 16 mm) and PET artifacts were less extensive, but all CT images had breathing artifacts. As SF allows independent alignment of PET and CT, no registration errors or artifacts of >1 cm of the diaphragm occurred. Hybrid PET/CT of the liver may have significant registration errors and artifacts related to breathing motion. The extent of these issues depends on the selected breathing protocol and the speed of the CT scanner. No protocol or scanner can guarantee perfect image fusion. On the basis of these findings, recommendations were formulated with regard to scanner requirements, breathing protocols, and reporting.
Haneder, Stefan; Siedek, Florian; Doerner, Jonas; Pahn, Gregor; Grosse Hokamp, Nils; Maintz, David; Wybranski, Christian
2018-01-01
Background A novel, multi-energy, dual-layer spectral detector computed tomography (SDCT) is commercially available now with the vendor's claim that it yields the same or better quality of polychromatic, conventional CT images like modern single-energy CT scanners without any radiation dose penalty. Purpose To intra-individually compare the quality of conventional polychromatic CT images acquired with a dual-layer spectral detector (SDCT) and the latest generation 128-row single-energy-detector (CT128) from the same manufacturer. Material and Methods Fifty patients underwent portal-venous phase, thoracic-abdominal CT scans with the SDCT and prior CT128 imaging. The SDCT scanning protocol was adapted to yield a similar estimated dose length product (DLP) as the CT128. Patient dose optimization by automatic tube current modulation and CT image reconstruction with a state-of-the-art iterative algorithm were identical on both scanners. CT image contrast-to-noise ratio (CNR) was compared between the SDCT and CT128 in different anatomic structures. Image quality and noise were assessed independently by two readers with 5-point-Likert-scales. Volume CT dose index (CTDI vol ), and DLP were recorded and normalized to 68 cm acquisition length (DLP 68 ). Results The SDCT yielded higher mean CNR values of 30.0% ± 2.0% (26.4-32.5%) in all anatomic structures ( P < 0.001) and excellent scores for qualitative parameters surpassing the CT128 (all P < 0.0001) with substantial inter-rater agreement (κ ≥ 0.801). Despite adapted scan protocols the SDCT yielded lower values for CTDI vol (-10.1 ± 12.8%), DLP (-13.1 ± 13.9%), and DLP 68 (-15.3 ± 16.9%) than the CT128 (all P < 0.0001). Conclusion The SDCT scanner yielded better CT image quality compared to the CT128 and lower radiation dose parameters.
Multimodal system for the planning and guidance of bronchoscopy
NASA Astrophysics Data System (ADS)
Higgins, William E.; Cheirsilp, Ronnarit; Zang, Xiaonan; Byrnes, Patrick
2015-03-01
Many technical innovations in multimodal radiologic imaging and bronchoscopy have emerged recently in the effort against lung cancer. Modern X-ray computed-tomography (CT) scanners provide three-dimensional (3D) high-resolution chest images, positron emission tomography (PET) scanners give complementary molecular imaging data, and new integrated PET/CT scanners combine the strengths of both modalities. State-of-the-art bronchoscopes permit minimally invasive tissue sampling, with vivid endobronchial video enabling navigation deep into the airway-tree periphery, while complementary endobronchial ultrasound (EBUS) reveals local views of anatomical structures outside the airways. In addition, image-guided intervention (IGI) systems have proven their utility for CT-based planning and guidance of bronchoscopy. Unfortunately, no IGI system exists that integrates all sources effectively through the complete lung-cancer staging work flow. This paper presents a prototype of a computer-based multimodal IGI system that strives to fill this need. The system combines a wide range of automatic and semi-automatic image-processing tools for multimodal data fusion and procedure planning. It also provides a flexible graphical user interface for follow-on guidance of bronchoscopy/EBUS. Human-study results demonstrate the system's potential.
Towards Omni-Tomography—Grand Fusion of Multiple Modalities for Simultaneous Interior Tomography
Wang, Ge; Zhang, Jie; Gao, Hao; Weir, Victor; Yu, Hengyong; Cong, Wenxiang; Xu, Xiaochen; Shen, Haiou; Bennett, James; Furth, Mark; Wang, Yue; Vannier, Michael
2012-01-01
We recently elevated interior tomography from its origin in computed tomography (CT) to a general tomographic principle, and proved its validity for other tomographic modalities including SPECT, MRI, and others. Here we propose “omni-tomography”, a novel concept for the grand fusion of multiple tomographic modalities for simultaneous data acquisition in a region of interest (ROI). Omni-tomography can be instrumental when physiological processes under investigation are multi-dimensional, multi-scale, multi-temporal and multi-parametric. Both preclinical and clinical studies now depend on in vivo tomography, often requiring separate evaluations by different imaging modalities. Over the past decade, two approaches have been used for multimodality fusion: Software based image registration and hybrid scanners such as PET-CT, PET-MRI, and SPECT-CT among others. While there are intrinsic limitations with both approaches, the main obstacle to the seamless fusion of multiple imaging modalities has been the bulkiness of each individual imager and the conflict of their physical (especially spatial) requirements. To address this challenge, omni-tomography is now unveiled as an emerging direction for biomedical imaging and systems biomedicine. PMID:22768108
NASA Astrophysics Data System (ADS)
McDougald, Wendy A.; Collins, Richard; Green, Mark; Tavares, Adriana A. S.
2017-10-01
Obtaining accurate quantitative measurements in preclinical Positron Emission Tomography/Computed Tomography (PET/CT) imaging is of paramount importance in biomedical research and helps supporting efficient translation of preclinical results to the clinic. The purpose of this study was two-fold: (1) to investigate the effects of different CT acquisition protocols on PET/CT image quality and data quantification; and (2) to evaluate the absorbed dose associated with varying CT parameters. Methods: An air/water quality control CT phantom, tissue equivalent material phantom, an in-house 3D printed phantom and an image quality PET/CT phantom were imaged using a Mediso nanoPET/CT scanner. Collected data was analyzed using PMOD software, VivoQuant software and National Electric Manufactures Association (NEMA) software implemented by Mediso. Measured Hounsfield Unit (HU) in collected CT images were compared to the known HU values and image noise was quantified. PET recovery coefficients (RC), uniformity and quantitative bias were also measured. Results: Only less than 2% and 1% of CT acquisition protocols yielded water HU values < -80 and air HU values < -840, respectively. Four out of eleven CT protocols resulted in more than 100 mGy absorbed dose. Different CT protocols did not impact PET uniformity and RC, and resulted in <4% overall bias relative to expected radioactive concentration. Conclusion: Preclinical CT protocols with increased exposure times can result in high absorbed doses to the small animals. These should be avoided, as they do not contributed towards improved microPET/CT image quantitative accuracy and could limit longitudinal scanning of small animals.
Registration of 2D to 3D joint images using phase-based mutual information
NASA Astrophysics Data System (ADS)
Dalvi, Rupin; Abugharbieh, Rafeef; Pickering, Mark; Scarvell, Jennie; Smith, Paul
2007-03-01
Registration of two dimensional to three dimensional orthopaedic medical image data has important applications particularly in the area of image guided surgery and sports medicine. Fluoroscopy to computer tomography (CT) registration is an important case, wherein digitally reconstructed radiographs derived from the CT data are registered to the fluoroscopy data. Traditional registration metrics such as intensity-based mutual information (MI) typically work well but often suffer from gross misregistration errors when the image to be registered contains a partial view of the anatomy visible in the target image. Phase-based MI provides a robust alternative similarity measure which, in addition to possessing the general robustness and noise immunity that MI provides, also employs local phase information in the registration process which makes it less susceptible to the aforementioned errors. In this paper, we propose using the complex wavelet transform for computing image phase information and incorporating that into a phase-based MI measure for image registration. Tests on a CT volume and 6 fluoroscopy images of the knee are presented. The femur and the tibia in the CT volume were individually registered to the fluoroscopy images using intensity-based MI, gradient-based MI and phase-based MI. Errors in the coordinates of fiducials present in the bone structures were used to assess the accuracy of the different registration schemes. Quantitative results demonstrate that the performance of intensity-based MI was the worst. Gradient-based MI performed slightly better, while phase-based MI results were the best consistently producing the lowest errors.
NASA Astrophysics Data System (ADS)
Takahashi, Noriyuki; Kinoshita, Toshibumi; Ohmura, Tomomi; Matsuyama, Eri; Toyoshima, Hideto
2017-03-01
The early diagnosis of idiopathic normal pressure hydrocephalus (iNPH) considered as a treatable dementia is important. The iNPH causes enlargement of lateral ventricles (LVs). The degree of the enlargement of the LVs on CT or MR images is evaluated by using a diagnostic imaging criterion, Evans index. Evans index is defined as the ratio of the maximal width of frontal horns (FH) of the LVs to the maximal width of the inner skull (IS). Evans index is the most commonly used parameter for the evaluation of ventricular enlargement. However, manual measurement of Evans index is a time-consuming process. In this study, we present an automated method to compute Evans index on brain CT images. The algorithm of the method consisted of five major steps: standardization of CT data to an atlas, extraction of FH and IS regions, the search for the outmost points of bilateral FH regions, determination of the maximal widths of both the FH and the IS, and calculation of Evans index. The standardization to the atlas was performed by using linear affine transformation and non-linear wrapping techniques. The FH regions were segmented by using a three dimensional region growing technique. This scheme was applied to CT scans from 44 subjects, including 13 iNPH patients. The average difference in Evans index between the proposed method and manual measurement was 0.01 (1.6%), and the correlation coefficient of these data for the Evans index was 0.98. Therefore, this computerized method may have the potential to accurately compute Evans index for the diagnosis of iNPH on CT images.
MR to CT registration of brains using image synthesis
NASA Astrophysics Data System (ADS)
Roy, Snehashis; Carass, Aaron; Jog, Amod; Prince, Jerry L.; Lee, Junghoon
2014-03-01
Computed tomography (CT) is the preferred imaging modality for patient dose calculation for radiation therapy. Magnetic resonance (MR) imaging (MRI) is used along with CT to identify brain structures due to its superior soft tissue contrast. Registration of MR and CT is necessary for accurate delineation of the tumor and other structures, and is critical in radiotherapy planning. Mutual information (MI) or its variants are typically used as a similarity metric to register MRI to CT. However, unlike CT, MRI intensity does not have an accepted calibrated intensity scale. Therefore, MI-based MR-CT registration may vary from scan to scan as MI depends on the joint histogram of the images. In this paper, we propose a fully automatic framework for MR-CT registration by synthesizing a synthetic CT image from MRI using a co-registered pair of MR and CT images as an atlas. Patches of the subject MRI are matched to the atlas and the synthetic CT patches are estimated in a probabilistic framework. The synthetic CT is registered to the original CT using a deformable registration and the computed deformation is applied to the MRI. In contrast to most existing methods, we do not need any manual intervention such as picking landmarks or regions of interests. The proposed method was validated on ten brain cancer patient cases, showing 25% improvement in MI and correlation between MR and CT images after registration compared to state-of-the-art registration methods.
68Ga-NODAGA-RGDyK PET/CT Imaging in Esophageal Cancer: First-in-Human Imaging.
Van Der Gucht, Axel; Pomoni, Anastasia; Jreige, Mario; Allemann, Pierre; Prior, John O
2016-11-01
Ga-NODAGA-RGDyK(cyclic) and FDG PET/CT were performed in a 39-year-old man for the work-up of a moderately differentiated carcinoma of the gastro-esophageal junction within a clinical study protocol. Although FDG PET images showed intense, diffuse hypermetabolic lesion activity, NODAGA-RGDyK illustrated the neo-angiogenesis process with tracer uptake clearly localized in non-FDG-avid perilesional structures. Neo-angiogenesis is characterized by ανβ3 integrin expression at the lesion surface of newly formed vessels. This case supports evidence that angiogenesis imaging might therefore be a crucial step in early disease identification and localization, metastatization potential, and in monitoring the efficacy of antiangiogenic therapies.
Qi, Zhihua; Gates, Erica L; O'Brien, Maureen M; Trout, Andrew T
2018-02-01
Both [F-18]2-fluoro-2-deoxyglucose positron emission tomography/computed tomography ( 18 F-FDG PET/CT) and diagnostic CT are at times required for lymphoma staging. This means some body segments are exposed twice to X-rays for generation of CT data (diagnostic CT + localization CT). To describe a combined PET/diagnostic CT approach that modulates CT tube current along the z-axis, providing diagnostic CT of some body segments and localization CT of the remaining body segments, thereby reducing patient radiation dose. We retrospectively compared total patient radiation dose between combined PET/diagnostic CT and separately acquired PET/CT and diagnostic CT exams. When available, we calculated effective doses for both approaches in the same patient; otherwise, we used data from patients of similar size. To confirm image quality, we compared image noise (Hounsfield unit [HU] standard deviation) as measured in the liver on both combined and separately acquired diagnostic CT images. We used t-tests for dose comparisons and two one-sided tests for image-quality equivalence testing. Mean total effective dose for the CT component of the combined and separately acquired diagnostic CT exams were 6.20±2.69 and 8.17±2.61 mSv, respectively (P<0.0001). Average dose savings with the combined approach was 24.8±17.8% (2.60±2.51 mSv [range: 0.32-4.72 mSv]) of total CT effective dose. Image noise was not statistically significantly different between approaches (12.2±1.8 HU vs. 11.7±1.5 HU for the combined and separately acquired diagnostic CT images, respectively). A combined PET/diagnostic CT approach as described offers dose savings at similar image quality for children and young adults with lymphoma who have indications for both PET and diagnostic CT examinations.
Grosser, Oliver S.; Kupitz, Dennis; Ruf, Juri; Czuczwara, Damian; Steffen, Ingo G.; Furth, Christian; Thormann, Markus; Loewenthal, David; Ricke, Jens; Amthauer, Holger
2015-01-01
Background Hybrid imaging combines nuclear medicine imaging such as single photon emission computed tomography (SPECT) or positron emission tomography (PET) with computed tomography (CT). Through this hybrid design, scanned patients accumulate radiation exposure from both applications. Imaging modalities have been the subject of long-term optimization efforts, focusing on diagnostic applications. It was the aim of this study to investigate the influence of an iterative CT image reconstruction algorithm (ASIR) on the image quality of the low-dose CT images. Methodology/Principal Findings Examinations were performed with a SPECT-CT scanner with standardized CT and SPECT-phantom geometries and CT protocols with systematically reduced X-ray tube currents. Analyses included image quality with respect to photon flux. Results were compared to the standard FBP reconstructed images. The general impact of the CT-based attenuation maps used during SPECT reconstruction was examined for two SPECT phantoms. Using ASIR for image reconstructions, image noise was reduced compared to FBP reconstructions for the same X-ray tube current. The Hounsfield unit (HU) values reconstructed by ASIR were correlated to the FBP HU values(R2 ≥ 0.88) and the contrast-to-noise ratio (CNR) was improved by ASIR. However, for a phantom with increased attenuation, the HU values shifted for low X-ray tube currents I ≤ 60 mA (p ≤ 0.04). In addition, the shift of the HU values was observed within the attenuation corrected SPECT images for very low X-ray tube currents (I ≤ 20 mA, p ≤ 0.001). Conclusion/Significance In general, the decrease in X-ray tube current up to 30 mA in combination with ASIR led to a reduction of CT-related radiation exposure without a significant decrease in image quality. PMID:26390216
Soukup, Jason W; Drees, Randi; Koenig, Lisa J; Snyder, Christopher J; Hetzel, Scott; Miles, Chanda R; Schwarz, Tobias
2015-01-01
The objective of this blinded study was to validate the use of cone beam computed tomography (C) for imaging of the canine maxillary dentoalveolar structures by comparing its diagnostic image quality with that of 64-multidetector row CT Sagittal slices of a tooth-bearing segment of the maxilla of a commercially purchased dog skull embedded in methylmethacrylate were obtained along a line parallel with the dental arch using a commercial histology diamond saw. The slice of tooth-bearing bone that best depicted the dentoalveolar structures was chosen and photographed. The maxillary segment was imaged with cone beam CT and 64-multidetector row CT. Four blinded evaluators compared the cone beam CT and 64-multidetector row CT images and image quality was scored as it related to the anatomy of dentoalveolar structures. Trabecular bone, enamel, dentin, pulp cavity, periodontal ligament space, and lamina dura were scored In addition, a score depicting the evaluators overall impression of the image was recorded. Images acquired with cone beam CT were found to be significantly superior in image quality to images acquired with 64-multidetector row CT overall, and in all scored categories. In our study setting cone beam CT was found to be a valid and clinically superior imaging modality for the canine maxillary dentoalveolar structures when compared to 64-multidetector row CT.
Imran, Jonathan B; Madni, Tarik D; Pruitt, Jeffrey H; Cornelius, Canon; Subramanian, Madhu; Clark, Audra T; Mokdad, Ali A; Rizk, Paul; Minei, Joseph P; Cripps, Michael W; Eastman, Alexander L
2018-07-01
The main objective of this study was to compare detection rates of clinically significant thoracolumbar spine (TLS) fracture between computed tomography (CT) imaging of the chest, abdomen, and spine (CT CAP) and CT for the thoracolumbar spine (CT TL). We retrospectively identified patients at our institution with a TLS fracture over a two-year period that had both CT CAP and reformatted CT TL imaging. The sensitivity of CT CAP to identify fracture was calculated for each fracture type. A total of 516 TLS fractures were identified in 125 patients using reformatted CT TL spine imaging. Overall, 69 of 512 fractures (13%) were missed on CT CAP that were identified on CT TL. Of those, there were no clinically significant missed fractures. CT CAP could potentially be used as a screening tool for clinically significant TLS injuries. Copyright © 2017 Elsevier Inc. All rights reserved.
Webster, G J; Kilgallon, J E; Ho, K F; Rowbottom, C G; Slevin, N J; Mackay, R I
2009-06-01
Uncertainty and inconsistency are observed in target volume delineation in the head and neck for radiotherapy treatment planning based only on CT imaging. Alternative modalities such as MRI have previously been incorporated into the delineation process to provide additional anatomical information. This work aims to improve on previous studies by combining good image quality with precise patient immobilisation in order to maintain patient position between scans. MR images were acquired using quadrature coils placed over the head and neck while the patient was immobilised in the treatment position using a five-point thermoplastic shell. The MR image and CT images were automatically fused in the Pinnacle treatment planning system using Syntegra software. Image quality, distortion and accuracy of the image registration using patient anatomy were evaluated. Image quality was found to be superior to that acquired using the body coil, while distortion was < 1.0 mm to a radius of 8.7 cm from the scan centre. Image registration accuracy was found to be 2.2 mm (+/- 0.9 mm) and < 3.0 degrees (n = 6). A novel MRI technique that combines good image quality with patient immobilization has been developed and is now in clinical use. The scan duration of approximately 15 min has been well tolerated by all patients.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cui Yunfeng; Galvin, James M.; Radiation Therapy Oncology Group, American College of Radiology, Philadelphia, Pennsylvania
2013-01-01
Purpose: To report the process and initial experience of remote credentialing of three-dimensional (3D) image guided radiation therapy (IGRT) as part of the quality assurance (QA) of submitted data for Radiation Therapy Oncology Group (RTOG) clinical trials; and to identify major issues resulting from this process and analyze the review results on patient positioning shifts. Methods and Materials: Image guided radiation therapy datasets including in-room positioning CT scans and daily shifts applied were submitted through the Image Guided Therapy QA Center from institutions for the IGRT credentialing process, as required by various RTOG trials. A centralized virtual environment is establishedmore » at the RTOG Core Laboratory, containing analysis tools and database infrastructure for remote review by the Physics Principal Investigators of each protocol. The appropriateness of IGRT technique and volumetric image registration accuracy were evaluated. Registration accuracy was verified by repeat registration with a third-party registration software system. With the accumulated review results, registration differences between those obtained by the Physics Principal Investigators and from the institutions were analyzed for different imaging sites, shift directions, and imaging modalities. Results: The remote review process was successfully carried out for 87 3D cases (out of 137 total cases, including 2-dimensional and 3D) during 2010. Frequent errors in submitted IGRT data and challenges in the review of image registration for some special cases were identified. Workarounds for these issues were developed. The average differences of registration results between reviewers and institutions ranged between 2 mm and 3 mm. Large discrepancies in the superior-inferior direction were found for megavoltage CT cases, owing to low spatial resolution in this direction for most megavoltage CT cases. Conclusion: This first experience indicated that remote review for 3D IGRT as part of QA for RTOG clinical trials is feasible and effective. The magnitude of registration discrepancy between institution and reviewer was presented, and the major issues were investigated to further improve this remote evaluation process.« less
NASA Astrophysics Data System (ADS)
Abu Anas, Emran Mohammad; Kim, Jae Gon; Lee, Soo Yeol; Kamrul Hasan, Md
2011-10-01
The use of an x-ray flat panel detector is increasingly becoming popular in 3D cone beam volume CT machines. Due to the deficient semiconductor array manufacturing process, the cone beam projection data are often corrupted by different types of abnormalities, which cause severe ring and radiant artifacts in a cone beam reconstruction image, and as a result, the diagnostic image quality is degraded. In this paper, a novel technique is presented for the correction of error in the 2D cone beam projections due to abnormalities often observed in 2D x-ray flat panel detectors. Template images are derived from the responses of the detector pixels using their statistical properties and then an effective non-causal derivative-based detection algorithm in 2D space is presented for the detection of defective and mis-calibrated detector elements separately. An image inpainting-based 3D correction scheme is proposed for the estimation of responses of defective detector elements, and the responses of the mis-calibrated detector elements are corrected using the normalization technique. For real-time implementation, a simplification of the proposed off-line method is also suggested. Finally, the proposed algorithms are tested using different real cone beam volume CT images and the experimental results demonstrate that the proposed methods can effectively remove ring and radiant artifacts from cone beam volume CT images compared to other reported techniques in the literature.
NASA Astrophysics Data System (ADS)
Wu, Jay; Shih, Cheng-Ting; Chang, Shu-Jun; Huang, Tzung-Chi; Chen, Chuan-Lin; Wu, Tung Hsin
2011-08-01
The quantitative ability of PET/CT allows the widespread use in clinical research and cancer staging. However, metal artifacts induced by high-density metal objects degrade the quality of CT images. These artifacts also propagate to the corresponding PET image and cause a false increase of 18F-FDG uptake near the metal implants when the CT-based attenuation correction (AC) is performed. In this study, we applied a model-based metal artifact reduction (MAR) algorithm to reduce the dark and bright streaks in the CT image and compared the differences between PET images with the general CT-based AC (G-AC) and the MAR-corrected-CT AC (MAR-AC). Results showed that the MAR algorithm effectively reduced the metal artifacts in the CT images of the ACR flangeless phantom and two clinical cases. The MAR-AC also removed the false-positive hot spot near the metal implants of the PET images. We conclude that the MAR-AC could be applied in clinical practice to improve the quantitative accuracy of PET images. Additionally, further use of PET/CT fusion images with metal artifact correction could be more valuable for diagnosis.
Globally optimal tumor segmentation in PET-CT images: a graph-based co-segmentation method.
Han, Dongfeng; Bayouth, John; Song, Qi; Taurani, Aakant; Sonka, Milan; Buatti, John; Wu, Xiaodong
2011-01-01
Tumor segmentation in PET and CT images is notoriously challenging due to the low spatial resolution in PET and low contrast in CT images. In this paper, we have proposed a general framework to use both PET and CT images simultaneously for tumor segmentation. Our method utilizes the strength of each imaging modality: the superior contrast of PET and the superior spatial resolution of CT. We formulate this problem as a Markov Random Field (MRF) based segmentation of the image pair with a regularized term that penalizes the segmentation difference between PET and CT. Our method simulates the clinical practice of delineating tumor simultaneously using both PET and CT, and is able to concurrently segment tumor from both modalities, achieving globally optimal solutions in low-order polynomial time by a single maximum flow computation. The method was evaluated on clinically relevant tumor segmentation problems. The results showed that our method can effectively make use of both PET and CT image information, yielding segmentation accuracy of 0.85 in Dice similarity coefficient and the average median hausdorff distance (HD) of 6.4 mm, which is 10% (resp., 16%) improvement compared to the graph cuts method solely using the PET (resp., CT) images.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Farjam, R; Tyagi, N; Veeraraghavan, H
Purpose: To develop image-analysis algorithms to synthesize CT with accurate electron densities for MR-only radiotherapy of head & neck (H&N) and pelvis anatomies. Methods: CT and 3T-MRI (Philips, mDixon sequence) scans were randomly selected from a pool of H&N (n=11) and pelvis (n=12) anatomies to form an atlas. All MRIs were pre-processed to eliminate scanner and patient-induced intensity inhomogeneities and standardize their intensity histograms. CT and MRI for each patient were then co-registered to construct CT-MRI atlases. For more accurate CT-MR fusion, bone intensities in CT were suppressed to improve the similarity between CT and MRI. For a new patient,more » all CT-MRI atlases are deformed onto the new patients’ MRI initially. A newly-developed generalized registration error (GRE) metric was then calculated as a measure of local registration accuracy. The synthetic CT value at each point is a 1/GRE-weighted average of CTs from all CT-MR atlases. For evaluation, the mean absolute error (MAE) between the original and synthetic CT (generated in a leave-one-out scheme) was computed. The planning dose from the original and synthetic CT was also compared. Results: For H&N patients, MAE was 67±9, 114±22, and 116±9 HU over the entire-CT, air and bone regions, respectively. For pelvis anatomy, MAE was 47±5 and 146±14 for the entire and bone regions. In comparison with MIRADA medical, an FDA-approved registration tool, we found that our proposed registration strategy reduces MAE by ∼30% and ∼50% over the entire and bone regions, respectively. GRE-weighted strategy further lowers MAE by ∼15% to ∼40%. Our primary dose calculation also showed highly consistent results between the original and synthetic CT. Conclusion: We’ve developed a novel image-analysis technique to synthesize CT for H&N and pelvis anatomies. Our proposed image fusion strategy and GRE metric help generate more accurate synthetic CT using locally more similar atlases (Support: Philips Healthcare). The research is supported by Philips HealthCare.« less
Lorenzoni, Fabio Cesar; Bonfante, Estevam A; Bonfante, Gerson; Martins, Leandro M; Witek, Lukasz; Silva, Nelson R F A
2013-08-01
This evaluation aimed to (1) validate micro-computed tomography (microCT) findings using scanning electron microscopy (SEM) imaging, and (2) quantify the volume of voids and the bonded surface area resulting from fiber-reinforced composite (FRC) dowel cementation technique using microCT scanning technology/3D reconstructing software. A fiberglass dowel was cemented in a condemned maxillary lateral incisor prior to its extraction. A microCT scan was performed of the extracted tooth creating a large volume of data in DICOM format. This set of images was imported to image-processing software to inspect the internal architecture of structures. The outer surface and the spatial relationship of dentin, FRC dowel, cement layer, and voids were reconstructed. Three-dimensional spatial architecture of structures and volumetric analysis revealed that 9.89% of the resin cement was composed of voids and that the bonded area between root dentin and cement was 60.63% larger than that between cement and FRC dowel. SEM imaging demonstrated the presence of voids similarly observed using microCT technology (aim 1). MicroCT technology was able to nondestructively measure the volume of voids within the cement layer and the bonded surface area at the root/cement/FRC interfaces (aim 2). The interfaces at the root dentin/cement/dowel represent a timely and relevant topic where several efforts have been conducted in the past few years to understand their inherent features. MicroCT technology combined with 3D reconstruction allows for not only inspecting the internal arrangement rendered by fiberglass adhesively bonded to root dentin, but also estimating the volume of voids and contacted bond area between the dentin and cement layer. © 2013 by the American College of Prosthodontists.
Deformable registration of x-ray to MRI for post-implant dosimetry in prostate brachytherapy
NASA Astrophysics Data System (ADS)
Park, Seyoun; Song, Danny Y.; Lee, Junghoon
2016-03-01
Post-implant dosimetric assessment in prostate brachytherapy is typically performed using CT as the standard imaging modality. However, poor soft tissue contrast in CT causes significant variability in target contouring, resulting in incorrect dose calculations for organs of interest. CT-MR fusion-based approach has been advocated taking advantage of the complementary capabilities of CT (seed identification) and MRI (soft tissue visibility), and has proved to provide more accurate dosimetry calculations. However, seed segmentation in CT requires manual review, and the accuracy is limited by the reconstructed voxel resolution. In addition, CT deposits considerable amount of radiation to the patient. In this paper, we propose an X-ray and MRI based post-implant dosimetry approach. Implanted seeds are localized using three X-ray images by solving a combinatorial optimization problem, and the identified seeds are registered to MR images by an intensity-based points-to-volume registration. We pre-process the MR images using geometric and Gaussian filtering. To accommodate potential soft tissue deformation, our registration is performed in two steps, an initial affine transformation and local deformable registration. An evolutionary optimizer in conjunction with a points-to-volume similarity metric is used for the affine registration. Local prostate deformation and seed migration are then adjusted by the deformable registration step with external and internal force constraints. We tested our algorithm on six patient data sets, achieving registration error of (1.2+/-0.8) mm in < 30 sec. Our proposed approach has the potential to be a fast and cost-effective solution for post-implant dosimetry with equivalent accuracy as the CT-MR fusion-based approach.
Optimising μCT imaging of the middle and inner cat ear.
Seifert, H; Röher, U; Staszyk, C; Angrisani, N; Dziuba, D; Meyer-Lindenberg, A
2012-04-01
This study's aim was to determine the optimal scan parameters for imaging the middle and inner ear of the cat with micro-computertomography (μCT). Besides, the study set out to assess whether adequate image quality can be obtained to use μCT in diagnostics and research on cat ears. For optimisation, μCT imaging of two cat skull preparations was performed using 36 different scanning protocols. The μCT-scans were evaluated by four experienced experts with regard to the image quality and detail detectability. By compiling a ranking of the results, the best possible scan parameters could be determined. From a third cat's skull, a μCT-scan, using these optimised scan parameters, and a comparative clinical CT-scan were acquired. Afterwards, histological specimens of the ears were produced which were compared to the μCT-images. The comparison shows that the osseous structures are depicted in detail. Although soft tissues cannot be differentiated, the osseous structures serve as valuable spatial orientation of relevant nerves and muscles. Clinical CT can depict many anatomical structures which can also be seen on μCT-images, but these appear a lot less sharp and also less detailed than with μCT. © 2011 Blackwell Verlag GmbH.
WE-EF-207-09: Single-Scan Dual-Energy CT Using Primary Modulation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Petrongolo, M; Zhu, L
Purpose: Compared with conventional CT, dual energy CT (DECT) provides better material differentiation but requires projection data with two different effective x-ray spectra. Current DECT scanners use either a two-scan setting or costly imaging components, which are not feasible or available on open-gantry cone-beam CT systems. We propose a hardware-based method which utilizes primary modulation to enable single-scan DECT on a conventional CT scanner. The CT imaging geometry of primary modulation is identical to that used in our previous method for scatter removal, making it possible for future combination with effective scatter correction on the same CT scanner. Methods: Wemore » insert an attenuation sheet with a spatially-varying pattern - primary modulator-between the x-ray source and the imaged object. During the CT scan, the modulator selectively hardens the x-ray beam at specific detector locations. Thus, the proposed method simultaneously acquires high and low energy data. High and low energy CT images are then reconstructed from projections with missing data via an iterative CT reconstruction algorithm with gradient weighting. Proof-of-concept studies are performed using a copper modulator on a cone-beam CT system. Results: Our preliminary results on the Catphan(c) 600 phantom indicate that the proposed method for single-scan DECT is able to successfully generate high-quality high and low energy CT images and distinguish different materials through basis material decomposition. By applying correction algorithms and using all of the acquired projection data, we can reconstruct a single CT image of comparable image quality to conventional CT images, i.e., without primary modulation. Conclusion: This work shows great promise in using a primary modulator to perform high-quality single-scan DECT imaging. Future studies will test method performance on anthropomorphic phantoms and perform quantitative analyses on image qualities and DECT decomposition accuracy. We will use simulations to optimize the modulator material and geometry parameters.« less
Registering 2D and 3D imaging data of bone during healing.
Hoerth, Rebecca M; Baum, Daniel; Knötel, David; Prohaska, Steffen; Willie, Bettina M; Duda, Georg N; Hege, Hans-Christian; Fratzl, Peter; Wagermaier, Wolfgang
2015-04-01
PURPOSE/AIMS OF THE STUDY: Bone's hierarchical structure can be visualized using a variety of methods. Many techniques, such as light and electron microscopy generate two-dimensional (2D) images, while micro-computed tomography (µCT) allows a direct representation of the three-dimensional (3D) structure. In addition, different methods provide complementary structural information, such as the arrangement of organic or inorganic compounds. The overall aim of the present study is to answer bone research questions by linking information of different 2D and 3D imaging techniques. A great challenge in combining different methods arises from the fact that they usually reflect different characteristics of the real structure. We investigated bone during healing by means of µCT and a couple of 2D methods. Backscattered electron images were used to qualitatively evaluate the tissue's calcium content and served as a position map for other experimental data. Nanoindentation and X-ray scattering experiments were performed to visualize mechanical and structural properties. We present an approach for the registration of 2D data in a 3D µCT reference frame, where scanning electron microscopies serve as a methodic link. Backscattered electron images are perfectly suited for registration into µCT reference frames, since both show structures based on the same physical principles. We introduce specific registration tools that have been developed to perform the registration process in a semi-automatic way. By applying this routine, we were able to exactly locate structural information (e.g. mineral particle properties) in the 3D bone volume. In bone healing studies this will help to better understand basic formation, remodeling and mineralization processes.
Yamashiro, Tsuneo; Miyara, Tetsuhiro; Honda, Osamu; Kamiya, Hisashi; Murata, Kiyoshi; Ohno, Yoshiharu; Tomiyama, Noriyuki; Moriya, Hiroshi; Koyama, Mitsuhiro; Noma, Satoshi; Kamiya, Ayano; Tanaka, Yuko; Murayama, Sadayuki
2014-01-01
To assess the advantages of Adaptive Iterative Dose Reduction using Three Dimensional Processing (AIDR3D) for image quality improvement and dose reduction for chest computed tomography (CT). Institutional Review Boards approved this study and informed consent was obtained. Eighty-eight subjects underwent chest CT at five institutions using identical scanners and protocols. During a single visit, each subject was scanned using different tube currents: 240, 120, and 60 mA. Scan data were converted to images using AIDR3D and a conventional reconstruction mode (without AIDR3D). Using a 5-point scale from 1 (non-diagnostic) to 5 (excellent), three blinded observers independently evaluated image quality for three lung zones, four patterns of lung disease (nodule/mass, emphysema, bronchiolitis, and diffuse lung disease), and three mediastinal measurements (small structure visibility, streak artifacts, and shoulder artifacts). Differences in these scores were assessed by Scheffe's test. At each tube current, scans using AIDR3D had higher scores than those without AIDR3D, which were significant for lung zones (p<0.0001) and all mediastinal measurements (p<0.01). For lung diseases, significant improvements with AIDR3D were frequently observed at 120 and 60 mA. Scans with AIDR3D at 120 mA had significantly higher scores than those without AIDR3D at 240 mA for lung zones and mediastinal streak artifacts (p<0.0001), and slightly higher or equal scores for all other measurements. Scans with AIDR3D at 60 mA were also judged superior or equivalent to those without AIDR3D at 120 mA. For chest CT, AIDR3D provides better image quality and can reduce radiation exposure by 50%.
Automatic seed picking for brachytherapy postimplant validation with 3D CT images.
Zhang, Guobin; Sun, Qiyuan; Jiang, Shan; Yang, Zhiyong; Ma, Xiaodong; Jiang, Haisong
2017-11-01
Postimplant validation is an indispensable part in the brachytherapy technique. It provides the necessary feedback to ensure the quality of operation. The ability to pick implanted seed relates directly to the accuracy of validation. To address it, an automatic approach is proposed for picking implanted brachytherapy seeds in 3D CT images. In order to pick seed configuration (location and orientation) efficiently, the approach starts with the segmentation of seed from CT images using a thresholding filter which based on gray-level histogram. Through the process of filtering and denoising, the touching seed and single seed are classified. The true novelty of this approach is found in the application of the canny edge detection and improved concave points matching algorithm to separate touching seeds. Through the computation of image moments, the seed configuration can be determined efficiently. Finally, two different experiments are designed to verify the performance of the proposed approach: (1) physical phantom with 60 model seeds, and (2) patient data with 16 cases. Through assessment of validated results by a medical physicist, the proposed method exhibited promising results. Experiment on phantom demonstrates that the error of seed location and orientation is within ([Formula: see text]) mm and ([Formula: see text])[Formula: see text], respectively. In addition, the most seed location and orientation error is controlled within 0.8 mm and 3.5[Formula: see text] in all cases, respectively. The average process time of seed picking is 8.7 s per 100 seeds. In this paper, an automatic, efficient and robust approach, performed on CT images, is proposed to determine the implanted seed location as well as orientation in a 3D workspace. Through the experiments with phantom and patient data, this approach also successfully exhibits good performance.
In vivo differentiation of complementary contrast media at dual-energy CT.
Mongan, John; Rathnayake, Samira; Fu, Yanjun; Wang, Runtang; Jones, Ella F; Gao, Dong-Wei; Yeh, Benjamin M
2012-10-01
To evaluate the feasibility of using a commercially available clinical dual-energy computed tomographic (CT) scanner to differentiate the in vivo enhancement due to two simultaneously administered contrast media with complementary x-ray attenuation ratios. Approval from the institutional animal care and use committee was obtained, and National Institutes of Health guidelines for the care and use of laboratory animals were observed. Dual-energy CT was performed in a set of iodine and tungsten solution phantoms and in a rabbit in which iodinated intravenous and bismuth subsalicylate oral contrast media were administered. In addition, a second rabbit was studied after intravenous administration of iodinated and tungsten cluster contrast media. Images were processed to produce virtual monochromatic images that simulated the appearance of conventional single-energy scans, as well as material decomposition images that separate the attenuation due to each contrast medium. Clear separation of each of the contrast media pairs was seen in the phantom and in both in vivo animal models. Separation of bowel lumen from vascular contrast medium allowed visualization of bowel wall enhancement that was obscured by intraluminal bowel contrast medium on conventional CT scans. Separation of two vascular contrast media in different vascular phases enabled acquisition of a perfectly coregistered CT angiogram and venous phase-enhanced CT scan simultaneously in a single examination. Commercially available clinical dual-energy CT scanners can help differentiate the enhancement of selected pairs of complementary contrast media in vivo. © RSNA, 2012.
In Vivo Differentiation of Complementary Contrast Media at Dual-Energy CT
Mongan, John; Rathnayake, Samira; Fu, Yanjun; Wang, Runtang; Jones, Ella F.; Gao, Dong-Wei
2012-01-01
Purpose: To evaluate the feasibility of using a commercially available clinical dual-energy computed tomographic (CT) scanner to differentiate the in vivo enhancement due to two simultaneously administered contrast media with complementary x-ray attenuation ratios. Materials and Methods: Approval from the institutional animal care and use committee was obtained, and National Institutes of Health guidelines for the care and use of laboratory animals were observed. Dual-energy CT was performed in a set of iodine and tungsten solution phantoms and in a rabbit in which iodinated intravenous and bismuth subsalicylate oral contrast media were administered. In addition, a second rabbit was studied after intravenous administration of iodinated and tungsten cluster contrast media. Images were processed to produce virtual monochromatic images that simulated the appearance of conventional single-energy scans, as well as material decomposition images that separate the attenuation due to each contrast medium. Results: Clear separation of each of the contrast media pairs was seen in the phantom and in both in vivo animal models. Separation of bowel lumen from vascular contrast medium allowed visualization of bowel wall enhancement that was obscured by intraluminal bowel contrast medium on conventional CT scans. Separation of two vascular contrast media in different vascular phases enabled acquisition of a perfectly coregistered CT angiogram and venous phase–enhanced CT scan simultaneously in a single examination. Conclusion: Commercially available clinical dual-energy CT scanners can help differentiate the enhancement of selected pairs of complementary contrast media in vivo. © RSNA, 2012 PMID:22778447
DOE Office of Scientific and Technical Information (OSTI.GOV)
McMillan, K; Bostani, M; McNitt-Gray, M
2014-06-15
Purpose: To demonstrate the feasibility of using existing data stored within the DICOM header of certain CT localizer radiographs as a patient size metric for calculating CT size-specific dose estimates (SSDE). Methods: For most Siemens CT scanners, the CT localizer radiograph (topogram) contains a private DICOM field that stores an array of numbers describing AP and LAT attenuation-based measures of patient dimension. The square root of the product of the AP and LAT size data, which provides an estimate of water-equivalent-diameter (WED), was calculated retrospectively from topogram data of 20 patients who received clinically-indicated abdomen/pelvis (n=10) and chest (n=10) scansmore » (WED-topo). In addition, slice-by-slice water-equivalent-diameter (WED-image) and effective diameter (ED-image) values were calculated from the respective image data. Using TG-204 lookup tables, size-dependent conversion factors were determined based upon WED-topo, WED-image and ED-image values. These conversion factors were used with the reported CTDIvol to calculate slice-by-slice SSDE for each method. Averaging over all slices, a single SSDE value was determined for each patient and size metric. Patientspecific SSDE and CTDIvol values were then compared with patientspecific organ doses derived from detailed Monte Carlo simulations of fixed tube current scans. Results: For abdomen/pelvis scans, the average difference between liver dose and CTDIvol, SSDE(WED-topo), SSDE(WED-image), and SSDE(ED-image) was 18.70%, 8.17%, 6.84%, and 7.58%, respectively. For chest scans, the average difference between lung dose and CTDIvol, SSDE(WED-topo), SSDE(WED-image), and SSDE(ED-image) was 25.80%, 3.33%, 4.11%, and 7.66%, respectively. Conclusion: SSDE calculated using WED derived from data in the DICOM header of the topogram was comparable to SSDE calculated using WED and ED derived from axial images; each of these estimated organ dose to within 10% for both abdomen/pelvis and chest CT examinations. The topogrambased method has the advantage that WED data are already provided and therefore available without additional post-processing of the image data. Funding Support: NIH Grant R01-EB017095; Disclosures - Michael McNitt-Gray: Institutional Research Agreement, Siemens AG; Research Support, Siemens AG; Consultant, Flaherty Sensabaugh Bonasso PLLC; Consultant, Fulbright and Jaworski; Disclosures - Cynthia McCollough: Research Grant, Siemens Healthcare.« less
NASA Astrophysics Data System (ADS)
Haneda, Eri; Luo, Jiajia; Can, Ali; Ramani, Sathish; Fu, Lin; De Man, Bruno
2016-05-01
In this study, we implement and compare model based iterative reconstruction (MBIR) with dictionary learning (DL) over MBIR with pairwise pixel-difference regularization, in the context of transportation security. DL is a technique of sparse signal representation using an over complete dictionary which has provided promising results in image processing applications including denoising,1 as well as medical CT reconstruction.2 It has been previously reported that DL produces promising results in terms of noise reduction and preservation of structural details, especially for low dose and few-view CT acquisitions.2 A distinguishing feature of transportation security CT is that scanned baggage may contain items with a wide range of material densities. While medical CT typically scans soft tissues, blood with and without contrast agents, and bones, luggage typically contains more high density materials (i.e. metals and glass), which can produce severe distortions such as metal streaking artifacts. Important factors of security CT are the emphasis on image quality such as resolution, contrast, noise level, and CT number accuracy for target detection. While MBIR has shown exemplary performance in the trade-off of noise reduction and resolution preservation, we demonstrate that DL may further improve this trade-off. In this study, we used the KSVD-based DL3 combined with the MBIR cost-minimization framework and compared results to Filtered Back Projection (FBP) and MBIR with pairwise pixel-difference regularization. We performed a parameter analysis to show the image quality impact of each parameter. We also investigated few-view CT acquisitions where DL can show an additional advantage relative to pairwise pixel difference regularization.
NASA Astrophysics Data System (ADS)
Marchadier, A.; Vidal, C.; Ordureau, S.; Lédée, R.; Léger, C.; Young, M.; Goldberg, M.
2011-03-01
Research on bone and teeth mineralization in animal models is critical for understanding human pathologies. Genetically modified mice represent highly valuable models for the study of osteo/dentinogenesis defects and osteoporosis. Current investigations on mice dental and skeletal phenotype use destructive and time consuming methods such as histology and scanning microscopy. Micro-CT imaging is quicker and provides high resolution qualitative phenotypic description. However reliable quantification of mineralization processes in mouse bone and teeth are still lacking. We have established novel CT imaging-based software for accurate qualitative and quantitative analysis of mouse mandibular bone and molars. Data were obtained from mandibles of mice lacking the Fibromodulin gene which is involved in mineralization processes. Mandibles were imaged with a micro-CT originally devoted to industrial applications (Viscom, X8060 NDT). 3D advanced visualization was performed using the VoxBox software (UsefulProgress) with ray casting algorithms. Comparison between control and defective mice mandibles was made by applying the same transfer function for each 3D data, thus allowing to detect shape, colour and density discrepencies. The 2D images of transverse slices of mandible and teeth were similar and even more accurate than those obtained with scanning electron microscopy. Image processing of the molars allowed the 3D reconstruction of the pulp chamber, providing a unique tool for the quantitative evaluation of dentinogenesis. This new method is highly powerful for the study of oro-facial mineralizations defects in mice models, complementary and even competitive to current histological and scanning microscopy appoaches.
NASA Astrophysics Data System (ADS)
Tesařová, M.; Zikmund, T.; Kaucká, M.; Adameyko, I.; Jaroš, J.; Paloušek, D.; Škaroupka, D.; Kaiser, J.
2016-03-01
Imaging of increasingly complex cartilage in vertebrate embryos is one of the key tasks of developmental biology. This is especially important to study shape-organizing processes during initial skeletal formation and growth. Advanced imaging techniques that are reflecting biological needs give a powerful impulse to push the boundaries of biological visualization. Recently, techniques for contrasting tissues and organs have improved considerably, extending traditional 2D imaging approaches to 3D . X-ray micro computed tomography (μCT), which allows 3D imaging of biological objects including their internal structures with a resolution in the micrometer range, in combination with contrasting techniques seems to be the most suitable approach for non-destructive imaging of embryonic developing cartilage. Despite there are many software-based ways for visualization of 3D data sets, having a real solid model of the studied object might give novel opportunities to fully understand the shape-organizing processes in the developing body. In this feasibility study we demonstrated the full procedure of creating a real 3D object of mouse embryo nasal capsule, i.e. the staining, the μCT scanning combined by the advanced data processing and the 3D printing.
Broadband X-ray Imaging in the Near-Field Region of an Airblast Atomizer
NASA Astrophysics Data System (ADS)
Li, Danyu; Bothell, Julie; Morgan, Timothy; Heindel, Theodore
2017-11-01
The atomization process has a close connection to the efficiency of many spray applications. Examples include improved fuel atomization increasing the combustion efficiency of aircraft engines, or controlled droplet size and spray angle enhancing the quality and speed of the painting process. Therefore, it is vital to understand the physics of the atomization process, but the near-field region is typically optically dense and difficult to probe with laser-based or intrusive measurement techniques. In this project, broadband X-ray radiography and X-ray computed tomography (CT) imaging were performed in the near-field region of a canonical coaxial airblast atomizer. The X-ray absorption rate was enhanced by adding 20% by weight of Potassium Iodide to the liquid phase to increase image contrast. The radiographs provided an estimate of the liquid effective mean path length and spray angle at the nozzle exit for different flow conditions. The reconstructed CT images provided a 3D map of the time-average liquid spray distribution. X-ray imaging was used to quantify the changes in the near-field spray characteristics for various coaxial airblast atomizer flow conditions. Office of Naval Research.
MO-FG-CAMPUS-TeP1-03: Pre-Treatment Surface Imaging Based Collision Detection
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wiant, D; Maurer, J; Liu, H
2016-06-15
Purpose: Modern radiotherapy increasingly employs large immobilization devices, gantry attachments, and couch rotations for treatments. All of which raise the risk of collisions between the patient and the gantry / couch. Collision detection is often achieved by manually checking each couch position in the treatment room and sometimes results in extraneous imaging if collisions are detected after image based setup has begun. In the interest of improving efficiency and avoiding extra imaging, we explore the use of a surface imaging based collision detection model. Methods: Surfaces acquired from AlignRT (VisionRT, London, UK) were transferred in wavefront format to a custommore » Matlab (Mathworks, Natick, MA) software package (CCHECK). Computed tomography (CT) scans acquired at the same time were sent to CCHECK in DICOM format. In CCHECK, binary maps of the surfaces were created and overlaid on the CT images based on the fixed relationship of the AlignRT and CT coordinate systems. Isocenters were added through a graphical user interface (GUI). CCHECK then compares the inputted surfaces to a model of the linear accelerator (linac) to check for collisions at defined gantry and couch positions. Note, CCHECK may be used with or without a CT. Results: The nominal surface image field of view is 650 mm × 900 mm, with variance based on patient position and size. The accuracy of collision detections is primarily based on the linac model and the surface mapping process. The current linac model and mapping process yield detection accuracies on the order of 5 mm, assuming no change in patient posture between surface acquisition and treatment. Conclusions: CCHECK provides a non-ionizing method to check for collisions without the patient in the treatment room. Collision detection accuracy may be improved with more robust linac modeling. Additional gantry attachments (e.g. conical collimators) can be easily added to the model.« less
A web-based computer aided system for liver surgery planning: initial implementation on RayPlus
NASA Astrophysics Data System (ADS)
Luo, Ming; Yuan, Rong; Sun, Zhi; Li, Tianhong; Xie, Qingguo
2016-03-01
At present, computer aided systems for liver surgery design and risk evaluation are widely used in clinical all over the world. However, most systems are local applications that run on high-performance workstations, and the images have to processed offline. Compared with local applications, a web-based system is accessible anywhere and for a range of regardless of relative processing power or operating system. RayPlus (http://rayplus.life.hust.edu.cn), a B/S platform for medical image processing, was developed to give a jump start on web-based medical image processing. In this paper, we implement a computer aided system for liver surgery planning on the architecture of RayPlus. The system consists of a series of processing to CT images including filtering, segmentation, visualization and analyzing. Each processing is packaged into an executable program and runs on the server side. CT images in DICOM format are processed step by to interactive modeling on browser with zero-installation and server-side computing. The system supports users to semi-automatically segment the liver, intrahepatic vessel and tumor from the pre-processed images. Then, surface and volume models are built to analyze the vessel structure and the relative position between adjacent organs. The results show that the initial implementation meets satisfactorily its first-order objectives and provide an accurate 3D delineation of the liver anatomy. Vessel labeling and resection simulation are planned to add in the future. The system is available on Internet at the link mentioned above and an open username for testing is offered.
Modeling respiratory motion for reducing motion artifacts in 4D CT images.
Zhang, Yongbin; Yang, Jinzhong; Zhang, Lifei; Court, Laurence E; Balter, Peter A; Dong, Lei
2013-04-01
Four-dimensional computed tomography (4D CT) images have been recently adopted in radiation treatment planning for thoracic and abdominal cancers to explicitly define respiratory motion and anatomy deformation. However, significant image distortions (artifacts) exist in 4D CT images that may affect accurate tumor delineation and the shape representation of normal anatomy. In this study, the authors present a patient-specific respiratory motion model, based on principal component analysis (PCA) of motion vectors obtained from deformable image registration, with the main goal of reducing image artifacts caused by irregular motion during 4D CT acquisition. For a 4D CT image set of a specific patient, the authors calculated displacement vector fields relative to a reference phase, using an in-house deformable image registration method. The authors then used PCA to decompose each of the displacement vector fields into linear combinations of principal motion bases. The authors have demonstrated that the regular respiratory motion of a patient can be accurately represented by a subspace spanned by three principal motion bases and their projections. These projections were parameterized using a spline model to allow the reconstruction of the displacement vector fields at any given phase in a respiratory cycle. Finally, the displacement vector fields were used to deform the reference CT image to synthesize CT images at the selected phase with much reduced image artifacts. The authors evaluated the performance of the in-house deformable image registration method using benchmark datasets consisting of ten 4D CT sets annotated with 300 landmark pairs that were approved by physicians. The initial large discrepancies across the landmark pairs were significantly reduced after deformable registration, and the accuracy was similar to or better than that reported by state-of-the-art methods. The proposed motion model was quantitatively validated on 4D CT images of a phantom and a lung cancer patient by comparing the synthesized images and the original images at different phases. The synthesized images matched well with the original images. The motion model was used to reduce irregular motion artifacts in the 4D CT images of three lung cancer patients. Visual assessment indicated that the proposed approach could reduce severe image artifacts. The shape distortions around the diaphragm and tumor regions were mitigated in the synthesized 4D CT images. The authors have derived a mathematical model to represent the regular respiratory motion from a patient-specific 4D CT set and have demonstrated its application in reducing irregular motion artifacts in 4D CT images. The authors' approach can mitigate shape distortions of anatomy caused by irregular breathing motion during 4D CT acquisition.
Lechuga, Lawrence; Weidlich, Georg A
2016-09-12
A comparison of image quality and dose delivered between two differing computed tomography (CT) imaging modalities-fan beam and cone beam-was performed. A literature review of quantitative analyses for various image quality aspects such as uniformity, signal-to-noise ratio, artifact presence, spatial resolution, modulation transfer function (MTF), and low contrast resolution was generated. With these aspects quantified, cone beam computed tomography (CBCT) shows a superior spatial resolution to that of fan beam, while fan beam shows a greater ability to produce clear and anatomically correct images with better soft tissue differentiation. The results indicate that fan beam CT produces superior images to that of on-board imaging (OBI) cone beam CT systems, while providing a considerably less dose to the patient.
Weidlich, Georg A.
2016-01-01
A comparison of image quality and dose delivered between two differing computed tomography (CT) imaging modalities—fan beam and cone beam—was performed. A literature review of quantitative analyses for various image quality aspects such as uniformity, signal-to-noise ratio, artifact presence, spatial resolution, modulation transfer function (MTF), and low contrast resolution was generated. With these aspects quantified, cone beam computed tomography (CBCT) shows a superior spatial resolution to that of fan beam, while fan beam shows a greater ability to produce clear and anatomically correct images with better soft tissue differentiation. The results indicate that fan beam CT produces superior images to that of on-board imaging (OBI) cone beam CT systems, while providing a considerably less dose to the patient. PMID:27752404
Real-time CT-video registration for continuous endoscopic guidance
NASA Astrophysics Data System (ADS)
Merritt, Scott A.; Rai, Lav; Higgins, William E.
2006-03-01
Previous research has shown that CT-image-based guidance could be useful for the bronchoscopic assessment of lung cancer. This research drew upon the registration of bronchoscopic video images to CT-based endoluminal renderings of the airway tree. The proposed methods either were restricted to discrete single-frame registration, which took several seconds to complete, or required non-real-time buffering and processing of video sequences. We have devised a fast 2D/3D image registration method that performs single-frame CT-Video registration in under 1/15th of a second. This allows the method to be used for real-time registration at full video frame rates without significantly altering the physician's behavior. The method achieves its speed through a gradient-based optimization method that allows most of the computation to be performed off-line. During live registration, the optimization iteratively steps toward the locally optimal viewpoint at which a CT-based endoluminal view is most similar to a current bronchoscopic video frame. After an initial registration to begin the process (generally done in the trachea for bronchoscopy), subsequent registrations are performed in real-time on each incoming video frame. As each new bronchoscopic video frame becomes available, the current optimization is initialized using the previous frame's optimization result, allowing continuous guidance to proceed without manual re-initialization. Tests were performed using both synthetic and pre-recorded bronchoscopic video. The results show that the method is robust to initialization errors, that registration accuracy is high, and that continuous registration can proceed on real-time video at >15 frames per sec. with minimal user-intervention.
Kaseno, Kenichi; Hisazaki, Kaori; Nakamura, Kohki; Ikeda, Etsuko; Hasegawa, Kanae; Aoyama, Daisetsu; Shiomi, Yuichiro; Ikeda, Hiroyuki; Morishita, Tetsuji; Ishida, Kentaro; Amaya, Naoki; Uzui, Hiroyasu; Tada, Hiroshi
2018-04-14
Intracardiac echocardiographic (ICE) imaging might be useful for integrating three-dimensional computed tomographic (CT) images for left atrial (LA) catheter navigation during atrial fibrillation (AF) ablation. However, the optimal CT image integration method using ICE has not been established. This study included 52 AF patients who underwent successful circumferential pulmonary vein isolation (CPVI). In all patients, CT image integration was performed after the CPVI with the following two methods: (1) using ICE images of the LA derived from the right atrium and right ventricular outflow tract (RA-merge) and (2) using ICE images of the LA directly derived from the LA added to the image for the RA-merge (LA-merge). The accuracy of these two methods was assessed by the distances between the integrated CT image and ICE image (ICE-to-CT distance), and between the CT image and actual ablated sites for the CPVI (CT-to-ABL distance). The mean ICE-to-CT distance was comparable between the two methods (RA-merge = 1.6 ± 0.5 mm, LA-merge = 1.7 ± 0.4 mm; p = 0.33). However, the mean CT-to-ABL distance was shorter for the LA-merge (2.1 ± 0.6 mm) than RA-merge (2.5 ± 0.8 mm; p < 0.01). The LA, especially the left-sided PVs and LA roof, was more sharply delineated by direct LA imaging, and whereas the greatest CT-to-ABL distance was observed at the roof portion of the left superior PV (3.7 ± 2.8 mm) after the RA-merge, it improved to 2.6 ± 1.9 mm after the LA-merge (p < 0.01). Additional ICE images of the LA directly acquired from the LA might lead to a greater accuracy of the CT image integration for the CVPI.
Advanced imaging programs: maximizing a multislice CT investment.
Falk, Robert
2008-01-01
Advanced image processing has moved from a luxury to a necessity in the practice of medicine. A hospital's adoption of sophisticated 3D imaging entails several important steps with many factors to consider in order to be successful. Like any new hospital program, 3D post-processing should be introduced through a strategic planning process that includes administrators, physicians, and technologists to design, implement, and market a program that is scalable-one that minimizes up front costs while providing top level service. This article outlines the steps for planning, implementation, and growth of an advanced imaging program.
Leiva-Salinas, C; Flors, L; Gras, P; Más-Estellés, F; Lemercier, P; Patrie, J T; Wintermark, M; Martí-Bonmatí, L
2014-01-01
CT is the imaging modality of choice to study the paranasal sinuses; unfortunately, it involves significant radiation dose. Our aim was to assess the diagnostic validity, image quality, and radiation-dose savings of dental conebeam CT in the evaluation of patients with suspected inflammatory disorders of the paranasal sinuses. We prospectively studied 40 patients with suspected inflammatory disorders of the sinuses with dental conebeam CT and standard CT. Two radiologists analyzed the images independently, blinded to clinical information. The image quality of both techniques and the diagnostic validity of dental conebeam CT compared with the reference standard CT were assessed by using 3 different scoring systems. Image noise, signal-to-noise ratio, and contrast-to-noise ratio were calculated for both techniques. The absorbed radiation dose to the lenses and thyroid and parotid glands was measured by using a phantom and dosimeter chips. The effective radiation dose for CT was calculated. All dental conebeam CT scans were judged of diagnostic quality. Compared with CT, the conebeam CT image noise was 37.3% higher (P < .001) and the SNR of the bone was 75% lower (P < .001). The effective dose of our conebeam CT protocol was 23 μSv. Compared with CT, the absorbed radiation dose to the lenses and parotid and thyroid glands with conebeam CT was 4%, 7.8%, and 7.3% of the dose delivered to the same organs by conventional CT (P < .001). Dental conebeam CT is a valid imaging procedure for the evaluation of patients with inflammatory sinonasal disorders. © 2014 by American Journal of Neuroradiology.
Hoffman, John M; Noo, Frédéric; Young, Stefano; Hsieh, Scott S; McNitt-Gray, Michael
2018-06-01
To facilitate investigations into the impacts of acquisition and reconstruction parameters on quantitative imaging, radiomics and CAD using CT imaging, we previously released an open source implementation of a conventional weighted filtered backprojection reconstruction called FreeCT_wFBP. Our purpose was to extend that work by providing an open-source implementation of a model-based iterative reconstruction method using coordinate descent optimization, called FreeCT_ICD. Model-based iterative reconstruction offers the potential for substantial radiation dose reduction, but can impose substantial computational processing and storage requirements. FreeCT_ICD is an open source implementation of a model-based iterative reconstruction method that provides a reasonable tradeoff between these requirements. This was accomplished by adapting a previously proposed method that allows the system matrix to be stored with a reasonable memory requirement. The method amounts to describing the attenuation coefficient using rotating slices that follow the helical geometry. In the initially-proposed version, the rotating slices are themselves described using blobs. We have replaced this description by a unique model that relies on tri-linear interpolation together with the principles of Joseph's method. This model offers an improvement in memory requirement while still allowing highly accurate reconstruction for conventional CT geometries. The system matrix is stored column-wise and combined with an iterative coordinate descent (ICD) optimization. The result is FreeCT_ICD, which is a reconstruction program developed on the Linux platform using C++ libraries and the open source GNU GPL v2.0 license. The software is capable of reconstructing raw projection data of helical CT scans. In this work, the software has been described and evaluated by reconstructing datasets exported from a clinical scanner which consisted of an ACR accreditation phantom dataset and a clinical pediatric thoracic scan. For the ACR phantom, image quality was comparable to clinical reconstructions as well as reconstructions using open-source FreeCT_wFBP software. The pediatric thoracic scan also yielded acceptable results. In addition, we did not observe any deleterious impact in image quality associated with the utilization of rotating slices. These evaluations also demonstrated reasonable tradeoffs in storage requirements and computational demands. FreeCT_ICD is an open-source implementation of a model-based iterative reconstruction method that extends the capabilities of previously released open source reconstruction software and provides the ability to perform vendor-independent reconstructions of clinically acquired raw projection data. This implementation represents a reasonable tradeoff between storage and computational requirements and has demonstrated acceptable image quality in both simulated and clinical image datasets. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Rapid Prototyping Integrated With Nondestructive Evaluation and Finite Element Analysis
NASA Technical Reports Server (NTRS)
Abdul-Aziz, Ali; Baaklini, George Y.
2001-01-01
Most reverse engineering approaches involve imaging or digitizing an object then creating a computerized reconstruction that can be integrated, in three dimensions, into a particular design environment. Rapid prototyping (RP) refers to the practical ability to build high-quality physical prototypes directly from computer aided design (CAD) files. Using rapid prototyping, full-scale models or patterns can be built using a variety of materials in a fraction of the time required by more traditional prototyping techniques (refs. 1 and 2). Many software packages have been developed and are being designed to tackle the reverse engineering and rapid prototyping issues just mentioned. For example, image processing and three-dimensional reconstruction visualization software such as Velocity2 (ref. 3) are being used to carry out the construction process of three-dimensional volume models and the subsequent generation of a stereolithography file that is suitable for CAD applications. Producing three-dimensional models of objects from computed tomography (CT) scans is becoming a valuable nondestructive evaluation methodology (ref. 4). Real components can be rendered and subjected to temperature and stress tests using structural engineering software codes. For this to be achieved, accurate high-resolution images have to be obtained via CT scans and then processed, converted into a traditional file format, and translated into finite element models. Prototyping a three-dimensional volume of a composite structure by reading in a series of two-dimensional images generated via CT and by using and integrating commercial software (e.g. Velocity2, MSC/PATRAN (ref. 5), and Hypermesh (ref. 6)) is being applied successfully at the NASA Glenn Research Center. The building process from structural modeling to the analysis level is outlined in reference 7. Subsequently, a stress analysis of a composite cooling panel under combined thermomechanical loading conditions was performed to validate this process.
Recent Developments and Applications of Radiation/Detection Technology in Tsinghua University
NASA Astrophysics Data System (ADS)
Kang, Ke-Jun
2010-03-01
Nuclear technology applications have been very important research fields in Tsinghua University (THU) for more than 50 years. This paper describes two major directions and related projects running in THU concerning nuclear technology applications for radiation imaging and nuclear technology applications for astrophysics. Radiation imaging is a significant application of nuclear technology for all kinds of real world needs including security inspections, anti-smuggling operations, and medicine. The current improved imaging systems give much higher quality radiation images. THU has produced accelerating tubes for both industrial and medical accelerators with energy levels ranging from 2.5˜20Mev. Detectors have been produced for medical and industrial imaging as well as for high energy physics experiments such as the MRPC with fast time and position resolutions. DR and CT systems for radiation imaging systems have been continuously improved with new system designs and improved algorithms for image reconstruction and processing. Two important new key initiatives are the dual-energy radiography and dual-energy CT systems. Dual-energy CT imaging improves material discrimination by providing both the electron density and the atomic number distribution of scanned objects. Finally, this paper also introduces recent developments related to the hard X-ray modulation telescope (HXMT) provided by THU.
O'Donnell, C; Iino, M; Mansharan, K; Leditscke, J; Woodford, N
2011-02-25
CT scanning of the deceased is an established technique performed on all individuals admitted to VIFM over the last 5 years. It is used primarily to assist pathologists in determining cause and manner of death but is also invaluable for identification of unknown deceased individuals where traditional methods are not possible. Based on this experience, CT scanning was incorporated into phase 2 of the Institute's DVI process for the 2009 Victorian bushfires. All deceased individuals and fragmented remains admitted to the mortuary were CT scanned in their body bags using established protocols. Images were reviewed by 2 teams of 2 radiologists experienced in forensic imaging and the findings transcribed onto a data sheet constructed specifically for the DVI exercise. The contents of 255 body bags were examined in the 28 days following the fires. 164 missing persons were included in the DVI process with 163 deceased individuals eventually identified. CT contributed to this identification in 161 persons. In 2 cases, radiologists were unable to recognize commingled remains. CT was utilized in the initial triage of each bag's contents. If radiological evaluation determined that bodies were incomplete then this information was provided to search teams who revisited the scenes of death. CT was helpful in differentiation of human from non-human remains in 8 bags, recognition of human/animal commingling in 10 bags and human commingling in 6 bags. In 61% of cases gender was able to be determined on CT using a novel technique of genitalia detection and in all but 2 cases this was correct. Age range was able to be determined on CT in 94% with an accuracy of 76%. Specific identification features detected on CT included the presence of disease (14 disease entities in 13 cases), medical devices (26 devices in 19 cases) and 274 everyday metallic items associated with the remains of 135 individuals. CT scanning provided useful information prior to autopsy by flagging likely findings including the presence of non-human remains, at the time of autopsy by assisting in the localization of identifying features in heavily disfigured bodies, and after autopsy by retrospective review of images for clarification of issues that arose at the time of pathologist case review. In view of the success of CT scanning in this mass disaster, DVI administrators should explore the incorporation of CT services into their disaster plans. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
Tracking Organs Composed of One or Multiple Regions Using Geodesic Active Region Models
NASA Astrophysics Data System (ADS)
Martínez, A.; Jiménez, J. J.
In radiotherapy treatment it is very important to find out the target organs on the medical image sequence in order to determine and apply the proper dose. The techniques to achieve this goal can be classified into extrinsic and intrinsic. Intrinsic techniques only use image processing with medical images associated to the radiotherapy
ImaSim, a software tool for basic education of medical x-ray imaging in radiotherapy and radiology
NASA Astrophysics Data System (ADS)
Landry, Guillaume; deBlois, François; Verhaegen, Frank
2013-11-01
Introduction: X-ray imaging is an important part of medicine and plays a crucial role in radiotherapy. Education in this field is mostly limited to textbook teaching due to equipment restrictions. A novel simulation tool, ImaSim, for teaching the fundamentals of the x-ray imaging process based on ray-tracing is presented in this work. ImaSim is used interactively via a graphical user interface (GUI). Materials and methods: The software package covers the main x-ray based medical modalities: planar kilo voltage (kV), planar (portal) mega voltage (MV), fan beam computed tomography (CT) and cone beam CT (CBCT) imaging. The user can modify the photon source, object to be imaged and imaging setup with three-dimensional editors. Objects are currently obtained by combining blocks with variable shapes. The imaging of three-dimensional voxelized geometries is currently not implemented, but can be added in a later release. The program follows a ray-tracing approach, ignoring photon scatter in its current implementation. Simulations of a phantom CT scan were generated in ImaSim and were compared to measured data in terms of CT number accuracy. Spatial variations in the photon fluence and mean energy from an x-ray tube caused by the heel effect were estimated from ImaSim and Monte Carlo simulations and compared. Results: In this paper we describe ImaSim and provide two examples of its capabilities. CT numbers were found to agree within 36 Hounsfield Units (HU) for bone, which corresponds to a 2% attenuation coefficient difference. ImaSim reproduced the heel effect reasonably well when compared to Monte Carlo simulations. Discussion: An x-ray imaging simulation tool is made available for teaching and research purposes. ImaSim provides a means to facilitate the teaching of medical x-ray imaging.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gratama van Andel, H. A. F.; Venema, H. W.; Streekstra, G. J.
For clear visualization of vessels in CT angiography (CTA) images of the head and neck using maximum intensity projection (MIP) or volume rendering (VR) bone has to be removed. In the past we presented a fully automatic method to mask the bone [matched mask bone elimination (MMBE)] for this purpose. A drawback is that vessels adjacent to bone may be partly masked as well. We propose a modification, multiscale MMBE, which reduces this problem by using images at two scales: a higher resolution than usual for image processing and a lower resolution to which the processed images are transformed formore » use in the diagnostic process. A higher in-plane resolution is obtained by the use of a sharper reconstruction kernel. The out-of-plane resolution is improved by deconvolution or by scanning with narrower collimation. The quality of the mask that is used to remove bone is improved by using images at both scales. After masking, the desired resolution for the normal clinical use of the images is obtained by blurring with Gaussian kernels of appropriate widths. Both methods (multiscale and original) were compared in a phantom study and with clinical CTA data sets. With the multiscale approach the width of the strip of soft tissue adjacent to the bone that is masked can be reduced from 1.0 to 0.2 mm without reducing the quality of the bone removal. The clinical examples show that vessels adjacent to bone are less affected and therefore better visible. Images processed with multiscale MMBE have a slightly higher noise level or slightly reduced resolution compared with images processed by the original method and the reconstruction and processing time is also somewhat increased. Nevertheless, multiscale MMBE offers a way to remove bone automatically from CT angiography images without affecting the integrity of the blood vessels. The overall image quality of MIP or VR images is substantially improved relative to images processed with the original MMBE method.« less
ERIC Educational Resources Information Center
Popyk, Marilyn K.
1986-01-01
Discusses the new automated office and its six major technologies (data processing, word processing, graphics, image, voice, and networking), the information processing cycle (input, processing, output, distribution/communication, and storage and retrieval), ergonomics, and ways to expand office education classes (versus class instruction). (CT)
Wen, Di; Nye, Katelyn; Zhou, Bo; Gilkeson, Robert C; Gupta, Amit; Ranim, Shiraz; Couturier, Spencer; Wilson, David L
2018-03-01
We have developed a technique to image coronary calcium, an excellent biomarker for atherosclerotic disease, using low cost, low radiation dual energy (DE) chest radiography, with potential for widespread screening from an already ordered exam. Our dual energy coronary calcium (DECC) processing method included automatic heart silhouette segmentation, sliding organ registration and scatter removal to create a bone-image-like, coronary calcium image with significant reduction in motion artifacts and improved calcium conspicuity compared to standard, clinically available DE processing. Experiments with a physical dynamic cardiac phantom showed that DECC processing reduced 73% of misregistration error caused by cardiac motion over a wide range of heart rates and x-ray radiation exposures. Using the functional measurement test (FMT), we determined significant image quality improvement in clinical images with DECC processing (p < 0.0001), where DECC images were chosen best in 94% of human readings. Comparing DECC images to registered and projected CT calcium images, we found good correspondence between the size and location of calcification signals. In a very preliminary coronary calcium ROC study, we used CT Agatston calcium score >50 as the gold standard for an actual positive test result. AUC performance was significantly improved from 0.73 ± 0.14 with standard DE to 0.87 ± 0.10 with DECC (p = 0.0095) for this limited set of surgical patient data biased towards heavy calcifications. The proposed DECC processing shows good potential for coronary calcium detection in DE chest radiography, giving impetus for a larger clinical evaluation. Copyright © 2018. Published by Elsevier Ltd.
Sharp, G C; Kandasamy, N; Singh, H; Folkert, M
2007-10-07
This paper shows how to significantly accelerate cone-beam CT reconstruction and 3D deformable image registration using the stream-processing model. We describe data-parallel designs for the Feldkamp, Davis and Kress (FDK) reconstruction algorithm, and the demons deformable registration algorithm, suitable for use on a commodity graphics processing unit. The streaming versions of these algorithms are implemented using the Brook programming environment and executed on an NVidia 8800 GPU. Performance results using CT data of a preserved swine lung indicate that the GPU-based implementations of the FDK and demons algorithms achieve a substantial speedup--up to 80 times for FDK and 70 times for demons when compared to an optimized reference implementation on a 2.8 GHz Intel processor. In addition, the accuracy of the GPU-based implementations was found to be excellent. Compared with CPU-based implementations, the RMS differences were less than 0.1 Hounsfield unit for reconstruction and less than 0.1 mm for deformable registration.
Building a medical image processing algorithm verification database
NASA Astrophysics Data System (ADS)
Brown, C. Wayne
2000-06-01
The design of a database containing head Computed Tomography (CT) studies is presented, along with a justification for the database's composition. The database will be used to validate software algorithms that screen normal head CT studies from studies that contain pathology. The database is designed to have the following major properties: (1) a size sufficient for statistical viability, (2) inclusion of both normal (no pathology) and abnormal scans, (3) inclusion of scans due to equipment malfunction, technologist error, and uncooperative patients, (4) inclusion of data sets from multiple scanner manufacturers, (5) inclusion of data sets from different gender and age groups, and (6) three independent diagnosis of each data set. Designed correctly, the database will provide a partial basis for FDA (United States Food and Drug Administration) approval of image processing algorithms for clinical use. Our goal for the database is the proof of viability of screening head CT's for normal anatomy using computer algorithms. To put this work into context, a classification scheme for 'computer aided diagnosis' systems is proposed.
NASA Astrophysics Data System (ADS)
Mori, Shinichiro; Kanematsu, Nobuyuki; Asakura, Hiroshi; Endo, Masahiro
2007-02-01
The concept of internal target volume (ITV) is highly significant in radiotherapy for the lung, an organ which is hampered by organ motion. To date, different methods to obtain the ITV have been published and are therefore available. To define ITV, we developed a new method by adapting a time filter to the four-dimensional CT scan technique (4DCT) which is projection-data processing (4D projection data maximum attenuation (4DPM)), and compared it with reconstructed image processing (4D image maximum intensity projection (4DIM)) using a phantom and clinical evaluations. 4DIM and 4DPM captured accurate maximum intensity volume (MIV), that is tumour encompassing volume, easily. Although 4DIM increased the CT number 1.8 times higher than 4DPM, 4DPM provided the original tumour CT number for MIV via a reconstruction algorithm. In the patient with lung fibrosis honeycomb, the MIV with 4DIM is 0.7 cm larger than that for cine imaging in the cranio-caudal direction. 4DPM therefore provided an accurate MIV independent of patient characteristics and reconstruction conditions. These findings indicate the usefulness of 4DPM in determining ITV in radiotherapy.
Niu, Qiang; Chi, Xiaoyi; Leu, Ming C; Ochoa, Jorge
2008-01-01
This paper describes image processing, geometric modeling and data management techniques for the development of a virtual bone surgery system. Image segmentation is used to divide CT scan data into different segments representing various regions of the bone. A region-growing algorithm is used to extract cortical bone and trabecular bone structures systematically and efficiently. Volume modeling is then used to represent the bone geometry based on the CT scan data. Material removal simulation is achieved by continuously performing Boolean subtraction of the surgical tool model from the bone model. A quadtree-based adaptive subdivision technique is developed to handle the large set of data in order to achieve the real-time simulation and visualization required for virtual bone surgery. A Marching Cubes algorithm is used to generate polygonal faces from the volumetric data. Rendering of the generated polygons is performed with the publicly available VTK (Visualization Tool Kit) software. Implementation of the developed techniques consists of developing a virtual bone-drilling software program, which allows the user to manipulate a virtual drill to make holes with the use of a PHANToM device on a bone model derived from real CT scan data.
CT Image Sequence Restoration Based on Sparse and Low-Rank Decomposition
Gou, Shuiping; Wang, Yueyue; Wang, Zhilong; Peng, Yong; Zhang, Xiaopeng; Jiao, Licheng; Wu, Jianshe
2013-01-01
Blurry organ boundaries and soft tissue structures present a major challenge in biomedical image restoration. In this paper, we propose a low-rank decomposition-based method for computed tomography (CT) image sequence restoration, where the CT image sequence is decomposed into a sparse component and a low-rank component. A new point spread function of Weiner filter is employed to efficiently remove blur in the sparse component; a wiener filtering with the Gaussian PSF is used to recover the average image of the low-rank component. And then we get the recovered CT image sequence by combining the recovery low-rank image with all recovery sparse image sequence. Our method achieves restoration results with higher contrast, sharper organ boundaries and richer soft tissue structure information, compared with existing CT image restoration methods. The robustness of our method was assessed with numerical experiments using three different low-rank models: Robust Principle Component Analysis (RPCA), Linearized Alternating Direction Method with Adaptive Penalty (LADMAP) and Go Decomposition (GoDec). Experimental results demonstrated that the RPCA model was the most suitable for the small noise CT images whereas the GoDec model was the best for the large noisy CT images. PMID:24023764
Metal artifact reduction through MVCBCT and kVCT in radiotherapy
NASA Astrophysics Data System (ADS)
Liugang, Gao; Hongfei, Sun; Xinye, Ni; Mingming, Fang; Zheng, Cao; Tao, Lin
2016-11-01
This study proposes a new method for removal of metal artifacts from megavoltage cone beam computed tomography (MVCBCT) and kilovoltage CT (kVCT) images. Both images were combined to obtain prior image, which was forward projected to obtain surrogate data and replace metal trace in the uncorrected kVCT image. The corrected image was then reconstructed through filtered back projection. A similar radiotherapy plan was designed using the theoretical CT image, the uncorrected kVCT image, and the corrected image. The corrected images removed most metal artifacts, and the CT values were accurate. The corrected image also distinguished the hollow circular hole at the center of the metal. The uncorrected kVCT image did not display the internal structure of the metal, and the hole was misclassified as metal portion. Dose distribution calculated based on the corrected image was similar to that based on the theoretical CT image. The calculated dose distribution also evidently differed between the uncorrected kVCT image and the theoretical CT image. The use of the combined kVCT and MVCBCT to obtain the prior image can distinctly improve the quality of CT images containing large metal implants.
Tan, A C; Richards, R
1989-01-01
Three-dimensional (3D) medical graphics is becoming popular in clinical use on tomographic scanners. Research work in 3D reconstructive display of computerized tomography (CT) and magnetic resonance imaging (MRI) scans on conventional computers has produced many so-called pseudo-3D images. The quality of these images depends on the rendering algorithm, the coarseness of the digitized object, the number of grey levels and the image screen resolution. CT and MRI data are fundamentally voxel based and they produce images that are coarse because of the resolution of the data acquisition system. 3D images produced by the Z-buffer depth shading technique suffer loss of detail when complex objects with fine textural detail need to be displayed. Attempts have been made to improve the display of voxel objects, and existing techniques have shown the improvement possible using these post-processing algorithms. The improved rendering technique works on the Z-buffer image to generate a shaded image using a single light source in any direction. The effectiveness of the technique in generating a shaded image has been shown to be a useful means of presenting 3D information for clinical use.
Liver CT image processing: a short introduction of the technical elements.
Masutani, Y; Uozumi, K; Akahane, Masaaki; Ohtomo, Kuni
2006-05-01
In this paper, we describe the technical aspects of image analysis for liver diagnosis and treatment, including the state-of-the-art of liver image analysis and its applications. After discussion on modalities for liver image analysis, various technical elements for liver image analysis such as registration, segmentation, modeling, and computer-assisted detection are covered with examples performed with clinical data sets. Perspective in the imaging technologies is also reviewed and discussed.
NASA Astrophysics Data System (ADS)
Magri, Alphonso; Krol, Andrzej; Lipson, Edward; Mandel, James; McGraw, Wendy; Lee, Wei; Tillapaugh-Fay, Gwen; Feiglin, David
2009-02-01
This study was undertaken to register 3D parametric breast images derived from Gd-DTPA MR and F-18-FDG PET/CT dynamic image series. Nonlinear curve fitting (Levenburg-Marquardt algorithm) based on realistic two-compartment models was performed voxel-by-voxel separately for MR (Brix) and PET (Patlak). PET dynamic series consists of 50 frames of 1-minute duration. Each consecutive PET image was nonrigidly registered to the first frame using a finite element method and fiducial skin markers. The 12 post-contrast MR images were nonrigidly registered to the precontrast frame using a free-form deformation (FFD) method. Parametric MR images were registered to parametric PET images via CT using FFD because the first PET time frame was acquired immediately after the CT image on a PET/CT scanner and is considered registered to the CT image. We conclude that nonrigid registration of PET and MR parametric images using CT data acquired during PET/CT scan and the FFD method resulted in their improved spatial coregistration. The success of this procedure was limited due to relatively large target registration error, TRE = 15.1+/-7.7 mm, as compared to spatial resolution of PET (6-7 mm), and swirling image artifacts created in MR parametric images by the FFD. Further refinement of nonrigid registration of PET and MR parametric images is necessary to enhance visualization and integration of complex diagnostic information provided by both modalities that will lead to improved diagnostic performance.
Hybrid SPECT-CT and PET-CT imaging of differentiated thyroid carcinoma.
Wong, K K; Zarzhevsky, N; Cahill, J M; Frey, K A; Avram, A M
2009-10-01
Hybrid imaging modalities such as radioiodine single photon emission CT with integrated CT ((131)I SPECT-CT) and 2-(fluorine-18)-fluoro-2-deoxy-D-glucose positron emission tomography with integrated CT (FDG PET-CT) allow the rapid and efficient fusion of functional and anatomic images, and provide diagnostic information that may influence management decisions in patients with differentiated thyroid carcinoma (DTC). Diagnostic localisation and therapy of these tumours are dependent upon their capacity to concentrate radioiodine ((131)I) via uptake through the sodium-iodide symporter and retention within the tumour. The prognosis for most patients with DTC is favourable, although controversy exists regarding the role of post-operative (131)I therapy in patients at low-risk for disease. Accurate identification of functional thyroid tissue (benign or malignant) using diagnostic (131)I planar scintigraphy complemented by SPECT-CT imaging enables the completion of post-operative staging and patient risk stratification prior to (131)I therapy administration. In patients with non-iodine-avid tumours (negative (131)I scan but elevated thyroglobulin indicative of persistent or recurrent disease), FDG PET-CT is used to identify tumours with enhanced glucose metabolism and to localise the source of thyroglobulin production. The CT component of this hybrid technology provides anatomic localisation of activity and allows CT-based attenuation correction of PET images. Images from 15 patients illustrate the applications of (131)I SPECT-CT and FDG PET-CT.
Nesvacil, Nicole; Schmid, Maximilian P; Pötter, Richard; Kronreif, Gernot; Kirisits, Christian
To investigate the feasibility of a treatment planning workflow for three-dimensional image-guided cervix cancer brachytherapy, combining volumetric transrectal ultrasound (TRUS) for target definition with CT for dose optimization to organs at risk (OARs), for settings with no access to MRI. A workflow for TRUS/CT-based volumetric treatment planning was developed, based on a customized system including ultrasound probe, stepper unit, and software for image volume acquisition. A full TRUS/CT-based workflow was simulated in a clinical case and compared with MR- or CT-only delineation. High-risk clinical target volume was delineated on TRUS, and OARs were delineated on CT. Manually defined tandem/ring applicator positions on TRUS and CT were used as a reference for rigid registration of the image volumes. Treatment plan optimization for TRUS target and CT organ volumes was performed and compared to MRI and CT target contours. TRUS/CT-based contouring, applicator reconstruction, image fusion, and treatment planning were feasible, and the full workflow could be successfully demonstrated. The TRUS/CT plan fulfilled all clinical planning aims. Dose-volume histogram evaluation of the TRUS/CT-optimized plan (high-risk clinical target volume D 90 , OARs D 2cm³ for) on different image modalities showed good agreement between dose values reported for TRUS/CT and MRI-only reference contours and large deviations for CT-only target parameters. A TRUS/CT-based workflow for full three-dimensional image-guided cervix brachytherapy treatment planning seems feasible and may be clinically comparable to MRI-based treatment planning. Further development to solve challenges with applicator definition in the TRUS volume is required before systematic applicability of this workflow. Copyright © 2016 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.
Ichikawa, Yasutaka; Kitagawa, Kakuya; Nagasawa, Naoki; Murashima, Shuichi; Sakuma, Hajime
2013-08-09
The recently developed model-based iterative reconstruction (MBIR) enables significant reduction of image noise and artifacts, compared with adaptive statistical iterative reconstruction (ASIR) and filtered back projection (FBP). The purpose of this study was to evaluate lesion detectability of low-dose chest computed tomography (CT) with MBIR in comparison with ASIR and FBP. Chest CT was acquired with 64-slice CT (Discovery CT750HD) with standard-dose (5.7 ± 2.3 mSv) and low-dose (1.6 ± 0.8 mSv) conditions in 55 patients (aged 72 ± 7 years) who were suspected of lung disease on chest radiograms. Low-dose CT images were reconstructed with MBIR, ASIR 50% and FBP, and standard-dose CT images were reconstructed with FBP, using a reconstructed slice thickness of 0.625 mm. Two observers evaluated the image quality of abnormal lung and mediastinal structures on a 5-point scale (Score 5 = excellent and score 1 = non-diagnostic). The objective image noise was also measured as the standard deviation of CT intensity in the descending aorta. The image quality score of enlarged mediastinal lymph nodes on low-dose MBIR CT (4.7 ± 0.5) was significantly improved in comparison with low-dose FBP and ASIR CT (3.0 ± 0.5, p = 0.004; 4.0 ± 0.5, p = 0.02, respectively), and was nearly identical to the score of standard-dose FBP image (4.8 ± 0.4, p = 0.66). Concerning decreased lung attenuation (bulla, emphysema, or cyst), the image quality score on low-dose MBIR CT (4.9 ± 0.2) was slightly better compared to low-dose FBP and ASIR CT (4.5 ± 0.6, p = 0.01; 4.6 ± 0.5, p = 0.01, respectively). There were no significant differences in image quality scores of visualization of consolidation or mass, ground-glass attenuation, or reticular opacity among low- and standard-dose CT series. Image noise with low-dose MBIR CT (11.6 ± 1.0 Hounsfield units (HU)) were significantly lower than with low-dose ASIR (21.1 ± 2.6 HU, p < 0.0005), low-dose FBP CT (30.9 ± 3.9 HU, p < 0.0005), and standard-dose FBP CT (16.6 ± 2.3 HU, p < 0.0005). MBIR shows greater potential than ASIR for providing diagnostically acceptable low-dose CT without compromising image quality. With radiation dose reduction of >70%, MBIR can provide equivalent lesion detectability of standard-dose FBP CT.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ali, I; Ahmad, S; Alsbou, N
Purpose: A motion algorithm was developed to extract actual length, CT-numbers and motion amplitude of a mobile target imaged with cone-beam-CT (CBCT) retrospective to image-reconstruction. Methods: The motion model considered a mobile target moving with a sinusoidal motion and employed three measurable parameters: apparent length, CT number level and gradient of a mobile target obtained from CBCT images to extract information about the actual length and CT number value of the stationary target and motion amplitude. The algorithm was verified experimentally with a mobile phantom setup that has three targets with different sizes manufactured from homogenous tissue-equivalent gel material embeddedmore » into a thorax phantom. The phantom moved sinusoidal in one-direction using eight amplitudes (0–20mm) and a frequency of 15-cycles-per-minute. The model required imaging parameters such as slice thickness, imaging time. Results: This motion algorithm extracted three unknown parameters: length of the target, CT-number-level, motion amplitude for a mobile target retrospective to CBCT image reconstruction. The algorithm relates three unknown parameters to measurable apparent length, CT-number-level and gradient for well-defined mobile targets obtained from CBCT images. The motion model agreed with measured apparent lengths which were dependent on actual length of the target and motion amplitude. The cumulative CT-number for a mobile target was dependent on CT-number-level of the stationary target and motion amplitude. The gradient of the CT-distribution of mobile target is dependent on the stationary CT-number-level, actual target length along the direction of motion, and motion amplitude. Motion frequency and phase did not affect the elongation and CT-number distributions of mobile targets when imaging time included several motion cycles. Conclusion: The motion algorithm developed in this study has potential applications in diagnostic CT imaging and radiotherapy to extract actual length, size and CT-numbers distorted by motion in CBCT imaging. The model provides further information about motion of the target.« less
Qiu, L L; Li, S; Bai, Y X
2016-06-01
To develop surgical templates for orthodontic miniscrew implantation based on cone-beam CT(CBCT)three-dimensional(3D)images and to evaluate the safety and stability of implantation guided by the templates. DICOM data obtained in patients who had CBCT scans taken were processed using Mimics software, and 3D images of teeth and maxillary bone were acquired. Meanwhile, 3D images of miniscrews were acquired using Solidworks software and processed with Mimics software. Virtual position of miniscrews was determined based on 3D images of teeth, bone, and miniscrews. 3D virtual templates were designed according to the virtual implantation plans. STL files were output and the real templates were fabricated with stereolithographic appliance(SLA). Postoperative CBCT scans were used to evaluate the implantation safety and the stability of miniscrews were investigated. All the templates were positioned accurately and kept stable throughout the implantation process. No root damage was found. The deviations were(1.73±0.65)mm at the corona, and(1.28±0.82)mm at the apex, respectively. The stability of miniscrews was fairly well. Surgical templates for miniscrew implantation could be acquired based on 3D CBCT images and fabricated with SLA. Implantation guided by these templates was safe and stable.
NASA Astrophysics Data System (ADS)
Mulyadin; Dewang, Syamsir; Abdullah, Bualkar; Tahir, Dahlang
2018-03-01
In this study, the image quality of CT scan using phantom American College of Radiology (ACR) was determined. Scanning multidetector CT is used to know the image quality parameters by using a solid phantom containing four modules and primarily from materials that are equivalent to water. Each module is 4 cm in diameter and 20 cm in diameter. There is white alignment marks painted white to reflect the alignment laser and there are also “HEAD”, “FOOT”, and “TOP” marks on the phantom to help align. This test obtains CT images of each module according to the routine inspection protocol of the head. Acceptance of image quality obtained for determination: CT Number Accuracy (CTN), CT Number Uniformity and Noise, Linearity CT Number, Slice Technique, Low Contrast Resolution and High Contrast Resolution represent image quality parameters. In testing CT Number Accuracy (CTN), CT Uniform number and Noise are in the range of tolerable values allowed. In the test, Linearity CT Number obtained correlation value above 0.99 is the relationship between electron density and CT Number. In a low contrast resolution test, the smallest contrast groups are visible. In contrast, the high resolution is seen up to 7 lp/cm. The quality of GE CT Scan is very high, as all the image quality tests obtained are within the tolerance brackets of values permitted by the Nuclear Power Control Agency (BAPETEN). Image quality test is a way to get very important information about the accuracy of snoring result by using phantom ACR.
MARS spectral molecular imaging of lamb tissue: data collection and image analysis
NASA Astrophysics Data System (ADS)
Aamir, R.; Chernoglazov, A.; Bateman, C. J.; Butler, A. P. H.; Butler, P. H.; Anderson, N. G.; Bell, S. T.; Panta, R. K.; Healy, J. L.; Mohr, J. L.; Rajendran, K.; Walsh, M. F.; de Ruiter, N.; Gieseg, S. P.; Woodfield, T.; Renaud, P. F.; Brooke, L.; Abdul-Majid, S.; Clyne, M.; Glendenning, R.; Bones, P. J.; Billinghurst, M.; Bartneck, C.; Mandalika, H.; Grasset, R.; Schleich, N.; Scott, N.; Nik, S. J.; Opie, A.; Janmale, T.; Tang, D. N.; Kim, D.; Doesburg, R. M.; Zainon, R.; Ronaldson, J. P.; Cook, N. J.; Smithies, D. J.; Hodge, K.
2014-02-01
Spectral molecular imaging is a new imaging technique able to discriminate and quantify different components of tissue simultaneously at high spatial and high energy resolution. Our MARS scanner is an x-ray based small animal CT system designed to be used in the diagnostic energy range (20-140 keV). In this paper, we demonstrate the use of the MARS scanner, equipped with the Medipix3RX spectroscopic photon-processing detector, to discriminate fat, calcium, and water in tissue. We present data collected from a sample of lamb meat including bone as an illustrative example of human tissue imaging. The data is analyzed using our 3D Algebraic Reconstruction Algorithm (MARS-ART) and by material decomposition based on a constrained linear least squares algorithm. The results presented here clearly show the quantification of lipid-like, water-like and bone-like components of tissue. However, it is also clear to us that better algorithms could extract more information of clinical interest from our data. Because we are one of the first to present data from multi-energy photon-processing small animal CT systems, we make the raw, partial and fully processed data available with the intention that others can analyze it using their familiar routines. The raw, partially processed and fully processed data of lamb tissue along with the phantom calibration data can be found at http://hdl.handle.net/10092/8531.
Wu, Yao; Yang, Wei; Lu, Lijun; Lu, Zhentai; Zhong, Liming; Huang, Meiyan; Feng, Yanqiu; Feng, Qianjin; Chen, Wufan
2016-10-01
Attenuation correction is important for PET reconstruction. In PET/MR, MR intensities are not directly related to attenuation coefficients that are needed in PET imaging. The attenuation coefficient map can be derived from CT images. Therefore, prediction of CT substitutes from MR images is desired for attenuation correction in PET/MR. This study presents a patch-based method for CT prediction from MR images, generating attenuation maps for PET reconstruction. Because no global relation exists between MR and CT intensities, we propose local diffeomorphic mapping (LDM) for CT prediction. In LDM, we assume that MR and CT patches are located on 2 nonlinear manifolds, and the mapping from the MR manifold to the CT manifold approximates a diffeomorphism under a local constraint. Locality is important in LDM and is constrained by the following techniques. The first is local dictionary construction, wherein, for each patch in the testing MR image, a local search window is used to extract patches from training MR/CT pairs to construct MR and CT dictionaries. The k-nearest neighbors and an outlier detection strategy are then used to constrain the locality in MR and CT dictionaries. Second is local linear representation, wherein, local anchor embedding is used to solve MR dictionary coefficients when representing the MR testing sample. Under these local constraints, dictionary coefficients are linearly transferred from the MR manifold to the CT manifold and used to combine CT training samples to generate CT predictions. Our dataset contains 13 healthy subjects, each with T1- and T2-weighted MR and CT brain images. This method provides CT predictions with a mean absolute error of 110.1 Hounsfield units, Pearson linear correlation of 0.82, peak signal-to-noise ratio of 24.81 dB, and Dice in bone regions of 0.84 as compared with real CTs. CT substitute-based PET reconstruction has a regression slope of 1.0084 and R 2 of 0.9903 compared with real CT-based PET. In this method, no image segmentation or accurate registration is required. Our method demonstrates superior performance in CT prediction and PET reconstruction compared with competing methods. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.
Boll, Hanne; Nittka, Stefanie; Doyon, Fabian; Neumaier, Michael; Marx, Alexander; Kramer, Martin; Groden, Christoph; Brockmann, Marc A.
2011-01-01
Background Micro-CT imaging of liver disease in mice relies on high soft tissue contrast to detect small lesions like liver metastases. Purpose of this study was to characterize the localization and time course of contrast enhancement of a nanoparticular alkaline earth metal-based contrast agent (VISCOVER ExiTron nano) developed for small animal liver CT imaging. Methodology ExiTron nano 6000 and ExiTron nano 12000, formulated for liver/spleen imaging and angiography, respectively, were intravenously injected in C57BL/6J-mice. The distribution and time course of contrast enhancement were analysed by repeated micro-CT up to 6 months. Finally, mice developing liver metastases after intrasplenic injection of colon carcinoma cells underwent longitudinal micro-CT imaging after a single injection of ExiTron nano. Principal Findings After a single injection of ExiTron nano the contrast of liver and spleen peaked after 4–8 hours, lasted up to several months and was tolerated well by all mice. In addition, strong contrast enhancement of abdominal and mediastinal lymph nodes and the adrenal glands was observed. Within the first two hours after injection, particularly ExiTron nano 12000 provided pronounced contrast for imaging of vascular structures. ExiTron nano facilitated detection of liver metastases and provided sufficient contrast for longitudinal observation of tumor development over weeks. Conclusions The nanoparticulate contrast agents ExiTron nano 6000 and 12000 provide strong contrast of the liver, spleen, lymph nodes and adrenal glands up to weeks, hereby allowing longitudinal monitoring of pathological processes of these organs in small animals, with ExiTron nano 12000 being particularly optimized for angiography due to its very high initial vessel contrast. PMID:21984939
Hertanto, Agung; Zhang, Qinghui; Hu, Yu-Chi; Dzyubak, Oleksandr; Rimner, Andreas; Mageras, Gig S
2012-06-01
Respiration-correlated CT (RCCT) images produced with commonly used phase-based sorting of CT slices often exhibit discontinuity artifacts between CT slices, caused by cycle-to-cycle amplitude variations in respiration. Sorting based on the displacement of the respiratory signal yields slices at more consistent respiratory motion states and hence reduces artifacts, but missing image data (gaps) may occur. The authors report on the application of a respiratory motion model to produce an RCCT image set with reduced artifacts and without missing data. Input data consist of CT slices from a cine CT scan acquired while recording respiration by monitoring abdominal displacement. The model-based generation of RCCT images consists of four processing steps: (1) displacement-based sorting of CT slices to form volume images at 10 motion states over the cycle; (2) selection of a reference image without gaps and deformable registration between the reference image and each of the remaining images; (3) generation of the motion model by applying a principal component analysis to establish a relationship between displacement field and respiration signal at each motion state; (4) application of the motion model to deform the reference image into images at the 9 other motion states. Deformable image registration uses a modified fast free-form algorithm that excludes zero-intensity voxels, caused by missing data, from the image similarity term in the minimization function. In each iteration of the minimization, the displacement field in the gap regions is linearly interpolated from nearest neighbor nonzero intensity slices. Evaluation of the model-based RCCT examines three types of image sets: cine scans of a physical phantom programmed to move according to a patient respiratory signal, NURBS-based cardiac torso (NCAT) software phantom, and patient thoracic scans. Comparison in physical motion phantom shows that object distortion caused by variable motion amplitude in phase-based sorting is visibly reduced with model-based RCCT. Comparison of model-based RCCT to original NCAT images as ground truth shows best agreement at motion states whose displacement-sorted images have no missing slices, with mean and maximum discrepancies in lung of 1 and 3 mm, respectively. Larger discrepancies correlate with motion states having a larger number of missing slices in the displacement-sorted images. Artifacts in patient images at different motion states are also reduced. Comparison with displacement-sorted patient images as a ground truth shows that the model-based images closely reproduce the ground truth geometry at different motion states. Results in phantom and patient images indicate that the proposed method can produce RCCT image sets with reduced artifacts relative to phase-sorted images, without the gaps inherent in displacement-sorted images. The method requires a reference image at one motion state that has no missing data. Highly irregular breathing patterns can affect the method's performance, by introducing artifacts in the reference image (although reduced relative to phase-sorted images), or in decreased accuracy in the image prediction of motion states containing large regions of missing data. © 2012 American Association of Physicists in Medicine.
Lell, M M; May, M S; Brand, M; Eller, A; Buder, T; Hofmann, E; Uder, M; Wuest, W
2015-07-01
CT is the imaging technique of choice in the evaluation of midface trauma or inflammatory disease. We performed a systematic evaluation of scan protocols to optimize image quality and radiation exposure on third-generation dual-source CT. CT protocols with different tube voltage (70-150 kV), current (25-300 reference mAs), prefiltration, pitch value, and rotation time were systematically evaluated. All images were reconstructed with iterative reconstruction (Advanced Modeled Iterative Reconstruction, level 2). To individually compare results with otherwise identical factors, we obtained all scans on a frozen human head. Conebeam CT was performed for image quality and dose comparison with multidetector row CT. Delineation of important anatomic structures and incidental pathologic conditions in the cadaver head was evaluated. One hundred kilovolts with tin prefiltration demonstrated the best compromise between dose and image quality. The most dose-effective combination for trauma imaging was Sn100 kV/250 mAs (volume CT dose index, 2.02 mGy), and for preoperative sinus surgery planning, Sn100 kV/150 mAs (volume CT dose index, 1.22 mGy). "Sn" indicates an additional prefiltration of the x-ray beam with a tin filter to constrict the energy spectrum. Exclusion of sinonasal disease was possible with even a lower dose by using Sn100 kV/25 mAs (volume CT dose index, 0.2 mGy). High image quality at very low dose levels can be achieved by using a Sn100-kV protocol with iterative reconstruction. The effective dose is comparable with that of conventional radiography, and the high image quality at even lower radiation exposure favors multidetector row CT over conebeam CT. © 2015 by American Journal of Neuroradiology.
Processing And Display Of Medical Three Dimensional Arrays Of Numerical Data Using Octree Encoding
NASA Astrophysics Data System (ADS)
Amans, Jean-Louis; Darier, Pierre
1986-05-01
imaging modalities such as X-Ray computerized Tomography (CT), Nuclear Medecine and Nuclear Magnetic Resonance can produce three-dimensional (3-D) arrays of numerical data of medical object internal structures. The analysis of 3-D data by synthetic generation of realistic images is an important area of computer graphics and imaging.
Pseudo CT estimation from MRI using patch-based random forest
NASA Astrophysics Data System (ADS)
Yang, Xiaofeng; Lei, Yang; Shu, Hui-Kuo; Rossi, Peter; Mao, Hui; Shim, Hyunsuk; Curran, Walter J.; Liu, Tian
2017-02-01
Recently, MR simulators gain popularity because of unnecessary radiation exposure of CT simulators being used in radiation therapy planning. We propose a method for pseudo CT estimation from MR images based on a patch-based random forest. Patient-specific anatomical features are extracted from the aligned training images and adopted as signatures for each voxel. The most robust and informative features are identified using feature selection to train the random forest. The well-trained random forest is used to predict the pseudo CT of a new patient. This prediction technique was tested with human brain images and the prediction accuracy was assessed using the original CT images. Peak signal-to-noise ratio (PSNR) and feature similarity (FSIM) indexes were used to quantify the differences between the pseudo and original CT images. The experimental results showed the proposed method could accurately generate pseudo CT images from MR images. In summary, we have developed a new pseudo CT prediction method based on patch-based random forest, demonstrated its clinical feasibility, and validated its prediction accuracy. This pseudo CT prediction technique could be a useful tool for MRI-based radiation treatment planning and attenuation correction in a PET/MRI scanner.
NASA Astrophysics Data System (ADS)
Bredfeldt, Jeremy S.; Liu, Yuming; Pehlke, Carolyn A.; Conklin, Matthew W.; Szulczewski, Joseph M.; Inman, David R.; Keely, Patricia J.; Nowak, Robert D.; Mackie, Thomas R.; Eliceiri, Kevin W.
2014-01-01
Second-harmonic generation (SHG) imaging can help reveal interactions between collagen fibers and cancer cells. Quantitative analysis of SHG images of collagen fibers is challenged by the heterogeneity of collagen structures and low signal-to-noise ratio often found while imaging collagen in tissue. The role of collagen in breast cancer progression can be assessed post acquisition via enhanced computation. To facilitate this, we have implemented and evaluated four algorithms for extracting fiber information, such as number, length, and curvature, from a variety of SHG images of collagen in breast tissue. The image-processing algorithms included a Gaussian filter, SPIRAL-TV filter, Tubeness filter, and curvelet-denoising filter. Fibers are then extracted using an automated tracking algorithm called fiber extraction (FIRE). We evaluated the algorithm performance by comparing length, angle and position of the automatically extracted fibers with those of manually extracted fibers in twenty-five SHG images of breast cancer. We found that the curvelet-denoising filter followed by FIRE, a process we call CT-FIRE, outperforms the other algorithms under investigation. CT-FIRE was then successfully applied to track collagen fiber shape changes over time in an in vivo mouse model for breast cancer.
Aukema, T S; Rutgers, E J Th; Vogel, W V; Teertstra, H J; Oldenburg, H S; Vrancken Peeters, M T F D; Wesseling, J; Russell, N S; Valdés Olmos, R A
2010-04-01
The aim of this study was to evaluate the impact of (18)F-fluorodeoxyglucose positron-emission tomography/computed tomography (FDG PET/CT) on clinical management in patients with locoregional breast cancer recurrence amenable for locoregional treatment and to compare the PET/CT results with the conventional imaging data. From January 2006 to August 2008, all patients with locoregional breast cancer recurrence underwent whole-body PET/CT. PET/CT findings were compared with results of the conventional imaging techniques and final pathology. The impact of PET/CT results on clinical management was evaluated based on clinical decisions obtained from patient files. 56 patients were included. In 32 patients (57%) PET/CT revealed additional tumour localisations. Distant metastases were detected in 11 patients on conventional imaging and in 23 patients on PET/CT images (p < 0.01). In 25 patients (45%), PET/CT detected additional lesions not visible on conventional imaging. PET/CT had an impact on clinical management in 27 patients (48%) by detecting more extensive locoregional disease or distant metastases. In 20 patients (36%) extensive surgery was prevented and treatment was changed to palliative treatment. The sensitivity, specificity, accuracy, positive and negative predictive values of FDG PET/CT were respectively 97%, 92%, 95%, 94% and 96%. PET/CT, in addition to conventional imaging techniques, plays an important role in staging patients with locoregional breast cancer recurrence since its result changed the clinical management in almost half of the patients. PET/CT could potentially replace conventional staging imaging in patients with a locoregional breast cancer recurrence. Copyright (c) 2009 Elsevier Ltd. All rights reserved.
Patient-specific lean body mass can be estimated from limited-coverage computed tomography images.
Devriese, Joke; Beels, Laurence; Maes, Alex; van de Wiele, Christophe; Pottel, Hans
2018-06-01
In PET/CT, quantitative evaluation of tumour metabolic activity is possible through standardized uptake values, usually normalized for body weight (BW) or lean body mass (LBM). Patient-specific LBM can be estimated from whole-body (WB) CT images. As most clinical indications only warrant PET/CT examinations covering head to midthigh, the aim of this study was to develop a simple and reliable method to estimate LBM from limited-coverage (LC) CT images and test its validity. Head-to-toe PET/CT examinations were retrospectively retrieved and semiautomatically segmented into tissue types based on thresholding of CT Hounsfield units. LC was obtained by omitting image slices. Image segmentation was validated on the WB CT examinations by comparing CT-estimated BW with actual BW, and LBM estimated from LC images were compared with LBM estimated from WB images. A direct method and an indirect method were developed and validated on an independent data set. Comparing LBM estimated from LC examinations with estimates from WB examinations (LBMWB) showed a significant but limited bias of 1.2 kg (direct method) and nonsignificant bias of 0.05 kg (indirect method). This study demonstrates that LBM can be estimated from LC CT images with no significant difference from LBMWB.
NASA Astrophysics Data System (ADS)
Dall'Ara, Enrico; Peña-Fernández, Marta; Palanca, Marco; Giorgi, Mario; Cristofolini, Luca; Tozzi, Gianluca
2017-11-01
Accurate measurement of local strain in heterogeneous and anisotropic bone tissue is fundamental to understand the pathophysiology of musculoskeletal diseases, to evaluate the effect of interventions from preclinical studies, and to optimize the design and delivery of biomaterials. Digital volume correlation (DVC) can be used to measure the three-dimensional displacement and strain fields from micro-Computed Tomography (µCT) images of loaded specimens. However, this approach is affected by the quality of the input images, by the morphology and density of the tissue under investigation, by the correlation scheme, and by the operational parameters used in the computation. Therefore, for each application the precision of the method should be evaluated. In this paper we present the results collected from datasets analyzed in previous studies as well as new data from a recent experimental campaign for characterizing the relationship between the precision of two different DVC approaches and the spatial resolution of the outputs. Different bone structures scanned with laboratory source µCT or Synchrotron light µCT (SRµCT) were processed in zero-strain tests to evaluate the precision of the DVC methods as a function of the subvolume size that ranged from 8 to 2500 micrometers. The results confirmed that for every microstructure the precision of DVC improves for larger subvolume size, following power laws. However, for the first time large differences in the precision of both local and global DVC approaches have been highlighted when SRµCT or in vivo µCT images were used instead of conventional ex vivo µCT. These findings suggest that in situ mechanical testing protocols applied in SRµCT facilities should be optimized in order to allow DVC analyses of localized strain measurements. Moreover, for in vivo µCT applications DVC analyses should be performed only with relatively course spatial resolution for achieving a reasonable precision of the method. In conclusion, we have extensively shown that the precision of both tested DVC approaches is affected by different bone structures, different input image resolution and different subvolume sizes. Before each specific application DVC users should always apply a similar approach to find the best compromise between precision and spatial resolution of the measurements.
GPU-accelerated regularized iterative reconstruction for few-view cone beam CT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Matenine, Dmitri, E-mail: dmitri.matenine.1@ulaval.ca; Goussard, Yves, E-mail: yves.goussard@polymtl.ca; Després, Philippe, E-mail: philippe.despres@phy.ulaval.ca
2015-04-15
Purpose: The present work proposes an iterative reconstruction technique designed for x-ray transmission computed tomography (CT). The main objective is to provide a model-based solution to the cone-beam CT reconstruction problem, yielding accurate low-dose images via few-views acquisitions in clinically acceptable time frames. Methods: The proposed technique combines a modified ordered subsets convex (OSC) algorithm and the total variation minimization (TV) regularization technique and is called OSC-TV. The number of subsets of each OSC iteration follows a reduction pattern in order to ensure the best performance of the regularization method. Considering the high computational cost of the algorithm, it ismore » implemented on a graphics processing unit, using parallelization to accelerate computations. Results: The reconstructions were performed on computer-simulated as well as human pelvic cone-beam CT projection data and image quality was assessed. In terms of convergence and image quality, OSC-TV performs well in reconstruction of low-dose cone-beam CT data obtained via a few-view acquisition protocol. It compares favorably to the few-view TV-regularized projections onto convex sets (POCS-TV) algorithm. It also appears to be a viable alternative to full-dataset filtered backprojection. Execution times are of 1–2 min and are compatible with the typical clinical workflow for nonreal-time applications. Conclusions: Considering the image quality and execution times, this method may be useful for reconstruction of low-dose clinical acquisitions. It may be of particular benefit to patients who undergo multiple acquisitions by reducing the overall imaging radiation dose and associated risks.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yoon, J; Jung, J; Yeo, I
2015-06-15
Purpose: To develop and to test a method to generate a new 4D CT images of the treatment day from the old 4D CT and the portal images of the day when the motion extent exceeded from that represented by plan CTs. Methods: A motion vector of a moving tumor in a patient may be extended to reconstruct the tumor position when the motion extent exceeded from that represented by plan CTs. To test this, 1. a phantom that consists of a polystyrene cylinder (tumor) embedded in cork (lung) was placed on a moving platform with 4 sec/cycle and amplitudesmore » of 1 cm and 2 cm, and was 4D-scanned. 2. A 6MV photon beam was irradiated on the moving phantoms and cineEPID images were obtained. 3. A motion vector of the tumor was acquired from 4D CT images of the phantom with 1 cm amplitude. 4. From cine EPID images of the phantom with the 2 cm amplitude, various motion extents (0.3 cm, 0.5 cm, etc) were acquired and programmed into the motion vector, producing CT images at each position. 5. The reconstructed CT images were then compared with pre-acquired “reference” 4D CT images at each position (i.e. phase). Results: The CT image was reconstructed and compared with the reference image, showing a slight mismatch in the transition direction limited by voxel size (slice thickness) in CT image. Due to the rigid nature of the phantom studied, the modeling the displacement of the center of object was sufficient. When deformable tumors are to be modeled, more complex scheme is necessary, which utilize cine EPID and 4D CT images. Conclusion: The new idea of CT image reconstruction was demonstrated. Deformable tumor movements need to be considered in the future.« less
Algorithm for lung cancer detection based on PET/CT images
NASA Astrophysics Data System (ADS)
Saita, Shinsuke; Ishimatsu, Keita; Kubo, Mitsuru; Kawata, Yoshiki; Niki, Noboru; Ohtsuka, Hideki; Nishitani, Hiromu; Ohmatsu, Hironobu; Eguchi, Kenji; Kaneko, Masahiro; Moriyama, Noriyuki
2009-02-01
The five year survival rate of the lung cancer is low with about twenty-five percent. In addition it is an obstinate lung cancer wherein three out of four people die within five years. Then, the early stage detection and treatment of the lung cancer are important. Recently, we can obtain CT and PET image at the same time because PET/CT device has been developed. PET/CT is possible for a highly accurate cancer diagnosis because it analyzes quantitative shape information from CT image and FDG distribution from PET image. However, neither benign-malignant classification nor staging intended for lung cancer have been established still enough by using PET/CT images. In this study, we detect lung nodules based on internal organs extracted from CT image, and we also develop algorithm which classifies benignmalignant and metastatic or non metastatic lung cancer using lung structure and FDG distribution(one and two hour after administering FDG). We apply the algorithm to 59 PET/CT images (malignant 43 cases [Ad:31, Sq:9, sm:3], benign 16 cases) and show the effectiveness of this algorithm.
Development of CT and 3D-CT Using Flat Panel Detector Based Real-Time Digital Radiography System
NASA Astrophysics Data System (ADS)
Ravindran, V. R.; Sreelakshmi, C.; Vibin, Vibin
2008-09-01
The application of Digital Radiography in the Nondestructive Evaluation (NDE) of space vehicle components is a recent development in India. A Real-time DR system based on amorphous silicon Flat Panel Detector has been developed for the NDE of solid rocket motors at Rocket Propellant Plant of VSSC in a few years back. The technique has been successfully established for the nondestructive evaluation of solid rocket motors. The DR images recorded for a few solid rocket specimens are presented in the paper. The Real-time DR system is capable of generating sufficient digital X-ray image data with object rotation for the CT image reconstruction. In this paper the indigenous development of CT imaging based on the Realtime DR system for solid rocket motor is presented. Studies are also carried out to generate 3D-CT image from a set of adjacent CT images of the rocket motor. The capability of revealing the spatial location and characterisation of defect is demonstrated by the CT and 3D-CT images generated.