PET/CT scanners: a hardware approach to image fusion.

PubMed

Townsend, David W; Beyer, Thomas; Blodgett, Todd M

2003-07-01

New technology that combines positron tomography with x-ray computed tomography (PET/CT) is available from all major vendors of PET imaging equipment: CTI, Siemens, GE, Philips. Although not all vendors have made the same design choices as those described in this review all have in common that their high performance design places a commercial CT scanner in tandem with a commercial PET scanner. The level of physical integration is actually less than that of the original prototype design where the CT and PET components were mounted on the same rotating support. There will undoubtedly be a demand for PET/CT technology with a greater level of integration, and at a reduced cost. This may be achieved through the design of a scanner specifically for combined anatomical and functional imaging, rather than a design combining separate CT and PET scanners, as in the current approaches. By avoiding the duplication of data acquisition and image reconstruction functions, for example, a more integrated design should also allow cost savings over current commercial PET/CT scanners. The goal is then to design and build a device specifically for imaging the function and anatomy of cancer in the most optimal and effective way, without conceptualizing it as combined PET and CT. The development of devices specifically for imaging a particular disease (eg, cancer) differs from the conventional approach of, for example, an all-purpose anatomical imaging device such as a CT scanner. This new concept targets more of a disease management approach rather than the usual division into the medical specialties of radiology (anatomical imaging) and nuclear medicine (functional imaging). Copyright 2003 Elsevier Inc. All rights reserved.

Dual-modality brain PET-CT image segmentation based on adaptive use of functional and anatomical information.

PubMed

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.

Molecular imaging of malignant tumor metabolism: whole-body image fusion of DWI/CT vs. PET/CT.

PubMed

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.

Artefacts of PET/CT images

PubMed Central

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

SedCT: MATLAB™ tools for standardized and quantitative processing of sediment core computed tomography (CT) data collected using a medical CT scanner

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.

Deep embedding convolutional neural network for synthesizing CT image from T1-Weighted MR image.

PubMed

Xiang, Lei; Wang, Qian; Nie, Dong; Zhang, Lichi; Jin, Xiyao; Qiao, Yu; Shen, Dinggang

2018-07-01

Recently, more and more attention is drawn to the field of medical image synthesis across modalities. Among them, the synthesis of computed tomography (CT) image from T1-weighted magnetic resonance (MR) image is of great importance, although the mapping between them is highly complex due to large gaps of appearances of the two modalities. In this work, we aim to tackle this MR-to-CT synthesis task by a novel deep embedding convolutional neural network (DECNN). Specifically, we generate the feature maps from MR images, and then transform these feature maps forward through convolutional layers in the network. We can further compute a tentative CT synthesis from the midway of the flow of feature maps, and then embed this tentative CT synthesis result back to the feature maps. This embedding operation results in better feature maps, which are further transformed forward in DECNN. After repeating this embedding procedure for several times in the network, we can eventually synthesize a final CT image in the end of the DECNN. We have validated our proposed method on both brain and prostate imaging datasets, by also comparing with the state-of-the-art methods. Experimental results suggest that our DECNN (with repeated embedding operations) demonstrates its superior performances, in terms of both the perceptive quality of the synthesized CT image and the run-time cost for synthesizing a CT image. Copyright © 2018. Published by Elsevier B.V.

Fully Convolutional Architecture for Low-Dose CT Image Noise Reduction

NASA Astrophysics Data System (ADS)

Badretale, S.; Shaker, F.; Babyn, P.; Alirezaie, J.

2017-10-01

One of the critical topics in medical low-dose Computed Tomography (CT) imaging is how best to maintain image quality. As the quality of images decreases with lowering the X-ray radiation dose, improving image quality is extremely important and challenging. We have proposed a novel approach to denoise low-dose CT images. Our algorithm learns directly from an end-to-end mapping from the low-dose Computed Tomography images for denoising the normal-dose CT images. Our method is based on a deep convolutional neural network with rectified linear units. By learning various low-level to high-level features from a low-dose image the proposed algorithm is capable of creating a high-quality denoised image. We demonstrate the superiority of our technique by comparing the results with two other state-of-the-art methods in terms of the peak signal to noise ratio, root mean square error, and a structural similarity index.

Image quality of conventional images of dual-layer SPECTRAL CT: A phantom study.

PubMed

van Ommen, Fasco; Bennink, Edwin; Vlassenbroek, Alain; Dankbaar, Jan Willem; Schilham, Arnold M R; Viergever, Max A; de Jong, Hugo W A M

2018-05-10

and larger phantoms with differences up to 0.51. Spatial resolution did not change with phantom size, but noise levels increased significantly. For head scans, IQon had a noise level that was significantly lower than the iCT, on the other hand IQon showed noise levels significantly higher than the iCT for body scans. Still, these differences were well within the specified range of performance of iCT scanners. At equivalent dose levels, this study showed similar quality of conventional images acquired on iCT and IQon for medium-sized phantoms and slightly degraded image quality for (very) large phantoms at lower tube voltages on the IQon. Accordingly, it may be concluded that the introduction of a dual-layer detector neither compromises image quality of conventional images nor increases radiation dose for normal-sized patients, and slightly degrades dose efficiency for large patients at 120 kVp and lower tube voltages. © 2018 The Authors. Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

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.

Outside CT imaging among emergency department transfer patients.

PubMed

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.

Computer-aided diagnosis workstation and network system for chest diagnosis based on multislice CT images

NASA Astrophysics Data System (ADS)

Satoh, Hitoshi; Niki, Noboru; Mori, Kiyoshi; Eguchi, Kenji; Kaneko, Masahiro; Kakinuma, Ryutarou; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru

2007-03-01

Multislice CT scanner advanced remarkably at the speed at which the chest CT images were acquired for mass screening. Mass screening based on multislice CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images and a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification. Moreover, we have provided diagnostic assistance methods to medical screening specialists by using a lung cancer screening algorithm built into mobile helical CT scanner for the lung cancer mass screening done in the region without the hospital. We also have developed electronic medical recording system and prototype internet system for the community health in two or more regions by using the Virtual Private Network router and Biometric fingerprint authentication system and Biometric face authentication system for safety of medical information. Based on these diagnostic assistance methods, we have now developed a new computer-aided workstation and database that can display suspected lesions three-dimensionally in a short time. This paper describes basic studies that have been conducted to evaluate this new system.

Multi-material decomposition of spectral CT images

NASA Astrophysics Data System (ADS)

Mendonça, Paulo R. S.; Bhotika, Rahul; Maddah, Mahnaz; Thomsen, Brian; Dutta, Sandeep; Licato, Paul E.; Joshi, Mukta C.

2010-04-01

Spectral Computed Tomography (Spectral CT), and in particular fast kVp switching dual-energy computed tomography, is an imaging modality that extends the capabilities of conventional computed tomography (CT). Spectral CT enables the estimation of the full linear attenuation curve of the imaged subject at each voxel in the CT volume, instead of a scalar image in Hounsfield units. Because the space of linear attenuation curves in the energy ranges of medical applications can be accurately described through a two-dimensional manifold, this decomposition procedure would be, in principle, limited to two materials. This paper describes an algorithm that overcomes this limitation, allowing for the estimation of N-tuples of material-decomposed images. The algorithm works by assuming that the mixing of substances and tissue types in the human body has the physicochemical properties of an ideal solution, which yields a model for the density of the imaged material mix. Under this model the mass attenuation curve of each voxel in the image can be estimated, immediately resulting in a material-decomposed image triplet. Decomposition into an arbitrary number of pre-selected materials can be achieved by automatically selecting adequate triplets from an application-specific material library. The decomposition is expressed in terms of the volume fractions of each constituent material in the mix; this provides for a straightforward, physically meaningful interpretation of the data. One important application of this technique is in the digital removal of contrast agent from a dual-energy exam, producing a virtual nonenhanced image, as well as in the quantification of the concentration of contrast observed in a targeted region, thus providing an accurate measure of tissue perfusion.

One-stop-shop stroke imaging with functional CT.

PubMed

Tong, Elizabeth; Komlosi, Peter; Wintermark, Max

2015-12-01

Advanced imaging techniques have extended beyond traditional anatomic imaging and progressed to dynamic, physiologic and functional imaging. Neuroimaging is no longer a mere diagnostic tool. Multimodal functional CT, comprising of NCCT, PCT and CTA, provides a one-stop-shop for rapid stroke imaging. Integrating those imaging findings with pertinent clinical information can help guide subsequent treatment decisions, medical management and follow-up imaging selection. This review article will briefly discuss the indication and utility of each modality in acute stroke imaging. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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

Imaging and Analytics: The changing face of Medical Imaging

NASA Astrophysics Data System (ADS)

Foo, Thomas

There have been significant technological advances in imaging capability over the past 40 years. Medical imaging capabilities have developed rapidly, along with technology development in computational processing speed and miniaturization. Moving to all-digital, the number of images that are acquired in a routine clinical examination has increased dramatically from under 50 images in the early days of CT and MRI to more than 500-1000 images today. The staggering number of images that are routinely acquired poses significant challenges for clinicians to interpret the data and to correctly identify the clinical problem. Although the time provided to render a clinical finding has not substantially changed, the amount of data available for interpretation has grown exponentially. In addition, the image quality (spatial resolution) and information content (physiologically-dependent image contrast) has also increased significantly with advances in medical imaging technology. On its current trajectory, medical imaging in the traditional sense is unsustainable. To assist in filtering and extracting the most relevant data elements from medical imaging, image analytics will have a much larger role. Automated image segmentation, generation of parametric image maps, and clinical decision support tools will be needed and developed apace to allow the clinician to manage, extract and utilize only the information that will help improve diagnostic accuracy and sensitivity. As medical imaging devices continue to improve in spatial resolution, functional and anatomical information content, image/data analytics will be more ubiquitous and integral to medical imaging capability.

Knowledge of medical imaging radiation dose and risk among doctors.

PubMed

Brown, Nicholas; Jones, Lee

2013-02-01

The growth of computed tomography (CT) and nuclear medicine (NM) scans has revolutionised healthcare but also greatly increased population radiation doses. Overuse of diagnostic radiation is becoming a feature of medical practice, leading to possible unnecessary radiation exposures and lifetime-risks of developing cancer. Doctors across all medical specialties and experience levels were surveyed to determine their knowledge of radiation doses and potential risks associated with some diagnostic imaging. A survey relating to knowledge and understanding of medical imaging radiation was distributed to doctors at 14 major Queensland public hospitals, as well as fellows and trainees in radiology, emergency medicine and general practice. From 608 valid responses, only 17.3% correctly estimated the radiation dose from CT scans and almost 1 in 10 incorrectly believed that CT radiation is not associated with any increased lifetime risk of developing cancer. There is a strong inverse relationship between a clinician's experience and their knowledge of CT radiation dose and risks, even among radiologists. More than a third (35.7%) of doctors incorrectly believed that typical NM imaging either does not use ionising radiation or emits doses equal to or less than a standard chest radiograph. Knowledge of CT and NM radiation doses is poor across all specialties, and there is a significant inverse relationship between experience and awareness of CT dose and risk. Despite having a poor understanding of these concepts, most doctors claim to consider them prior to requesting scans and when discussing potential risks with patients. © 2012 The Authors. Journal of Medical Imaging and Radiation Oncology © 2012 The Royal Australian and New Zealand College of Radiologists.

Computer-aided diagnosis workstation and database system for chest diagnosis based on multi-helical CT images

NASA Astrophysics Data System (ADS)

Satoh, Hitoshi; Niki, Noboru; Mori, Kiyoshi; Eguchi, Kenji; Kaneko, Masahiro; Kakinuma, Ryutarou; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru; Sasagawa, Michizou

2006-03-01

Multi-helical CT scanner advanced remarkably at the speed at which the chest CT images were acquired for mass screening. Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images and a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification. We also have developed electronic medical recording system and prototype internet system for the community health in two or more regions by using the Virtual Private Network router and Biometric fingerprint authentication system and Biometric face authentication system for safety of medical information. Based on these diagnostic assistance methods, we have now developed a new computer-aided workstation and database that can display suspected lesions three-dimensionally in a short time. This paper describes basic studies that have been conducted to evaluate this new system. The results of this study indicate that our computer-aided diagnosis workstation and network system can increase diagnostic speed, diagnostic accuracy and safety of medical information.

Discovering Hominins - Application of Medical Computed Tomography (CT) to Fossil-Bearing Rocks from the Site of Malapa, South Africa.

PubMed

Smilg, Jacqueline S; Berger, Lee R

2015-01-01

In the South African context, computed tomography (CT) has been used applied to individually prepared fossils and small rocks containing fossils, but has not been utilized on large breccia blocks as a means of discovering fossils, and particularly fossil hominins. Previous attempts at CT imaging of rocks from other South African sites for this purpose yielded disappointing results. For this study, 109 fossil- bearing rocks from the site of Malapa, South Africa were scanned with medical CT prior to manual preparation. The resultant images were assessed for accuracy of fossil identification and characterization against the standard of manual preparation. The accurate identification of fossils, including those of early hominins, that were not visible on the surface of individual blocks, is shown to be possible. The discovery of unexpected fossils is reduced, thus lowering the potential that fossils could be damaged through accidental encounter during routine preparation, or even entirely missed. This study should significantly change the way fossil discovery, recovery and preparation is done in the South African context and has potential for application in other palaeontological situations. Medical CT imaging is shown to be reliable, readily available, cost effective and accurate in finding fossils within matrix conglomerates. Improvements in CT equipment and in CT image quality are such that medical CT is now a viable imaging modality for this palaeontological application.

Discovering Hominins - Application of Medical Computed Tomography (CT) to Fossil-Bearing Rocks from the Site of Malapa, South Africa

PubMed Central

Smilg, Jacqueline S.; Berger, Lee R.

2015-01-01

In the South African context, computed tomography (CT) has been used applied to individually prepared fossils and small rocks containing fossils, but has not been utilized on large breccia blocks as a means of discovering fossils, and particularly fossil hominins. Previous attempts at CT imaging of rocks from other South African sites for this purpose yielded disappointing results. For this study, 109 fossil- bearing rocks from the site of Malapa, South Africa were scanned with medical CT prior to manual preparation. The resultant images were assessed for accuracy of fossil identification and characterization against the standard of manual preparation. The accurate identification of fossils, including those of early hominins, that were not visible on the surface of individual blocks, is shown to be possible. The discovery of unexpected fossils is reduced, thus lowering the potential that fossils could be damaged through accidental encounter during routine preparation, or even entirely missed. This study should significantly change the way fossil discovery, recovery and preparation is done in the South African context and has potential for application in other palaeontological situations. Medical CT imaging is shown to be reliable, readily available, cost effective and accurate in finding fossils within matrix conglomerates. Improvements in CT equipment and in CT image quality are such that medical CT is now a viable imaging modality for this palaeontological application. PMID:26684299

Point spread function modeling and image restoration for cone-beam CT

NASA Astrophysics Data System (ADS)

Zhang, Hua; Huang, Kui-Dong; Shi, Yi-Kai; Xu, Zhe

2015-03-01

X-ray cone-beam computed tomography (CT) has such notable features as high efficiency and precision, and is widely used in the fields of medical imaging and industrial non-destructive testing, but the inherent imaging degradation reduces the quality of CT images. Aimed at the problems of projection image degradation and restoration in cone-beam CT, a point spread function (PSF) modeling method is proposed first. The general PSF model of cone-beam CT is established, and based on it, the PSF under arbitrary scanning conditions can be calculated directly for projection image restoration without the additional measurement, which greatly improved the application convenience of cone-beam CT. Secondly, a projection image restoration algorithm based on pre-filtering and pre-segmentation is proposed, which can make the edge contours in projection images and slice images clearer after restoration, and control the noise in the equivalent level to the original images. Finally, the experiments verified the feasibility and effectiveness of the proposed methods. Supported by National Science and Technology Major Project of the Ministry of Industry and Information Technology of China (2012ZX04007021), Young Scientists Fund of National Natural Science Foundation of China (51105315), Natural Science Basic Research Program of Shaanxi Province of China (2013JM7003) and Northwestern Polytechnical University Foundation for Fundamental Research (JC20120226, 3102014KYJD022)

CT scan (image)

MedlinePlus

CT stands for computerized tomography. In this procedure, a thin X-ray beam is rotated around the ... D image of a section through the body. CT scans are very detailed and provide excellent information ...

Head CT (image)

MedlinePlus

CT stands for computerized tomography. In this procedure, a thin X-ray beam is rotated around the ... D image of a section through the body. CT scans are very detailed and provide excellent information ...

Reducing noise component on medical images

NASA Astrophysics Data System (ADS)

Semenishchev, Evgeny; Voronin, Viacheslav; Dub, Vladimir; Balabaeva, Oksana

2018-04-01

Medical visualization and analysis of medical data is an actual direction. Medical images are used in microbiology, genetics, roentgenology, oncology, surgery, ophthalmology, etc. Initial data processing is a major step towards obtaining a good diagnostic result. The paper considers the approach allows an image filtering with preservation of objects borders. The algorithm proposed in this paper is based on sequential data processing. At the first stage, local areas are determined, for this purpose the method of threshold processing, as well as the classical ICI algorithm, is applied. The second stage uses a method based on based on two criteria, namely, L2 norm and the first order square difference. To preserve the boundaries of objects, we will process the transition boundary and local neighborhood the filtering algorithm with a fixed-coefficient. For example, reconstructed images of CT, x-ray, and microbiological studies are shown. The test images show the effectiveness of the proposed algorithm. This shows the applicability of analysis many medical imaging applications.

Integration of Medical Imaging Including Ultrasound into a New Clinical Anatomy Curriculum

ERIC Educational Resources Information Center

Moscova, Michelle; Bryce, Deborah A.; Sindhusake, Doungkamol; Young, Noel

2015-01-01

In 2008 a new clinical anatomy curriculum with integrated medical imaging component was introduced into the University of Sydney Medical Program. Medical imaging used for teaching the new curriculum included normal radiography, MRI, CT scans, and ultrasound imaging. These techniques were incorporated into teaching over the first two years of the…

Improved Interactive Medical-Imaging System

NASA Technical Reports Server (NTRS)

Ross, Muriel D.; Twombly, Ian A.; Senger, Steven

2003-01-01

An improved computational-simulation system for interactive medical imaging has been invented. The system displays high-resolution, three-dimensional-appearing images of anatomical objects based on data acquired by such techniques as computed tomography (CT) and magnetic-resonance imaging (MRI). The system enables users to manipulate the data to obtain a variety of views for example, to display cross sections in specified planes or to rotate images about specified axes. Relative to prior such systems, this system offers enhanced capabilities for synthesizing images of surgical cuts and for collaboration by users at multiple, remote computing sites.

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.

Facilitating medical information search using Google Glass connected to a content-based medical image retrieval system.

PubMed

Widmer, Antoine; Schaer, Roger; Markonis, Dimitrios; Muller, Henning

2014-01-01

Wearable computing devices are starting to change the way users interact with computers and the Internet. Among them, Google Glass includes a small screen located in front of the right eye, a camera filming in front of the user and a small computing unit. Google Glass has the advantage to provide online services while allowing the user to perform tasks with his/her hands. These augmented glasses uncover many useful applications, also in the medical domain. For example, Google Glass can easily provide video conference between medical doctors to discuss a live case. Using these glasses can also facilitate medical information search by allowing the access of a large amount of annotated medical cases during a consultation in a non-disruptive fashion for medical staff. In this paper, we developed a Google Glass application able to take a photo and send it to a medical image retrieval system along with keywords in order to retrieve similar cases. As a preliminary assessment of the usability of the application, we tested the application under three conditions (images of the skin; printed CT scans and MRI images; and CT and MRI images acquired directly from an LCD screen) to explore whether using Google Glass affects the accuracy of the results returned by the medical image retrieval system. The preliminary results show that despite minor problems due to the relative stability of the Google Glass, images can be sent to and processed by the medical image retrieval system and similar images are returned to the user, potentially helping in the decision making process.

Medical imaging by fluorescent x-ray CT: its preliminary clinical evaluation

NASA Astrophysics Data System (ADS)

Takeda, Tohoru; Zeniya, Tsutomu; Wu, Jin; Yu, Quanwen; Lwin, Thet T.; Tsuchiya, Yoshinori; Rao, Donepudi V.; Yuasa, Tetsuya; Yashiro, Toru; Dilmanian, F. Avraham; Itai, Yuji; Akatsuka, Takao

2002-01-01

Fluorescent x-ray CT (FXCT) with synchrotron radiation (SR) is being developed to detect the very low concentration of specific elements. The endogenous iodine of the human thyroid and the non-radioactive iodine labeled BMIPP in myocardium were imaged by FXCT. FXCT system consists of a silicon (111) double crystal monochromator, an x-ray slit, a scanning table for object positioning, a fluorescent x-ray detector, and a transmission x-ray detector. Monochromatic x-ray with 37 keV energy was collimated into a pencil beam (from 1 mm to 0.025 mm). FXCT clearly imaged endogenous iodine of thyroid and iodine labeled BMIPP in myocardium, whereas transmission x-ray CT could not demonstrate iodine. The distribution of iodine was heterogeneous within thyroid cancer, and its concentration was lower than that of normal thyroid. Distribution of BMIPP in normal rat myocardium was almost homogeneous; however, reduced uptake was slightly shown in ischemic region. FXCT is a highly sensitive imaging modality to detect very low concentration of specific element and will be applied to reveal endogenous iodine distribution in thyroid and to use tracer study with various kinds of labeled material.

Hybrid SPECT-CT and PET-CT imaging of differentiated thyroid carcinoma.

PubMed

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.

Optimization of SPECT-CT Hybrid Imaging Using Iterative Image Reconstruction for Low-Dose CT: A Phantom Study

PubMed Central

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

Image reconstruction for PET/CT scanners: past achievements and future challenges

PubMed Central

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

Computer-aided diagnosis workstation and telemedicine network system for chest diagnosis based on multislice CT images

NASA Astrophysics Data System (ADS)

Satoh, Hitoshi; Niki, Noboru; Eguchi, Kenji; Ohmatsu, Hironobu; Kakinuma, Ryutaru; Moriyama, Noriyuki

2009-02-01

Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. Moreover, the doctor who diagnoses a medical image is insufficient in Japan. To overcome these problems, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images, a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification and a vertebra body analysis algorithm for quantitative evaluation of osteoporosis likelihood by using helical CT scanner for the lung cancer mass screening. The functions to observe suspicious shadow in detail are provided in computer-aided diagnosis workstation with these screening algorithms. We also have developed the telemedicine network by using Web medical image conference system with the security improvement of images transmission, Biometric fingerprint authentication system and Biometric face authentication system. Biometric face authentication used on site of telemedicine makes "Encryption of file" and "Success in login" effective. As a result, patients' private information is protected. We can share the screen of Web medical image conference system from two or more web conference terminals at the same time. An opinion can be exchanged mutually by using a camera and a microphone that are connected with workstation. Based on these diagnostic assistance methods, we have developed a new computer-aided workstation and a new telemedicine network that can display suspected lesions three-dimensionally in a short time. The results of this study indicate that our radiological information system without film by using computer-aided diagnosis workstation and our telemedicine network system can increase diagnostic speed, diagnostic accuracy and

Stereoscopic medical imaging collaboration system

NASA Astrophysics Data System (ADS)

Okuyama, Fumio; Hirano, Takenori; Nakabayasi, Yuusuke; Minoura, Hirohito; Tsuruoka, Shinji

2007-02-01

The computerization of the clinical record and the realization of the multimedia have brought improvement of the medical service in medical facilities. It is very important for the patients to obtain comprehensible informed consent. Therefore, the doctor should plainly explain the purpose and the content of the diagnoses and treatments for the patient. We propose and design a Telemedicine Imaging Collaboration System which presents a three dimensional medical image as X-ray CT, MRI with stereoscopic image by using virtual common information space and operating the image from a remote location. This system is composed of two personal computers, two 15 inches stereoscopic parallax barrier type LCD display (LL-151D, Sharp), one 1Gbps router and 1000base LAN cables. The software is composed of a DICOM format data transfer program, an operation program of the images, the communication program between two personal computers and a real time rendering program. Two identical images of 512×768 pixcels are displayed on two stereoscopic LCD display, and both images show an expansion, reduction by mouse operation. This system can offer a comprehensible three-dimensional image of the diseased part. Therefore, the doctor and the patient can easily understand it, depending on their needs.

Image Fusion of CT and MR with Sparse Representation in NSST Domain

PubMed Central

Qiu, Chenhui; Wang, Yuanyuan; Zhang, Huan

2017-01-01

Multimodal image fusion techniques can integrate the information from different medical images to get an informative image that is more suitable for joint diagnosis, preoperative planning, intraoperative guidance, and interventional treatment. Fusing images of CT and different MR modalities are studied in this paper. Firstly, the CT and MR images are both transformed to nonsubsampled shearlet transform (NSST) domain. So the low-frequency components and high-frequency components are obtained. Then the high-frequency components are merged using the absolute-maximum rule, while the low-frequency components are merged by a sparse representation- (SR-) based approach. And the dynamic group sparsity recovery (DGSR) algorithm is proposed to improve the performance of the SR-based approach. Finally, the fused image is obtained by performing the inverse NSST on the merged components. The proposed fusion method is tested on a number of clinical CT and MR images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation. PMID:29250134

Image Fusion of CT and MR with Sparse Representation in NSST Domain.

PubMed

Qiu, Chenhui; Wang, Yuanyuan; Zhang, Huan; Xia, Shunren

2017-01-01

Multimodal image fusion techniques can integrate the information from different medical images to get an informative image that is more suitable for joint diagnosis, preoperative planning, intraoperative guidance, and interventional treatment. Fusing images of CT and different MR modalities are studied in this paper. Firstly, the CT and MR images are both transformed to nonsubsampled shearlet transform (NSST) domain. So the low-frequency components and high-frequency components are obtained. Then the high-frequency components are merged using the absolute-maximum rule, while the low-frequency components are merged by a sparse representation- (SR-) based approach. And the dynamic group sparsity recovery (DGSR) algorithm is proposed to improve the performance of the SR-based approach. Finally, the fused image is obtained by performing the inverse NSST on the merged components. The proposed fusion method is tested on a number of clinical CT and MR images and compared with several popular image fusion methods. The experimental results demonstrate that the proposed fusion method can provide better fusion results in terms of subjective quality and objective evaluation.

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.

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.

Low dose CT image restoration using a database of image patches

NASA Astrophysics Data System (ADS)

Ha, Sungsoo; Mueller, Klaus

2015-01-01

Reducing the radiation dose in CT imaging has become an active research topic and many solutions have been proposed to remove the significant noise and streak artifacts in the reconstructed images. Most of these methods operate within the domain of the image that is subject to restoration. This, however, poses limitations on the extent of filtering possible. We advocate to take into consideration the vast body of external knowledge that exists in the domain of already acquired medical CT images, since after all, this is what radiologists do when they examine these low quality images. We can incorporate this knowledge by creating a database of prior scans, either of the same patient or a diverse corpus of different patients, to assist in the restoration process. Our paper follows up on our previous work that used a database of images. Using images, however, is challenging since it requires tedious and error prone registration and alignment. Our new method eliminates these problems by storing a diverse set of small image patches in conjunction with a localized similarity matching scheme. We also empirically show that it is sufficient to store these patches without anatomical tags since their statistics are sufficiently strong to yield good similarity matches from the database and as a direct effect, produce image restorations of high quality. A final experiment demonstrates that our global database approach can recover image features that are difficult to preserve with conventional denoising approaches.

Quantitative CT imaging for adipose tissue analysis in mouse model of obesity

NASA Astrophysics Data System (ADS)

Marchadier, A.; Vidal, C.; Tafani, J.-P.; Ordureau, S.; Lédée, R.; Léger, C.

2011-03-01

In obese humans CT imaging is a validated method for follow up studies of adipose tissue distribution and quantification of visceral and subcutaneous fat. Equivalent methods in murine models of obesity are still lacking. Current small animal micro-CT involves long-term X-ray exposure precluding longitudinal studies. We have overcome this limitation by using a human medical CT which allows very fast 3D imaging (2 sec) and minimal radiation exposure. This work presents novel methods fitted to in vivo investigations of mice model of obesity, allowing (i) automated detection of adipose tissue in abdominal regions of interest, (ii) quantification of visceral and subcutaneous fat. For each mouse, 1000 slices (100μm thickness, 160 μm resolution) were acquired in 2 sec using a Toshiba medical CT (135 kV, 400mAs). A Gaussian mixture model of the Hounsfield curve of 2D slices was computed with the Expectation Maximization algorithm. Identification of each Gaussian part allowed the automatic classification of adipose tissue voxels. The abdominal region of interest (umbilical) was automatically detected as the slice showing the highest ratio of the Gaussian proportion between adipose and lean tissues. Segmentation of visceral and subcutaneous fat compartments was achieved with 2D 1/2 level set methods. Our results show that the application of human clinical CT to mice is a promising approach for the study of obesity, allowing valuable comparison between species using the same imaging materials and software analysis.

Computer-aided diagnosis workstation and network system for chest diagnosis based on multislice CT images

NASA Astrophysics Data System (ADS)

Satoh, Hitoshi; Niki, Noboru; Eguchi, Kenji; Moriyama, Noriyuki; Ohmatsu, Hironobu; Masuda, Hideo; Machida, Suguru

2008-03-01

Mass screening based on multi-helical CT images requires a considerable number of images to be read. It is this time-consuming step that makes the use of helical CT for mass screening impractical at present. To overcome this problem, we have provided diagnostic assistance methods to medical screening specialists by developing a lung cancer screening algorithm that automatically detects suspected lung cancers in helical CT images, a coronary artery calcification screening algorithm that automatically detects suspected coronary artery calcification and a vertebra body analysis algorithm for quantitative evaluation of osteoporosis likelihood by using helical CT scanner for the lung cancer mass screening. The function to observe suspicious shadow in detail are provided in computer-aided diagnosis workstation with these screening algorithms. We also have developed the telemedicine network by using Web medical image conference system with the security improvement of images transmission, Biometric fingerprint authentication system and Biometric face authentication system. Biometric face authentication used on site of telemedicine makes "Encryption of file" and Success in login" effective. As a result, patients' private information is protected. Based on these diagnostic assistance methods, we have developed a new computer-aided workstation and a new telemedicine network that can display suspected lesions three-dimensionally in a short time. The results of this study indicate that our radiological information system without film by using computer-aided diagnosis workstation and our telemedicine network system can increase diagnostic speed, diagnostic accuracy and security improvement of medical information.

Imaging-related medications: a class overview

PubMed Central

2007-01-01

Imaging-related medications (contrast agents) are commonly utilized to improve visualization of radiographic, computed tomography (CT), and magnetic resonance (MR) images. While traditional medications are used specifically for their pharmacological actions, the ideal imaging agent provides enhanced contrast with little biological interaction. The radiopaque agents, barium sulfate and iodinated contrast agents, confer “contrast” to x-ray films by their physical ability to directly absorb x-rays. Gadolinium-based MR agents enhance visualization of tissues when exposed to a magnetic field. Ferrous-ferric oxide–based paramagnetic agents provide negative contrast for MR liver studies. This article provides an overview of clinically relevant information for the imaging-related medications commonly in use. It reviews the safety improvements in new generations of drugs; risk factors and precautions for the reduction of severe adverse reactions (i.e., extravasation, contrast-induced nephropathy, metformin-induced lactic acidosis, and nephrogenic fibrosing dermopathy/nephrogenic systemic fibrosis); and the significance of diligent patient screening before contrast exposure and appropriate monitoring after exposure. PMID:17948119

Cone Beam CT vs. Fan Beam CT: A Comparison of Image Quality and Dose Delivered Between Two Differing CT Imaging Modalities.

PubMed

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.

Cone Beam CT vs. Fan Beam CT: A Comparison of Image Quality and Dose Delivered Between Two Differing CT Imaging Modalities

PubMed Central

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

Image reconstruction from few-view CT data by gradient-domain dictionary learning.

PubMed

Hu, Zhanli; Liu, Qiegen; Zhang, Na; Zhang, Yunwan; Peng, Xi; Wu, Peter Z; Zheng, Hairong; Liang, Dong

2016-05-21

Decreasing the number of projections is an effective way to reduce the radiation dose exposed to patients in medical computed tomography (CT) imaging. However, incomplete projection data for CT reconstruction will result in artifacts and distortions. In this paper, a novel dictionary learning algorithm operating in the gradient-domain (Grad-DL) is proposed for few-view CT reconstruction. Specifically, the dictionaries are trained from the horizontal and vertical gradient images, respectively and the desired image is reconstructed subsequently from the sparse representations of both gradients by solving the least-square method. Since the gradient images are sparser than the image itself, the proposed approach could lead to sparser representations than conventional DL methods in the image-domain, and thus a better reconstruction quality is achieved. To evaluate the proposed Grad-DL algorithm, both qualitative and quantitative studies were employed through computer simulations as well as real data experiments on fan-beam and cone-beam geometry. The results show that the proposed algorithm can yield better images than the existing algorithms.

Monte Carlo simulations of medical imaging modalities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Estes, G.P.

Because continuous-energy Monte Carlo radiation transport calculations can be nearly exact simulations of physical reality (within data limitations, geometric approximations, transport algorithms, etc.), it follows that one should be able to closely approximate the results of many experiments from first-principles computations. This line of reasoning has led to various MCNP studies that involve simulations of medical imaging modalities and other visualization methods such as radiography, Anger camera, computerized tomography (CT) scans, and SABRINA particle track visualization. It is the intent of this paper to summarize some of these imaging simulations in the hope of stimulating further work, especially as computermore » power increases. Improved interpretation and prediction of medical images should ultimately lead to enhanced medical treatments. It is also reasonable to assume that such computations could be used to design new or more effective imaging instruments.« less

Novel medical image enhancement algorithms

NASA Astrophysics Data System (ADS)

Agaian, Sos; McClendon, Stephen A.

2010-01-01

In this paper, we present two novel medical image enhancement algorithms. The first, a global image enhancement algorithm, utilizes an alpha-trimmed mean filter as its backbone to sharpen images. The second algorithm uses a cascaded unsharp masking technique to separate the high frequency components of an image in order for them to be enhanced using a modified adaptive contrast enhancement algorithm. Experimental results from enhancing electron microscopy, radiological, CT scan and MRI scan images, using the MATLAB environment, are then compared to the original images as well as other enhancement methods, such as histogram equalization and two forms of adaptive contrast enhancement. An image processing scheme for electron microscopy images of Purkinje cells will also be implemented and utilized as a comparison tool to evaluate the performance of our algorithm.

Bariatric CT Imaging: Challenges and Solutions.

PubMed

Fursevich, Dzmitry M; LiMarzi, Gary M; O'Dell, Matthew C; Hernandez, Manuel A; Sensakovic, William F

2016-01-01

The obesity epidemic in the adult and pediatric populations affects all aspects of health care, including diagnostic imaging. With the increasing prevalence of obese and morbidly obese patients, bariatric computed tomographic (CT) imaging is becoming common in day-to-day radiology practice, and a basic understanding of the unique problems that bariatric patients pose to the imaging community is crucial in any setting. Because larger patients may not fit into conventional scanners, having a CT scanner with an adequate table load limit, a large gantry aperture, a large scan field of view, and a high-power generator is a prerequisite for bariatric imaging. Iterative reconstruction methods, high tube current, and high tube voltage can reduce the image noise that is frequently seen in bariatric CT images. Truncation artifacts, cropping artifacts, and ring artifacts frequently complicate the interpretation of CT images of larger patients. If recognized, these artifacts can be easily reduced by using the proper CT equipment, scan acquisition parameters, and postprocessing options. Lastly, because of complex contrast material dynamics, contrast material-enhanced studies of bariatric patients require special attention. Understanding how the rate of injection, the scan timing, and the total mass of iodine affect vascular and parenchymal enhancement will help to optimize contrast-enhanced studies in the bariatric population. This article familiarizes the reader with the challenges that are frequently encountered at CT imaging of bariatric patients, beginning with equipment selection and ending with a review of the most commonly encountered obesity-related artifacts and the technical considerations in the acquisition of contrast-enhanced images. (©)RSNA, 2016.

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

Agile convolutional neural network for pulmonary nodule classification using CT images.

PubMed

Zhao, Xinzhuo; Liu, Liyao; Qi, Shouliang; Teng, Yueyang; Li, Jianhua; Qian, Wei

2018-04-01

To distinguish benign from malignant pulmonary nodules using CT images is critical for their precise diagnosis and treatment. A new Agile convolutional neural network (CNN) framework is proposed to conquer the challenges of a small-scale medical image database and the small size of the nodules, and it improves the performance of pulmonary nodule classification using CT images. A hybrid CNN of LeNet and AlexNet is constructed through combining the layer settings of LeNet and the parameter settings of AlexNet. A dataset with 743 CT image nodule samples is built up based on the 1018 CT scans of LIDC to train and evaluate the Agile CNN model. Through adjusting the parameters of the kernel size, learning rate, and other factors, the effect of these parameters on the performance of the CNN model is investigated, and an optimized setting of the CNN is obtained finally. After finely optimizing the settings of the CNN, the estimation accuracy and the area under the curve can reach 0.822 and 0.877, respectively. The accuracy of the CNN is significantly dependent on the kernel size, learning rate, training batch size, dropout, and weight initializations. The best performance is achieved when the kernel size is set to [Formula: see text], the learning rate is 0.005, the batch size is 32, and dropout and Gaussian initialization are used. This competitive performance demonstrates that our proposed CNN framework and the optimization strategy of the CNN parameters are suitable for pulmonary nodule classification characterized by small medical datasets and small targets. The classification model might help diagnose and treat pulmonary nodules effectively.

Non-rigid registration of serial dedicated breast CT, longitudinal dedicated breast CT and PET/CT images using the diffeomorphic demons method.

PubMed

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.

Can we trust the calculation of texture indices of CT images? A phantom study.

PubMed

Caramella, Caroline; Allorant, Adrien; Orlhac, Fanny; Bidault, Francois; Asselain, Bernard; Ammari, Samy; Jaranowski, Patricia; Moussier, Aurelie; Balleyguier, Corinne; Lassau, Nathalie; Pitre-Champagnat, Stephanie

2018-04-01

Texture analysis is an emerging tool in the field of medical imaging analysis. However, many issues have been raised in terms of its use in assessing patient images and it is crucial to harmonize and standardize this new imaging measurement tool. This study was designed to evaluate the reliability of texture indices of CT images on a phantom including a reproducibility study, to assess the discriminatory capacity of indices potentially relevant in CT medical images and to determine their redundancy. For the reproducibility and discriminatory analysis, eight identical CT acquisitions were performed on a phantom including one homogeneous insert and two close heterogeneous inserts. Texture indices were selected for their high reproducibility and capability of discriminating different textures. For the redundancy analysis, 39 acquisitions of the same phantom were performed using varying acquisition parameters and a correlation matrix was used to explore the 2 × 2 relationships. LIFEx software was used to explore 34 different parameters including first order and texture indices. Only eight indices of 34 exhibited high reproducibility and discriminated textures from each other. Skewness and kurtosis from histogram were independent from the six other indices but were intercorrelated, the other six indices correlated in diverse degrees (entropy, dissimilarity, and contrast of the co-occurrence matrix, contrast of the Neighborhood Gray Level difference matrix, SZE, ZLNU of the Gray-Level Size Zone Matrix). Care should be taken when using texture analysis as a tool to characterize CT images because changes in quantitation may be primarily due to internal variability rather than from real physio-pathological effects. Some textural indices appear to be sufficiently reliable and capable to discriminate close textures on CT images. © 2018 American Association of Physicists in Medicine.

Hepatic CT image query using Gabor features

NASA Astrophysics Data System (ADS)

Zhao, Chenguang; Cheng, Hongyan; Zhuang, Tiange

2004-07-01

A retrieval scheme for liver computerize tomography (CT) images based on Gabor texture is presented. For each hepatic CT image, we manually delineate abnormal regions within liver area. Then, a continuous Gabor transform is utilized to analyze the texture of the pathology bearing region and extract the corresponding feature vectors. For a given sample image, we compare its feature vector with those of other images. Similar images with the highest rank are retrieved. In experiments, 45 liver CT images are collected, and the effectiveness of Gabor texture for content based retrieval is verified.

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.

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.

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

Flow behaviour of supercritical CO2 and brine in Berea sandstone during drainage and imbibition revealed by medical X-ray CT images

NASA Astrophysics Data System (ADS)

Zhang, Yi; Nishizawa, Osamu; Kiyama, Tamotsu; Chiyonobu, Shun; Xue, Ziqiu

2014-06-01

We injected Berea sandstone with supercritical CO2 and imaged the results with a medical X-ray computed tomography (CT) scanner. The images were acquired by injecting CO2 into a core of brine-saturated sandstone (drainage), and additional images were acquired during reinjection of brine (imbibition) after drainage. We then analysed the temporal variations of CO2 saturation maps obtained from the CT images. The experiments were performed under a confining pressure of 12 MPa, a pore pressure of 10 MPa and a temperature of 40 °C. Porosity and CO2 saturation were calculated for each image voxel of the rock on the basis of the Hounsfield unit values (CT numbers) measured at three states of saturation: dry, full brine saturation and full CO2 saturation. The saturation maps indicated that the distributions of CO2 and brine were controlled by the sub-core-scale heterogeneities which consisted of a laminated structure (bedding) with high- and low-porosity layers. During drainage, CO2 preferentially flowed through the high-porosity layers where most of the CO2 was entrapped during low flow-rate imbibition. The entrapped CO2 was flushed out when high flow-rate imbibition commenced. Plots of the voxel's CT number against porosity revealed the relationship between fluid replacement and porosity. By reference to the CT numbers at the full brine-saturated stage, differential CT numbers were classified into three bins corresponding to voxel porosity: high, medium and low porosity. Distributions of the differential CT number for the three porosity bins were bimodal and in order with respect to the porosity bins during both drainage and imbibitions; however, the order differed between the two stages. This difference suggested that different replacement mechanisms operated for the two processes. Spatial autocorrelation of CO2 saturation maps on sections perpendicular to the flow direction revealed remarkable changes during passage of the replacement fronts during both drainage and

Relationship between solitary pulmonary nodule lung cancer and CT image features based on gradual clustering

NASA Astrophysics Data System (ADS)

Zhang, Weipeng

2017-06-01

The relationship between the medical characteristics of lung cancers and computer tomography (CT) images are explored so as to improve the early diagnosis rate of lung cancers. This research collected CT images of patients with solitary pulmonary nodule lung cancer, and used gradual clustering methodology to classify them. Preliminary classifications were made, followed by continuous modification and iteration to determine the optimal condensation point, until iteration stability was achieved. Reasonable classification results were obtained. the clustering results fell into 3 categories. The first type of patients was mostly female, with ages between 50 and 65 years. CT images of solitary pulmonary nodule lung cancer for this group contain complete lobulation and burr, with pleural indentation; The second type of patients was mostly male with ages between 50 and 80 years. CT images of solitary pulmonary nodule lung cancer for this group contain complete lobulation and burr, but with no pleural indentation; The third type of patients was also mostly male with ages between 50 and 80 years. CT images for this group showed no abnormalities. the application of gradual clustering methodology can scientifically classify CT image features of patients with lung cancer in the initial lesion stage. These findings provide the basis for early detection and treatment of malignant lesions in patients with lung cancer.

Feature and Intensity Based Medical Image Registration Using Particle Swarm Optimization.

PubMed

Abdel-Basset, Mohamed; Fakhry, Ahmed E; El-Henawy, Ibrahim; Qiu, Tie; Sangaiah, Arun Kumar

2017-11-03

Image registration is an important aspect in medical image analysis, and kinds use in a variety of medical applications. Examples include diagnosis, pre/post surgery guidance, comparing/merging/integrating images from multi-modal like Magnetic Resonance Imaging (MRI), and Computed Tomography (CT). Whether registering images across modalities for a single patient or registering across patients for a single modality, registration is an effective way to combine information from different images into a normalized frame for reference. Registered datasets can be used for providing information relating to the structure, function, and pathology of the organ or individual being imaged. In this paper a hybrid approach for medical images registration has been developed. It employs a modified Mutual Information (MI) as a similarity metric and Particle Swarm Optimization (PSO) method. Computation of mutual information is modified using a weighted linear combination of image intensity and image gradient vector flow (GVF) intensity. In this manner, statistical as well as spatial image information is included into the image registration process. Maximization of the modified mutual information is effected using the versatile Particle Swarm Optimization which is developed easily with adjusted less parameter. The developed approach has been tested and verified successfully on a number of medical image data sets that include images with missing parts, noise contamination, and/or of different modalities (CT, MRI). The registration results indicate the proposed model as accurate and effective, and show the posture contribution in inclusion of both statistical and spatial image data to the developed approach.

Image mottle in abdominal CT.

PubMed

Ende, J F; Huda, W; Ros, P R; Litwiller, A L

1999-04-01

To investigate image mottle in conventional CT images of the abdomen as a function of radiographic technique factors and patient size. Water-filled phantoms simulating the abdomens of adult (32 cm in diameter) and pediatric (16 cm in diameter) patients were used to investigate image mottle in CT as a function of x-ray tube potential and mAs. CT images from 39 consecutive patients with noncontrast liver scans and 49 patients with iodine contrast scans were analyzed retrospectively. Measurements were made of the mean liver parenchyma Hounsfield unit value and the corresponding image mottle. For a given water phantom and x-ray tube potential, image mottle was proportional to the mAs-0.5. Increasing the phantom diameter from 16 cm (pediatric) to 32 cm increased the mottle by a factor of 2.4, and increasing the x-ray tube potential from 80 kVp to 140 kVp reduced the mottle by a factor of 2.5. All patients were scanned at 120 kVp, with no correlation between patient size and the x-ray tube mAs. The mean mottle level was 7.8 +/- 2.2 and 10.0 +/- 2.5 for the noncontrast and contrast studies, respectively. An increase in patient diameter of 3 cm would require approximately 65% more mAs to maintain the same level of image mottle. The mottle in abdominal CT images may be controlled by adjusting radiographic technique factors, which should be adjusted to take into account the size of the patient undergoing the examination.

Vision 20/20: Single photon counting x-ray detectors in medical imaging

PubMed Central

Taguchi, Katsuyuki; Iwanczyk, Jan S.

2013-01-01

Photon counting detectors (PCDs) with energy discrimination capabilities have been developed for medical x-ray computed tomography (CT) and x-ray (XR) imaging. Using detection mechanisms that are completely different from the current energy integrating detectors and measuring the material information of the object to be imaged, these PCDs have the potential not only to improve the current CT and XR images, such as dose reduction, but also to open revolutionary novel applications such as molecular CT and XR imaging. The performance of PCDs is not flawless, however, and it seems extremely challenging to develop PCDs with close to ideal characteristics. In this paper, the authors offer our vision for the future of PCD-CT and PCD-XR with the review of the current status and the prediction of (1) detector technologies, (2) imaging technologies, (3) system technologies, and (4) potential clinical benefits with PCDs. PMID:24089889

Brain medical image diagnosis based on corners with importance-values.

PubMed

Gao, Linlin; Pan, Haiwei; Li, Qing; Xie, Xiaoqin; Zhang, Zhiqiang; Han, Jinming; Zhai, Xiao

2017-11-21

Brain disorders are one of the top causes of human death. Generally, neurologists analyze brain medical images for diagnosis. In the image analysis field, corners are one of the most important features, which makes corner detection and matching studies essential. However, existing corner detection studies do not consider the domain information of brain. This leads to many useless corners and the loss of significant information. Regarding corner matching, the uncertainty and structure of brain are not employed in existing methods. Moreover, most corner matching studies are used for 3D image registration. They are inapplicable for 2D brain image diagnosis because of the different mechanisms. To address these problems, we propose a novel corner-based brain medical image classification method. Specifically, we automatically extract multilayer texture images (MTIs) which embody diagnostic information from neurologists. Moreover, we present a corner matching method utilizing the uncertainty and structure of brain medical images and a bipartite graph model. Finally, we propose a similarity calculation method for diagnosis. Brain CT and MRI image sets are utilized to evaluate the proposed method. First, classifiers are trained in N-fold cross-validation analysis to produce the best θ and K. Then independent brain image sets are tested to evaluate the classifiers. Moreover, the classifiers are also compared with advanced brain image classification studies. For the brain CT image set, the proposed classifier outperforms the comparison methods by at least 8% on accuracy and 2.4% on F1-score. Regarding the brain MRI image set, the proposed classifier is superior to the comparison methods by more than 7.3% on accuracy and 4.9% on F1-score. Results also demonstrate that the proposed method is robust to different intensity ranges of brain medical image. In this study, we develop a robust corner-based brain medical image classifier. Specifically, we propose a corner detection

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.

The appearance and effects of metallic implants in CT images.

PubMed

Kairn, T; Crowe, S B; Fogg, P; Trapp, J V

2013-06-01

The computed tomography (CT) imaging artefacts that metallic medical implants produce in surrounding tissues are usually contoured and over-ridden during radiotherapy treatment planning. In cases where radiotherapy treatment beams unavoidably pass though implants, it is especially important to understand the imaging artefacts that may occur within the implants themselves. This study examines CT images of a set of simple metallic objects, immersed in water, in order to evaluate reliability and variability of CT numbers (Hounsfield units, HUs) within medical implants. Model implants with a range of sizes (heights from 2.2 to 49.6 mm), electron densities (from 2.3 to 7.7 times the electron density of water) and effective atomic numbers (from 3.9 to 9.0 times the effective atomic number of water in a CT X-ray beam) were created by stacking metal coins from several currencies. These 'implants' were CT scanned within a large (31.0 cm across) and a small (12.8 cm across) water phantom. Resulting HU values are as much as 50 % lower than the result of extrapolating standard electron density calibration data (obtained for tissue and bone densities) up to the metal densities and there is a 6 % difference between the results obtained by scanning with 120 and 140 kVp tube potentials. Profiles through the implants show localised cupping artefacts, within the implants, as well as a gradual decline in HU outside the implants that can cause the implants' sizes to be over estimated by 1.3-9.0 mm. These effects are exacerbated when the implants are scanned in the small phantom or at the side of the large phantom, due to reduced pre-hardening of the X-ray beam in these configurations. These results demonstrate the necessity of over-riding the densities of metallic implants, as well as their artefacts in tissue, in order to obtain accurate radiotherapy dose calculations.

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.

Image analysis and modeling in medical image computing. Recent developments and advances.

PubMed

Handels, H; Deserno, T M; Meinzer, H-P; Tolxdorff, T

2012-01-01

Medical image computing is of growing importance in medical diagnostics and image-guided therapy. Nowadays, image analysis systems integrating advanced image computing methods are used in practice e.g. to extract quantitative image parameters or to support the surgeon during a navigated intervention. However, the grade of automation, accuracy, reproducibility and robustness of medical image computing methods has to be increased to meet the requirements in clinical routine. In the focus theme, recent developments and advances in the field of modeling and model-based image analysis are described. The introduction of models in the image analysis process enables improvements of image analysis algorithms in terms of automation, accuracy, reproducibility and robustness. Furthermore, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients. Selected contributions are assembled to present latest advances in the field. The authors were invited to present their recent work and results based on their outstanding contributions to the Conference on Medical Image Computing BVM 2011 held at the University of Lübeck, Germany. All manuscripts had to pass a comprehensive peer review. Modeling approaches and model-based image analysis methods showing new trends and perspectives in model-based medical image computing are described. Complex models are used in different medical applications and medical images like radiographic images, dual-energy CT images, MR images, diffusion tensor images as well as microscopic images are analyzed. The applications emphasize the high potential and the wide application range of these methods. The use of model-based image analysis methods can improve segmentation quality as well as the accuracy and reproducibility of quantitative image analysis. Furthermore, image-based models enable new insights and can lead to a deeper understanding of complex dynamic mechanisms in the human body

CT image electron density quantification in regions with metal implants: implications for radiotherapy treatment planning

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

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.

The segmentation of bones in pelvic CT images based on extraction of key frames.

PubMed

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.

SU-E-J-242: Volume-Dependence of Quantitative Imaging Features From CT and CE-CT Images of NSCLC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fave, X; Fried, D; UT Health Science Center Graduate School of Biomedical Sciences, Houston, TX

Purpose: To determine whether tumor volume plays a significant role in the values obtained for texture features when they are extracted from computed tomography (CT) images of non-small cell lung cancer (NSCLC). We also sought to identify whether features can be reliably measured at all volumes or if a minimum volume threshold should be recommended. Methods: Eleven features were measured on 40 CT and 32 contrast-enhanced CT (CECT) patient images for this study. Features were selected for their prognostic/diagnostic value in previous publications. Direct correlations between these textures and volume were evaluated using the Spearman correlation coefficient. Any texture thatmore » the Wilcoxon rank-sum test was used to compare the variation above and below a volume cutoff. Four different volume thresholds (5, 10, 15, and 20 cm{sup 3}) were tested. Results: Four textures were found to be significantly correlated with volume in both the CT and CE-CT images. These were busyness, coarseness, gray-level nonuniformity, and run-length nonuniformity with correlation coefficients of 0.92, −0.96, 0.94, and 0.98 for the CT images and 0.95, −0.97, 0.98, and 0.98 for the CE-CT images. After volume normalization, the correlation coefficients decreased substantially. For the data obtained from the CT images, the results of the Wilcoxon rank-sum test were significant when volume thresholds of 5–15 cm3 were used. No volume threshold was shown to be significant for the CE-CT data. Conclusion: Equations for four features that have been used in several published studies were found to be volume-dependent. Future studies should consider implementing normalization factors or removing these features entirely to prevent this potential source of redundancy or bias. This work was supported in part by National Cancer Institute grant R03CA178495-01. Xenia Fave is a recipient of the American Association of Physicists in Medicine Graduate Fellowship.« less

The Handbook of Medical Image Perception and Techniques

NASA Astrophysics Data System (ADS)

Samei, Ehsan; Krupinski, Elizabeth

2014-07-01

1. Medical image perception Ehsan Samei and Elizabeth Krupinski; Part I. Historical Reflections and Theoretical Foundations: 2. A short history of image perception in medical radiology Harold Kundel and Calvin Nodine; 3. Spatial vision research without noise Arthur Burgess; 4. Signal detection theory, a brief history Arthur Burgess; 5. Signal detection in radiology Arthur Burgess; 6. Lessons from dinners with the giants of modern image science Robert Wagner; Part II. Science of Image Perception: 7. Perceptual factors in reading medical images Elizabeth Krupinski; 8. Cognitive factors in reading medical images David Manning; 9. Satisfaction of search in traditional radiographic imaging Kevin Berbaum, Edmund Franken, Robert Caldwell and Kevin Schartz; 10. The role of expertise in radiologic image interpretation Calvin Nodine and Claudia Mello-Thoms; 11. A primer of image quality and its perceptual relevance Robert Saunders and Ehsan Samei; 12. Beyond the limitations of human vision Maria Petrou; Part III. Perception Metrology: 13. Logistical issues in designing perception experiments Ehsan Samei and Xiang Li; 14. ROC analysis: basic concepts and practical applications Georgia Tourassi; 15. Multi-reader ROC Steve Hillis; 16. Recent developments in FROC methodology Dev Chakraborty; 17. Observer models as a surrogate to perception experiments Craig Abbey and Miguel Eckstein; 18. Implementation of observer models Matthew Kupinski; Part IV. Decision Support and Computer Aided Detection: 19. CAD: an image perception perspective Maryellen Giger and Weijie Chen; 20. Common designs of CAD studies Yulei Jiang; 21. Perceptual effect of CAD in reading chest images Matthew Freedman and Teresa Osicka; 22. Perceptual issues in mammography and CAD Michael Ulissey; 23. How perceptual factors affect the use and accuracy of CAD for interpretation of CT images Ronald Summers; 24. CAD: risks and benefits for radiologists' decisions Eugenio Alberdi, Andrey Povyakalo, Lorenzo Strigini and

The Handbook of Medical Image Perception and Techniques

NASA Astrophysics Data System (ADS)

Samei, Ehsan; Krupinski, Elizabeth

2009-12-01

1. Medical image perception Ehsan Samei and Elizabeth Krupinski; Part I. Historical Reflections and Theoretical Foundations: 2. A short history of image perception in medical radiology Harold Kundel and Calvin Nodine; 3. Spatial vision research without noise Arthur Burgess; 4. Signal detection theory, a brief history Arthur Burgess; 5. Signal detection in radiology Arthur Burgess; 6. Lessons from dinners with the giants of modern image science Robert Wagner; Part II. Science of Image Perception: 7. Perceptual factors in reading medical images Elizabeth Krupinski; 8. Cognitive factors in reading medical images David Manning; 9. Satisfaction of search in traditional radiographic imaging Kevin Berbaum, Edmund Franken, Robert Caldwell and Kevin Schartz; 10. The role of expertise in radiologic image interpretation Calvin Nodine and Claudia Mello-Thoms; 11. A primer of image quality and its perceptual relevance Robert Saunders and Ehsan Samei; 12. Beyond the limitations of human vision Maria Petrou; Part III. Perception Metrology: 13. Logistical issues in designing perception experiments Ehsan Samei and Xiang Li; 14. ROC analysis: basic concepts and practical applications Georgia Tourassi; 15. Multi-reader ROC Steve Hillis; 16. Recent developments in FROC methodology Dev Chakraborty; 17. Observer models as a surrogate to perception experiments Craig Abbey and Miguel Eckstein; 18. Implementation of observer models Matthew Kupinski; Part IV. Decision Support and Computer Aided Detection: 19. CAD: an image perception perspective Maryellen Giger and Weijie Chen; 20. Common designs of CAD studies Yulei Jiang; 21. Perceptual effect of CAD in reading chest images Matthew Freedman and Teresa Osicka; 22. Perceptual issues in mammography and CAD Michael Ulissey; 23. How perceptual factors affect the use and accuracy of CAD for interpretation of CT images Ronald Summers; 24. CAD: risks and benefits for radiologists' decisions Eugenio Alberdi, Andrey Povyakalo, Lorenzo Strigini and

Image Quality and Radiation Dose for Prospectively Triggered Coronary CT Angiography: 128-Slice Single-Source CT versus First-Generation 64-Slice Dual-Source CT

NASA Astrophysics Data System (ADS)

Gu, Jin; Shi, He-Shui; Han, Ping; Yu, Jie; Ma, Gui-Na; Wu, Sheng

2016-10-01

This study sought to compare the image quality and radiation dose of coronary computed tomography angiography (CCTA) from prospectively triggered 128-slice CT (128-MSCT) versus dual-source 64-slice CT (DSCT). The study was approved by the Medical Ethics Committee at Tongji Medical College of Huazhong University of Science and Technology. Eighty consecutive patients with stable heart rates lower than 70 bpm were enrolled. Forty patients were scanned with 128-MSCT, and the other 40 patients were scanned with DSCT. Two radiologists independently assessed the image quality in segments (diameter >1 mm) according to a three-point scale (1: excellent; 2: moderate; 3: insufficient). The CCTA radiation dose was calculated. Eighty patients with 526 segments in the 128-MSCT group and 544 segments in the DSCT group were evaluated. The image quality 1, 2 and 3 scores were 91.6%, 6.9% and 1.5%, respectively, for the 128-MSCT group and 97.6%, 1.7% and 0.7%, respectively, for the DSCT group, and there was a statistically significant inter-group difference (P ≤ 0.001). The effective doses were 3.0 mSv in the 128-MSCT group and 4.5 mSv in the DSCT group (P ≤ 0.001). Compared with DSCT, CCTA with prospectively triggered 128-MSCT had adequate image quality and a 33.3% lower radiation dose.

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.

Automatic and hierarchical segmentation of the human skeleton in CT images.

PubMed

Fu, Yabo; Liu, Shi; Li, Harold; Yang, Deshan

2017-04-07

Accurate segmentation of each bone of the human skeleton is useful in many medical disciplines. The results of bone segmentation could facilitate bone disease diagnosis and post-treatment assessment, and support planning and image guidance for many treatment modalities including surgery and radiation therapy. As a medium level medical image processing task, accurate bone segmentation can facilitate automatic internal organ segmentation by providing stable structural reference for inter- or intra-patient registration and internal organ localization. Even though bones in CT images can be visually observed with minimal difficulty due to the high image contrast between the bony structures and surrounding soft tissues, automatic and precise segmentation of individual bones is still challenging due to the many limitations of the CT images. The common limitations include low signal-to-noise ratio, insufficient spatial resolution, and indistinguishable image intensity between spongy bones and soft tissues. In this study, a novel and automatic method is proposed to segment all the major individual bones of the human skeleton above the upper legs in CT images based on an articulated skeleton atlas. The reported method is capable of automatically segmenting 62 major bones, including 24 vertebrae and 24 ribs, by traversing a hierarchical anatomical tree and by using both rigid and deformable image registration. The degrees of freedom of femora and humeri are modeled to support patients in different body and limb postures. The segmentation results are evaluated using the Dice coefficient and point-to-surface error (PSE) against manual segmentation results as the ground-truth. The results suggest that the reported method can automatically segment and label the human skeleton into detailed individual bones with high accuracy. The overall average Dice coefficient is 0.90. The average PSEs are 0.41 mm for the mandible, 0.62 mm for cervical vertebrae, 0.92 mm for thoracic

Automatic and hierarchical segmentation of the human skeleton in CT images

NASA Astrophysics Data System (ADS)

Fu, Yabo; Liu, Shi; Li, H. Harold; Yang, Deshan

2017-04-01

Accurate segmentation of each bone of the human skeleton is useful in many medical disciplines. The results of bone segmentation could facilitate bone disease diagnosis and post-treatment assessment, and support planning and image guidance for many treatment modalities including surgery and radiation therapy. As a medium level medical image processing task, accurate bone segmentation can facilitate automatic internal organ segmentation by providing stable structural reference for inter- or intra-patient registration and internal organ localization. Even though bones in CT images can be visually observed with minimal difficulty due to the high image contrast between the bony structures and surrounding soft tissues, automatic and precise segmentation of individual bones is still challenging due to the many limitations of the CT images. The common limitations include low signal-to-noise ratio, insufficient spatial resolution, and indistinguishable image intensity between spongy bones and soft tissues. In this study, a novel and automatic method is proposed to segment all the major individual bones of the human skeleton above the upper legs in CT images based on an articulated skeleton atlas. The reported method is capable of automatically segmenting 62 major bones, including 24 vertebrae and 24 ribs, by traversing a hierarchical anatomical tree and by using both rigid and deformable image registration. The degrees of freedom of femora and humeri are modeled to support patients in different body and limb postures. The segmentation results are evaluated using the Dice coefficient and point-to-surface error (PSE) against manual segmentation results as the ground-truth. The results suggest that the reported method can automatically segment and label the human skeleton into detailed individual bones with high accuracy. The overall average Dice coefficient is 0.90. The average PSEs are 0.41 mm for the mandible, 0.62 mm for cervical vertebrae, 0.92 mm for thoracic

Physics of cardiac imaging with multiple-row detector CT.

PubMed

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.

Performance evaluation of 2D and 3D deep learning approaches for automatic segmentation of multiple organs on CT images

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.

Medical image processing on the GPU - past, present and future.

PubMed

Eklund, Anders; Dufort, Paul; Forsberg, Daniel; LaConte, Stephen M

2013-12-01

Graphics processing units (GPUs) are used today in a wide range of applications, mainly because they can dramatically accelerate parallel computing, are affordable and energy efficient. In the field of medical imaging, GPUs are in some cases crucial for enabling practical use of computationally demanding algorithms. This review presents the past and present work on GPU accelerated medical image processing, and is meant to serve as an overview and introduction to existing GPU implementations. The review covers GPU acceleration of basic image processing operations (filtering, interpolation, histogram estimation and distance transforms), the most commonly used algorithms in medical imaging (image registration, image segmentation and image denoising) and algorithms that are specific to individual modalities (CT, PET, SPECT, MRI, fMRI, DTI, ultrasound, optical imaging and microscopy). The review ends by highlighting some future possibilities and challenges. Copyright © 2013 Elsevier B.V. All rights reserved.

Radionuclide bone scan SPECT-CT: lowering the dose of CT significantly reduces radiation dose without impacting CT image quality

PubMed Central

Gupta, Sandeep Kumar; Trethewey, Scott; Brooker, Bree; Rutherford, Natalie; Diffey, Jenny; Viswanathan, Suresh; Attia, John

2017-01-01

The CT component of SPECT-CT is required for attenuation correction and anatomical localization of the uptake on SPECT but there is no guideline about the optimal CT acquisition parameters. In our department, a standard CT acquisition protocol was changed in 2013 to give lower radiation dose to the patient. In this study, we retrospectively compared the effects on patient dose as well as the CT image quality with current versus older CT protocols. Ninety nine consecutive patients [n=51 Standard dose ‘old’ protocol (SDP); n=48 lower dose ‘new’ protocol (LDP)] with lumbar spine SPECT-CT for bone scan were examined. The main differences between the two protocols were that SDP used 130 kVp tube voltage and reference current-time product of 70 mAs whereas the LDP used 110 kVp and 40 mAs respectively. Various quantitative parameters from the CT images were obtained and the images were also rated blindly by two experienced nuclear medicine physicians for bony definition and noise. The mean calculated dose length product of the LDP group (121.5±39.6 mGy.cm) was significantly lower compared to the SDP group patients (266.9±96.9 mGy.cm; P<0.0001). This translated into a significant reduction in the mean effective dose to 1.8 mSv from 4.0 mSv. The physicians reported better CT image quality for the bony structures in LDP group although for soft tissue structures, the SDP group had better image quality. The optimized new CT acquisition protocol significantly reduced the radiation dose to the patient and in-fact improved CT image quality for the assessment of bony structures. PMID:28533938

Multi-institutional MicroCT image comparison of image-guided small animal irradiators

NASA Astrophysics Data System (ADS)

Johnstone, Chris D.; Lindsay, Patricia; E Graves, Edward; Wong, Eugene; Perez, Jessica R.; Poirier, Yannick; Ben-Bouchta, Youssef; Kanesalingam, Thilakshan; Chen, Haijian; E Rubinstein, Ashley; Sheng, Ke; Bazalova-Carter, Magdalena

2017-07-01

To recommend imaging protocols and establish tolerance levels for microCT image quality assurance (QA) performed on conformal image-guided small animal irradiators. A fully automated QA software SAPA (small animal phantom analyzer) for image analysis of the commercial Shelley micro-CT MCTP 610 phantom was developed, in which quantitative analyses of CT number linearity, signal-to-noise ratio (SNR), uniformity and noise, geometric accuracy, spatial resolution by means of modulation transfer function (MTF), and CT contrast were performed. Phantom microCT scans from eleven institutions acquired with four image-guided small animal irradiator units (including the commercial PXi X-RAD SmART and Xstrahl SARRP systems) with varying parameters used for routine small animal imaging were analyzed. Multi-institutional data sets were compared using SAPA, based on which tolerance levels for each QA test were established and imaging protocols for QA were recommended. By analyzing microCT data from 11 institutions, we established image QA tolerance levels for all image quality tests. CT number linearity set to R 2  >  0.990 was acceptable in microCT data acquired at all but three institutions. Acceptable SNR  >  36 and noise levels  <55 HU were obtained at five of the eleven institutions, where failing scans were acquired with current-exposure time of less than 120 mAs. Acceptable spatial resolution (>1.5 lp mm-1 for MTF  =  0.2) was obtained at all but four institutions due to their large image voxel size used (>0.275 mm). Ten of the eleven institutions passed the set QA tolerance for geometric accuracy (<1.5%) and nine of the eleven institutions passed the QA tolerance for contrast (>2000 HU for 30 mgI ml-1). We recommend performing imaging QA with 70 kVp, 1.5 mA, 120 s imaging time, 0.20 mm voxel size, and a frame rate of 5 fps for the PXi X-RAD SmART. For the Xstrahl SARRP, we recommend using 60 kVp, 1.0 mA, 240 s imaging time, 0.20�

Accuracy of CT-based attenuation correction in PET/CT bone imaging

NASA Astrophysics Data System (ADS)

Abella, Monica; Alessio, Adam M.; Mankoff, David A.; MacDonald, Lawrence R.; Vaquero, Juan Jose; Desco, Manuel; Kinahan, Paul E.

2012-05-01

We evaluate the accuracy of scaling CT images for attenuation correction of PET data measured for bone. While the standard tri-linear approach has been well tested for soft tissues, the impact of CT-based attenuation correction on the accuracy of tracer uptake in bone has not been reported in detail. We measured the accuracy of attenuation coefficients of bovine femur segments and patient data using a tri-linear method applied to CT images obtained at different kVp settings. Attenuation values at 511 keV obtained with a 68Ga/68Ge transmission scan were used as a reference standard. The impact of inaccurate attenuation images on PET standardized uptake values (SUVs) was then evaluated using simulated emission images and emission images from five patients with elevated levels of FDG uptake in bone at disease sites. The CT-based linear attenuation images of the bovine femur segments underestimated the true values by 2.9 ± 0.3% for cancellous bone regardless of kVp. For compact bone the underestimation ranged from 1.3% at 140 kVp to 14.1% at 80 kVp. In the patient scans at 140 kVp the underestimation was approximately 2% averaged over all bony regions. The sensitivity analysis indicated that errors in PET SUVs in bone are approximately proportional to errors in the estimated attenuation coefficients for the same regions. The variability in SUV bias also increased approximately linearly with the error in linear attenuation coefficients. These results suggest that bias in bone uptake SUVs of PET tracers ranges from 2.4% to 5.9% when using CT scans at 140 and 120 kVp for attenuation correction. Lower kVp scans have the potential for considerably more error in dense bone. This bias is present in any PET tracer with bone uptake but may be clinically insignificant for many imaging tasks. However, errors from CT-based attenuation correction methods should be carefully evaluated if quantitation of tracer uptake in bone is important.

The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Reference Database of Lung Nodules on CT Scans

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

Brain CT image similarity retrieval method based on uncertain location graph.

PubMed

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.

Relative location prediction in CT scan images using convolutional neural networks.

PubMed

Guo, Jiajia; Du, Hongwei; Zhu, Jianyue; Yan, Ting; Qiu, Bensheng

2018-07-01

Relative location prediction in computed tomography (CT) scan images is a challenging problem. Many traditional machine learning methods have been applied in attempts to alleviate this problem. However, the accuracy and speed of these methods cannot meet the requirement of medical scenario. In this paper, we propose a regression model based on one-dimensional convolutional neural networks (CNN) to determine the relative location of a CT scan image both quickly and precisely. In contrast to other common CNN models that use a two-dimensional image as an input, the input of this CNN model is a feature vector extracted by a shape context algorithm with spatial correlation. Normalization via z-score is first applied as a pre-processing step. Then, in order to prevent overfitting and improve model's performance, 20% of the elements of the feature vectors are randomly set to zero. This CNN model consists primarily of three one-dimensional convolutional layers, three dropout layers and two fully-connected layers with appropriate loss functions. A public dataset is employed to validate the performance of the proposed model using a 5-fold cross validation. Experimental results demonstrate an excellent performance of the proposed model when compared with contemporary techniques, achieving a median absolute error of 1.04 cm and mean absolute error of 1.69 cm. The time taken for each relative location prediction is approximately 2 ms. Results indicate that the proposed CNN method can contribute to a quick and accurate relative location prediction in CT scan images, which can improve efficiency of the medical picture archiving and communication system in the future. Copyright © 2018 Elsevier B.V. All rights reserved.

SU-F-I-08: CT Image Ring Artifact Reduction Based On Prior Image

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yuan, C; Qi, H; Chen, Z

Purpose: In computed tomography (CT) system, CT images with ring artifacts will be reconstructed when some adjacent bins of detector don’t work. The ring artifacts severely degrade CT image quality. We present a useful CT ring artifacts reduction based on projection data correction, aiming at estimating the missing data of projection data accurately, thus removing the ring artifacts of CT images. Methods: The method consists of ten steps: 1) Identification of abnormal pixel line in projection sinogram; 2) Linear interpolation within the pixel line of projection sinogram; 3) FBP reconstruction using interpolated projection data; 4) Filtering FBP image using meanmore » filter; 5) Forwarding projection of filtered FBP image; 6) Subtraction forwarded projection from original projection; 7) Linear interpolation of abnormal pixel line area in the subtraction projection; 8) Adding the interpolated subtraction projection on the forwarded projection; 9) FBP reconstruction using corrected projection data; 10) Return to step 4 until the pre-set iteration number is reached. The method is validated on simulated and real data to restore missing projection data and reconstruct ring artifact-free CT images. Results: We have studied impact of amount of dead bins of CT detector on the accuracy of missing data estimation in projection sinogram. For the simulated case with a resolution of 256 by 256 Shepp-Logan phantom, three iterations are sufficient to restore projection data and reconstruct ring artifact-free images when the dead bins rating is under 30%. The dead-bin-induced artifacts are substantially reduced. More iteration number is needed to reconstruct satisfactory images while the rating of dead bins increases. Similar results were found for a real head phantom case. Conclusion: A practical CT image ring artifact correction scheme based on projection data is developed. This method can produce ring artifact-free CT images feasibly and effectively.« less

Diagnostic and clinical benefit of combined coronary calcium and perfusion assessment in patients undergoing PET/CT myocardial perfusion stress imaging.

PubMed

Bybee, Kevin A; Lee, John; Markiewicz, Richard; Longmore, Ryan; McGhie, A Iain; O'Keefe, James H; Hsu, Bai-Ling; Kennedy, Kevin; Thompson, Randall C; Bateman, Timothy M

2010-04-01

A limitation of stress myocardial perfusion imaging (MPI) is the inability to detect non-obstructive coronary artery disease (CAD). One advantage of MPI with a hybrid CT device is the ability to obtain same-setting measurement of the coronary artery calcium score (CACS). Utilizing our single-center nuclear database, we identified 760 consecutive patients with: (1) no CAD history; (2) a normal clinically indicated Rb-82 PET/CT stress perfusion study; and (3) a same-setting CAC scan. 487 of 760 patients (64.1%) had subclinical CAD based on an abnormal CACS. Of those with CAC, the CACS was > or =100, > or =400, and > or =1000 in 47.0%, 22.4%, and 8.4% of patients, respectively. Less than half of the patients with CAC were receiving aspirin or statin medications prior to PET/CT imaging. Patients with CAC were more likely to be initiated or optimized on proven medical therapy for CAD immediately following PET/CT MPI compared to those without CAC. Subclinical CAD is common in patients without known CAD and normal myocardial perfusion assessed by hybrid PET/CT imaging. Identification of CAC influences subsequent physician prescribing patterns such that those with CAC are more likely to be treated with proven medical therapy for the treatment of CAD.

Effect of clinical decision rules, patient cost and malpractice information on clinician brain CT image ordering: a randomized controlled trial.

PubMed

Gimbel, Ronald W; Pirrallo, Ronald G; Lowe, Steven C; Wright, David W; Zhang, Lu; Woo, Min-Jae; Fontelo, Paul; Liu, Fang; Connor, Zachary

2018-03-12

The frequency of head computed tomography (CT) imaging for mild head trauma patients has raised safety and cost concerns. Validated clinical decision rules exist in the published literature and on-line sources to guide medical image ordering but are often not used by emergency department (ED) clinicians. Using simulation, we explored whether the presentation of a clinical decision rule (i.e. Canadian CT Head Rule - CCHR), findings from malpractice cases related to clinicians not ordering CT imaging in mild head trauma cases, and estimated patient out-of-pocket cost might influence clinician brain CT ordering. Understanding what type and how information may influence clinical decision making in the ordering advanced medical imaging is important in shaping the optimal design and implementation of related clinical decision support systems. Multi-center, double-blinded simulation-based randomized controlled trial. Following standardized clinical vignette presentation, clinicians made an initial imaging decision for the patient. This was followed by additional information on decision support rules, malpractice outcome review, and patient cost; each with opportunity to modify their initial order. The malpractice and cost information differed by assigned group to test the any temporal relationship. The simulation closed with a second vignette and an imaging decision. One hundred sixteen of the 167 participants (66.9%) initially ordered a brain CT scan. After CCHR presentation, the number of clinicians ordering a CT dropped to 76 (45.8%), representing a 21.1% reduction in CT ordering (P = 0.002). This reduction in CT ordering was maintained, in comparison to initial imaging orders, when presented with malpractice review information (p = 0.002) and patient cost information (p = 0.002). About 57% of clinicians changed their order during study, while 43% never modified their imaging order. This study suggests that ED clinician brain CT imaging decisions may be

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

Full-Body CT Scans - What You Need to Know

MedlinePlus

... Medical Imaging Medical X-ray Imaging Full-Body CT Scans - What You Need to Know Share Tweet ... new service for health-conscious people: "Whole-body CT screening." This typically involves scanning the body from ...

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

The impact of skull bone intensity on the quality of compressed CT neuro images

NASA Astrophysics Data System (ADS)

Kowalik-Urbaniak, Ilona; Vrscay, Edward R.; Wang, Zhou; Cavaro-Menard, Christine; Koff, David; Wallace, Bill; Obara, Boguslaw

2012-02-01

The increasing use of technologies such as CT and MRI, along with a continuing improvement in their resolution, has contributed to the explosive growth of digital image data being generated. Medical communities around the world have recognized the need for efficient storage, transmission and display of medical images. For example, the Canadian Association of Radiologists (CAR) has recommended compression ratios for various modalities and anatomical regions to be employed by lossy JPEG and JPEG2000 compression in order to preserve diagnostic quality. Here we investigate the effects of the sharp skull edges present in CT neuro images on JPEG and JPEG2000 lossy compression. We conjecture that this atypical effect is caused by the sharp edges between the skull bone and the background regions as well as between the skull bone and the interior regions. These strong edges create large wavelet coefficients that consume an unnecessarily large number of bits in JPEG2000 compression because of its bitplane coding scheme, and thus result in reduced quality at the interior region, which contains most diagnostic information in the image. To validate the conjecture, we investigate a segmentation based compression algorithm based on simple thresholding and morphological operators. As expected, quality is improved in terms of PSNR as well as the structural similarity (SSIM) image quality measure, and its multiscale (MS-SSIM) and informationweighted (IW-SSIM) versions. This study not only supports our conjecture, but also provides a solution to improve the performance of JPEG and JPEG2000 compression for specific types of CT images.

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.

A feasibility study of X-ray phase-contrast mammographic tomography at the Imaging and Medical beamline of the Australian Synchrotron.

PubMed

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.

Image Reconstruction for Hybrid True-Color Micro-CT

PubMed Central

Xu, Qiong; Yu, Hengyong; Bennett, James; He, Peng; Zainon, Rafidah; Doesburg, Robert; Opie, Alex; Walsh, Mike; Shen, Haiou; Butler, Anthony; Butler, Phillip; Mou, Xuanqin; Wang, Ge

2013-01-01

X-ray micro-CT is an important imaging tool for biomedical researchers. Our group has recently proposed a hybrid “true-color” micro-CT system to improve contrast resolution with lower system cost and radiation dose. The system incorporates an energy-resolved photon-counting true-color detector into a conventional micro-CT configuration, and can be used for material decomposition. In this paper, we demonstrate an interior color-CT image reconstruction algorithm developed for this hybrid true-color micro-CT system. A compressive sensing-based statistical interior tomography method is employed to reconstruct each channel in the local spectral imaging chain, where the reconstructed global gray-scale image from the conventional imaging chain served as the initial guess. Principal component analysis was used to map the spectral reconstructions into the color space. The proposed algorithm was evaluated by numerical simulations, physical phantom experiments, and animal studies. The results confirm the merits of the proposed algorithm, and demonstrate the feasibility of the hybrid true-color micro-CT system. Additionally, a “color diffusion” phenomenon was observed whereby high-quality true-color images are produced not only inside the region of interest, but also in neighboring regions. It appears harnessing that this phenomenon could potentially reduce the color detector size for a given ROI, further reducing system cost and radiation dose. PMID:22481806

Deformable planning CT to cone-beam CT image registration in head-and-neck cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hou Jidong; Guerrero, Mariana; Chen, Wenjuan

2011-04-15

Purpose: The purpose of this work was to implement and validate a deformable CT to cone-beam computed tomography (CBCT) image registration method in head-and-neck cancer to eventually facilitate automatic target delineation on CBCT. Methods: Twelve head-and-neck cancer patients underwent a planning CT and weekly CBCT during the 5-7 week treatment period. The 12 planning CT images (moving images) of these patients were registered to their weekly CBCT images (fixed images) via the symmetric force Demons algorithm and using a multiresolution scheme. Histogram matching was used to compensate for the intensity difference between the two types of images. Using nine knownmore » anatomic points as registration targets, the accuracy of the registration was evaluated using the target registration error (TRE). In addition, region-of-interest (ROI) contours drawn on the planning CT were morphed to the CBCT images and the volume overlap index (VOI) between registered contours and manually delineated contours was evaluated. Results: The mean TRE value of the nine target points was less than 3.0 mm, the slice thickness of the planning CT. Of the 369 target points evaluated for registration accuracy, the average TRE value was 2.6{+-}0.6 mm. The mean TRE for bony tissue targets was 2.4{+-}0.2 mm, while the mean TRE for soft tissue targets was 2.8{+-}0.2 mm. The average VOI between the registered and manually delineated ROI contours was 76.2{+-}4.6%, which is consistent with that reported in previous studies. Conclusions: The authors have implemented and validated a deformable image registration method to register planning CT images to weekly CBCT images in head-and-neck cancer cases. The accuracy of the TRE values suggests that they can be used as a promising tool for automatic target delineation on CBCT.« less

Reducing image noise in computed tomography (CT) colonography: effect of an integrated circuit CT detector.

PubMed

Liu, Yu; Leng, Shuai; Michalak, Gregory J; Vrieze, Thomas J; Duan, Xinhui; Qu, Mingliang; Shiung, Maria M; McCollough, Cynthia H; Fletcher, Joel G

2014-01-01

To investigate whether the integrated circuit (IC) detector results in reduced noise in computed tomography (CT) colonography (CTC). Three hundred sixty-six consecutive patients underwent clinically indicated CTC using the same CT scanner system, except for a difference in CT detectors (IC or conventional). Image noise, patient size, and scanner radiation output (volume CT dose index) were quantitatively compared between patient cohorts using each detector system, with separate comparisons for the abdomen and pelvis. For the abdomen and pelvis, despite significantly larger patient sizes in the IC detector cohort (both P < 0.001), image noise was significantly lower (both P < 0.001), whereas volume CT dose index was unchanged (both P > 0.18). Based on the observed image noise reduction, radiation dose could alternatively be reduced by approximately 20% to result in similar levels of image noise. Computed tomography colonography images acquired using the IC detector had significantly lower noise than images acquired using the conventional detector. This noise reduction can permit further radiation dose reduction in CTC.

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.

An atlas of the (near) future: cognitive computing applications for medical imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

LeGrand, Anne

2017-02-01

The role of medical imaging in global health systems is literally fundamental. Like labs, medical images are used at one point or another in almost every high cost, high value episode of care. CT scans, mammograms, and x-rays, for example, "atlas" the body and help chart a course forward for a patient's care team. Imaging precision has improved as a result of technological advancements and breakthroughs in related medical research. Those advancements also bring with them exponential growth in medical imaging data. As IBM trains Watson to "see" medical images, Ms. Le Grand will discuss recent advances made by Watson Health and explore the potential value of "augmented intelligence" to assist healthcare providers like radiologists and cardiologists, as well as the patients they serve.

Artifact Reduction in X-Ray CT Images of Al-Steel-Perspex Specimens Mimicking a Hip Prosthesis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Madhogarhia, Manish; Munshi, P.; Lukose, Sijo

2008-09-26

X-ray Computed Tomography (CT) is a relatively new technique developed in the late 1970's, which enables the nondestructive visualization of the internal structure of objects. Beam hardening caused by the polychromatic spectrum is an important problem in X-ray computed tomography (X-CT). It leads to various artifacts in reconstruction images and reduces image quality. In the present work we are considering the Artifact Reduction in Total Hip Prosthesis CT Scan which is a problem of medical imaging. We are trying to reduce the cupping artifact induced by beam hardening as well as metal artifact as they exist in the CT scanmore » of a human hip after the femur is replaced by a metal implant. The correction method for beam hardening used here is based on a previous work. Simulation study for the present problem includes a phantom consisting of mild steel, aluminium and perspex mimicking the photon attenuation properties of a hum hip cross section with metal implant.« less

ImageParser: a tool for finite element generation from three-dimensional medical images

PubMed Central

Yin, HM; Sun, LZ; Wang, G; Yamada, T; Wang, J; Vannier, MW

2004-01-01

Background The finite element method (FEM) is a powerful mathematical tool to simulate and visualize the mechanical deformation of tissues and organs during medical examinations or interventions. It is yet a challenge to build up an FEM mesh directly from a volumetric image partially because the regions (or structures) of interest (ROIs) may be irregular and fuzzy. Methods A software package, ImageParser, is developed to generate an FEM mesh from 3-D tomographic medical images. This software uses a semi-automatic method to detect ROIs from the context of image including neighboring tissues and organs, completes segmentation of different tissues, and meshes the organ into elements. Results The ImageParser is shown to build up an FEM model for simulating the mechanical responses of the breast based on 3-D CT images. The breast is compressed by two plate paddles under an overall displacement as large as 20% of the initial distance between the paddles. The strain and tangential Young's modulus distributions are specified for the biomechanical analysis of breast tissues. Conclusion The ImageParser can successfully exact the geometry of ROIs from a complex medical image and generate the FEM mesh with customer-defined segmentation information. PMID:15461787

CT Dose Optimization in Pediatric Radiology: A Multiyear Effort to Preserve the Benefits of Imaging While Reducing the Risks.

PubMed

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.

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.

PET/CT image registration: preliminary tests for its application to clinical dosimetry in radiotherapy.

PubMed

Baños-Capilla, M C; García, M A; Bea, J; Pla, C; Larrea, L; López, E

2007-06-01

The quality of dosimetry in radiotherapy treatment requires the accurate delimitation of the gross tumor volume. This can be achieved by complementing the anatomical detail provided by CT images through fusion with other imaging modalities that provide additional metabolic and physiological information. Therefore, use of multiple imaging modalities for radiotherapy treatment planning requires an accurate image registration method. This work describes tests carried out on a Discovery LS positron emission/computed tomography (PET/CT) system by General Electric Medical Systems (GEMS), for its later use to obtain images to delimit the target in radiotherapy treatment. Several phantoms have been used to verify image correlation, in combination with fiducial markers, which were used as a system of external landmarks. We analyzed the geometrical accuracy of two different fusion methods with the images obtained with these phantoms. We first studied the fusion method used by the PET/CT system by GEMS (hardware fusion) on the basis that there is satisfactory coincidence between the reconstruction centers in CT and PET systems; and secondly the fiducial fusion, a registration method, by means of least-squares fitting algorithm of a landmark points system. The study concluded with the verification of the centroid position of some phantom components in both imaging modalities. Centroids were estimated through a calculation similar to center-of-mass, weighted by the value of the CT number and the uptake intensity in PET. The mean deviations found for the hardware fusion method were: deltax/ +/-sigma = 3.3 mm +/- 1.0 mm and /deltax/ +/-sigma = 3.6 mm +/- 1.0 mm. These values were substantially improved upon applying fiducial fusion based on external landmark points: /deltax/ +/-sigma = 0.7 mm +/- 0.8 mm and /deltax/ +/-sigma = 0.3 mm 1.7 mm. We also noted that differences found for each of the fusion methods were similar for both the axial and helical CT image acquisition

Combined use of iterative reconstruction and monochromatic imaging in spinal fusion CT images.

PubMed

Wang, Fengdan; Zhang, Yan; Xue, Huadan; Han, Wei; Yang, Xianda; Jin, Zhengyu; Zwar, Richard

2017-01-01

Spinal fusion surgery is an important procedure for treating spinal diseases and computed tomography (CT) is a critical tool for postoperative evaluation. However, CT image quality is considerably impaired by metal artifacts and image noise. To explore whether metal artifacts and image noise can be reduced by combining two technologies, adaptive statistical iterative reconstruction (ASIR) and monochromatic imaging generated by gemstone spectral imaging (GSI) dual-energy CT. A total of 51 patients with 318 spinal pedicle screws were prospectively scanned by dual-energy CT using fast kV-switching GSI between 80 and 140 kVp. Monochromatic GSI images at 110 keV were reconstructed either without or with various levels of ASIR (30%, 50%, 70%, and 100%). The quality of five sets of images was objectively and subjectively assessed. With objective image quality assessment, metal artifacts decreased when increasing levels of ASIR were applied (P < 0.001). Moreover, adding ASIR to GSI also decreased image noise (P < 0.001) and improved the signal-to-noise ratio (P < 0.001). The subjective image quality analysis showed good inter-reader concordance, with intra-class correlation coefficients between 0.89 and 0.99. The visualization of peri-implant soft tissue was improved at higher ASIR levels (P < 0.001). Combined use of ASIR and GSI decreased image noise and improved image quality in post-spinal fusion CT scans. Optimal results were achieved with ASIR levels ≥70%. © The Foundation Acta Radiologica 2016.

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.

Evaluation of image registration in PET/CT of the liver and recommendations for optimized imaging.

PubMed

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

MO-DE-207A-09: Low-Dose CT Image Reconstruction Via Learning From Different Patient Normal-Dose Images

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

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.

Adaptive iterative dose reduction (AIDR) 3D in low dose CT abdomen-pelvis: Effects on image quality and radiation exposure

NASA Astrophysics Data System (ADS)

Ang, W. C.; Hashim, S.; Karim, M. K. A.; Bahruddin, N. A.; Salehhon, N.; Musa, Y.

2017-05-01

The widespread use of computed tomography (CT) has increased the medical radiation exposure and cancer risk. We aimed to evaluate the impact of AIDR 3D in CT abdomen-pelvic examinations based on image quality and radiation dose in low dose (LD) setting compared to standard dose (STD) with filtered back projection (FBP) reconstruction. We retrospectively reviewed the images of 40 patients who underwent CT abdomen-pelvic using a 80 slice CT scanner. Group 1 patients (n=20, mean age 41 ± 17 years) were performed at LD with AIDR 3D reconstruction and Group 2 patients (n=20, mean age 52 ± 21 years) were scanned with STD using FBP reconstruction. Objective image noise was assessed by region of interest (ROI) measurements in the liver and aorta as standard deviation (SD) of the attenuation value (Hounsfield Unit, HU) while subjective image quality was evaluated by two radiologists. Statistical analysis was used to compare the scan length, CT dose index volume (CTDIvol) and image quality of both patient groups. Although both groups have similar mean scan length, the CTDIvol significantly decreased by 38% in LD CT compared to STD CT (p<0.05). Objective and subjective image quality were statistically improved with AIDR 3D (p<0.05). In conclusion, AIDR 3D enables significant dose reduction of 38% with superior image quality in LD CT abdomen-pelvis.

CT image segmentation methods for bone used in medical additive manufacturing.

PubMed

van Eijnatten, Maureen; van Dijk, Roelof; Dobbe, Johannes; Streekstra, Geert; Koivisto, Juha; Wolff, Jan

2018-01-01

The accuracy of additive manufactured medical constructs is limited by errors introduced during image segmentation. The aim of this study was to review the existing literature on different image segmentation methods used in medical additive manufacturing. Thirty-two publications that reported on the accuracy of bone segmentation based on computed tomography images were identified using PubMed, ScienceDirect, Scopus, and Google Scholar. The advantages and disadvantages of the different segmentation methods used in these studies were evaluated and reported accuracies were compared. The spread between the reported accuracies was large (0.04 mm - 1.9 mm). Global thresholding was the most commonly used segmentation method with accuracies under 0.6 mm. The disadvantage of this method is the extensive manual post-processing required. Advanced thresholding methods could improve the accuracy to under 0.38 mm. However, such methods are currently not included in commercial software packages. Statistical shape model methods resulted in accuracies from 0.25 mm to 1.9 mm but are only suitable for anatomical structures with moderate anatomical variations. Thresholding remains the most widely used segmentation method in medical additive manufacturing. To improve the accuracy and reduce the costs of patient-specific additive manufactured constructs, more advanced segmentation methods are required. Copyright © 2017 IPEM. Published by Elsevier Ltd. All rights reserved.

Deploying swarm intelligence in medical imaging identifying metastasis, micro-calcifications and brain image segmentation.

PubMed

al-Rifaie, Mohammad Majid; Aber, Ahmed; Hemanth, Duraiswamy Jude

2015-12-01

This study proposes an umbrella deployment of swarm intelligence algorithm, such as stochastic diffusion search for medical imaging applications. After summarising the results of some previous works which shows how the algorithm assists in the identification of metastasis in bone scans and microcalcifications on mammographs, for the first time, the use of the algorithm in assessing the CT images of the aorta is demonstrated along with its performance in detecting the nasogastric tube in chest X-ray. The swarm intelligence algorithm presented in this study is adapted to address these particular tasks and its functionality is investigated by running the swarms on sample CT images and X-rays whose status have been determined by senior radiologists. In addition, a hybrid swarm intelligence-learning vector quantisation (LVQ) approach is proposed in the context of magnetic resonance (MR) brain image segmentation. The particle swarm optimisation is used to train the LVQ which eliminates the iteration-dependent nature of LVQ. The proposed methodology is used to detect the tumour regions in the abnormal MR brain images.

New and emerging patient-centered CT imaging and image-guided treatment paradigms for maxillofacial trauma.

PubMed

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.

Study of CT image texture using deep learning techniques

NASA Astrophysics Data System (ADS)

Dutta, Sandeep; Fan, Jiahua; Chevalier, David

2018-03-01

For CT imaging, reduction of radiation dose while improving or maintaining image quality (IQ) is currently a very active research and development topic. Iterative Reconstruction (IR) approaches have been suggested to be able to offer better IQ to dose ratio compared to the conventional Filtered Back Projection (FBP) reconstruction. However, it has been widely reported that often CT image texture from IR is different compared to that from FBP. Researchers have proposed different figure of metrics to quantitate the texture from different reconstruction methods. But there is still a lack of practical and robust method in the field for texture description. This work applied deep learning method for CT image texture study. Multiple dose scans of a 20cm diameter cylindrical water phantom was performed on Revolution CT scanner (GE Healthcare, Waukesha) and the images were reconstructed with FBP and four different IR reconstruction settings. The training images generated were randomly allotted (80:20) to a training and validation set. An independent test set of 256-512 images/class were collected with the same scan and reconstruction settings. Multiple deep learning (DL) networks with Convolution, RELU activation, max-pooling, fully-connected, global average pooling and softmax activation layers were investigated. Impact of different image patch size for training was investigated. Original pixel data as well as normalized image data were evaluated. DL models were reliably able to classify CT image texture with accuracy up to 99%. Results show that the deep learning techniques suggest that CT IR techniques may help lower the radiation dose compared to FBP.

SU-F-J-214: Dose Reduction by Spatially Optimized Image Quality Via Fluence Modulated Proton CT (FMpCT)

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

TLD assessment of mouse dosimetry during microCT imaging

PubMed Central

Figueroa, Said Daibes; Winkelmann, Christopher T.; Miller, William H.; Volkert, Wynn A.; Hoffman, Timothy J.

2008-01-01

Advances in laboratory animal imaging have provided new resources for noninvasive biomedical research. Among these technologies is microcomputed tomography (microCT) which is widely used to obtain high resolution anatomic images of small animals. Because microCT utilizes ionizing radiation for image formation, radiation exposure during imaging is a concern. The objective of this study was to quantify the radiation dose delivered during a standard microCT scan. Radiation dose was measured using thermoluminescent dosimeters (TLDs), which were irradiated employing an 80 kVp x-ray source, with 0.5 mm Al filtration and a total of 54 mA s for a full 360 deg rotation of the unit. The TLD data were validated using a 3.2 cm3 CT ion chamber probe. TLD results showed a single microCT scan air kerma of 78.0±5.0 mGy when using a poly(methylmethacrylate) (PMMA) anesthesia support module and an air kerma of 92.0±6.0 mGy without the use of the anesthesia module. The validation CT ion chamber study provided a measured radiation air kerma of 81.0±4.0 mGy and 97.0±5.0 mGy with and without the PMMA anesthesia module, respectively. Internal TLD analysis demonstrated an average mouse organ radiation absorbed dose of 76.0±5.0 mGy. The author’s results have defined x-ray exposure for a routine microCT study which must be taken into consideration when performing serial molecular imaging studies involving the microCT imaging modality. PMID:18841837

Automatic lumbar spine measurement in CT images

NASA Astrophysics Data System (ADS)

Mao, Yunxiang; Zheng, Dong; Liao, Shu; Peng, Zhigang; Yan, Ruyi; Liu, Junhua; Dong, Zhongxing; Gong, Liyan; Zhou, Xiang Sean; Zhan, Yiqiang; Fei, Jun

2017-03-01

Accurate lumbar spine measurement in CT images provides an essential way for quantitative spinal diseases analysis such as spondylolisthesis and scoliosis. In today's clinical workflow, the measurements are manually performed by radiologists and surgeons, which is time consuming and irreproducible. Therefore, automatic and accurate lumbar spine measurement algorithm becomes highly desirable. In this study, we propose a method to automatically calculate five different lumbar spine measurements in CT images. There are three main stages of the proposed method: First, a learning based spine labeling method, which integrates both the image appearance and spine geometry information, is used to detect lumbar and sacrum vertebrae in CT images. Then, a multiatlases based image segmentation method is used to segment each lumbar vertebra and the sacrum based on the detection result. Finally, measurements are derived from the segmentation result of each vertebra. Our method has been evaluated on 138 spinal CT scans to automatically calculate five widely used clinical spine measurements. Experimental results show that our method can achieve more than 90% success rates across all the measurements. Our method also significantly improves the measurement efficiency compared to manual measurements. Besides benefiting the routine clinical diagnosis of spinal diseases, our method also enables the large scale data analytics for scientific and clinical researches.

Image-guided tissue engineering of anatomically shaped implants via MRI and micro-CT using injection molding.

PubMed

Ballyns, Jeffery J; Gleghorn, Jason P; Niebrzydowski, Vicki; Rawlinson, Jeremy J; Potter, Hollis G; Maher, Suzanne A; Wright, Timothy M; Bonassar, Lawrence J

2008-07-01

This study demonstrates for the first time the development of engineered tissues based on anatomic geometries derived from widely used medical imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI). Computer-aided design and tissue injection molding techniques have demonstrated the ability to generate living implants of complex geometry. Due to its complex geometry, the meniscus of the knee was used as an example of this technique's capabilities. MRI and microcomputed tomography (microCT) were used to design custom-printed molds that enabled the generation of anatomically shaped constructs that retained shape throughout 8 weeks of culture. Engineered constructs showed progressive tissue formation indicated by increases in extracellular matrix content and mechanical properties. The paradigm of interfacing tissue injection molding technology can be applied to other medical imaging techniques that render 3D models of anatomy, demonstrating the potential to apply the current technique to engineering of many tissues and organs.

Successful patient recruitment in CT imaging clinical trials: what factors influence patient participation?

PubMed

Hollada, Jacqueline; Marfori, Wanda; Tognolini, Alessia; Speier, William; Ristow, Lindsey; Ruehm, Stefan G

2014-01-01

Analyze factors that influence participation in research studies that use coronary computed tomography (CT) imaging. A 12-point survey using a questionnaire was conducted on 80 subjects, of whom 40 agreed to participate in a cardiovascular CT imaging research study (enrolling subjects) and 40 declined participation (non-enrolling subjects). Potential factors that motivated the acceptance or refusal of enrollment were evaluated using a 5-point Likert scale. The following aspects were addressed: (1) additional health information, (2) free imaging, (3) altruistic benefit to society, (4) monetary compensation, (5) radiation exposure, (6) role as an experimental subject, (7) possible loss of confidentiality, (8) contrast or investigational drug use, (9) premedication use, (10) blood draw or intravenous placement, (11) time commitment, and (12) personal medical opinion. Response distributions were obtained for each question and compared between enrolling and non-enrolling groups. Enrolling subjects gave significantly higher ratings than non-enrolling subjects for the following factors: additional health information (P < .001), free imaging (P < .001), and the altruistic benefit to society (P < .001). For non-enrolling subjects, concern for possible drug use or contrast injection (P < .001), concern for possible premedication (P < .001), and personal availability or time commitment (P < .001) were all given significantly higher ratings. Concern for radiation exposure (P = .002) and personal medical opinion (P < .001) received significantly high ratings among both groups but did not differ between groups. Several influential concerns and benefits were identified from potential research subjects. Knowledge of what influences patient participation in studies involving CT imaging may allow researchers to effectively address concerns and highlight the potential benefits related to participation. Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Adaptively Tuned Iterative Low Dose CT Image Denoising

PubMed Central

Hashemi, SayedMasoud; Paul, Narinder S.; Beheshti, Soosan; Cobbold, Richard S. C.

2015-01-01

Improving image quality is a critical objective in low dose computed tomography (CT) imaging and is the primary focus of CT image denoising. State-of-the-art CT denoising algorithms are mainly based on iterative minimization of an objective function, in which the performance is controlled by regularization parameters. To achieve the best results, these should be chosen carefully. However, the parameter selection is typically performed in an ad hoc manner, which can cause the algorithms to converge slowly or become trapped in a local minimum. To overcome these issues a noise confidence region evaluation (NCRE) method is used, which evaluates the denoising residuals iteratively and compares their statistics with those produced by additive noise. It then updates the parameters at the end of each iteration to achieve a better match to the noise statistics. By combining NCRE with the fundamentals of block matching and 3D filtering (BM3D) approach, a new iterative CT image denoising method is proposed. It is shown that this new denoising method improves the BM3D performance in terms of both the mean square error and a structural similarity index. Moreover, simulations and patient results show that this method preserves the clinically important details of low dose CT images together with a substantial noise reduction. PMID:26089972

[Design of visualized medical images network and web platform based on MeVisLab].

PubMed

Xiang, Jun; Ye, Qing; Yuan, Xun

2017-04-01

With the trend of the development of "Internet +", some further requirements for the mobility of medical images have been required in the medical field. In view of this demand, this paper presents a web-based visual medical imaging platform. First, the feasibility of medical imaging is analyzed and technical points. CT (Computed Tomography) or MRI (Magnetic Resonance Imaging) images are reconstructed three-dimensionally by MeVisLab and packaged as X3D (Extensible 3D Graphics) files shown in the present paper. Then, the B/S (Browser/Server) system specially designed for 3D image is designed by using the HTML 5 and WebGL rendering engine library, and the X3D image file is parsed and rendered by the system. The results of this study showed that the platform was suitable for multiple operating systems to realize the platform-crossing and mobilization of medical image data. The development of medical imaging platform is also pointed out in this paper. It notes that web application technology will not only promote the sharing of medical image data, but also facilitate image-based medical remote consultations and distance learning.

Image analysis of pulmonary nodules using micro CT

NASA Astrophysics Data System (ADS)

Niki, Noboru; Kawata, Yoshiki; Fujii, Masashi; Kakinuma, Ryutaro; Moriyama, Noriyuki; Tateno, Yukio; Matsui, Eisuke

2001-07-01

We are developing a micro-computed tomography (micro CT) system for imaging pulmonary nodules. The purpose is to enhance the physician performance in accessing the micro- architecture of the nodule for classification between malignant and benign nodules. The basic components of the micro CT system consist of microfocus X-ray source, a specimen manipulator, and an image intensifier detector coupled to charge-coupled device (CCD) camera. 3D image reconstruction was performed by the slice. A standard fan- beam convolution and backprojection algorithm was used to reconstruct the center plane intersecting the X-ray source. The preprocessing of the 3D image reconstruction included the correction of the geometrical distortions and the shading artifact introduced by the image intensifier. The main advantage of the system is to obtain a high spatial resolution which ranges between b micrometers and 25 micrometers . In this work we report on preliminary studies performed with the micro CT for imaging resected tissues of normal and abnormal lung. Experimental results reveal micro architecture of lung tissues, such as alveolar wall, septal wall of pulmonary lobule, and bronchiole. From the results, the micro CT system is expected to have interesting potentials for high confidential differential diagnosis.

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.

Optimising μCT imaging of the middle and inner cat ear.

PubMed

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.

Combined endeavor of Neutrosophic Set and Chan-Vese model to extract accurate liver image from CT scan.

PubMed

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.

Adaptive tight frame based medical image reconstruction: a proof-of-concept study for computed tomography

NASA Astrophysics Data System (ADS)

Zhou, Weifeng; Cai, Jian-Feng; Gao, Hao

2013-12-01

A popular approach for medical image reconstruction has been through the sparsity regularization, assuming the targeted image can be well approximated by sparse coefficients under some properly designed system. The wavelet tight frame is such a widely used system due to its capability for sparsely approximating piecewise-smooth functions, such as medical images. However, using a fixed system may not always be optimal for reconstructing a variety of diversified images. Recently, the method based on the adaptive over-complete dictionary that is specific to structures of the targeted images has demonstrated its superiority for image processing. This work is to develop the adaptive wavelet tight frame method image reconstruction. The proposed scheme first constructs the adaptive wavelet tight frame that is task specific, and then reconstructs the image of interest by solving an l1-regularized minimization problem using the constructed adaptive tight frame system. The proof-of-concept study is performed for computed tomography (CT), and the simulation results suggest that the adaptive tight frame method improves the reconstructed CT image quality from the traditional tight frame method.

PET/CT (and CT) instrumentation, image reconstruction and data transfer for radiotherapy planning.

PubMed

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

A framework for optimizing micro-CT in dual-modality micro-CT/XFCT small-animal imaging system

NASA Astrophysics Data System (ADS)

Vedantham, Srinivasan; Shrestha, Suman; Karellas, Andrew; Cho, Sang Hyun

2017-09-01

Dual-modality Computed Tomography (CT)/X-ray Fluorescence Computed Tomography (XFCT) can be a valuable tool for imaging and quantifying the organ and tissue distribution of small concentrations of high atomic number materials in small-animal system. In this work, the framework for optimizing the micro-CT imaging system component of the dual-modality system is described, either when the micro-CT images are concurrently acquired with XFCT and using the x-ray spectral conditions for XFCT, or when the micro-CT images are acquired sequentially and independently of XFCT. This framework utilizes the cascaded systems analysis for task-specific determination of the detectability index using numerical observer models at a given radiation dose, where the radiation dose is determined using Monte Carlo simulations.

A Hybrid Method for Pancreas Extraction from CT Image Based on Level Set Methods

PubMed Central

Tan, Hanqing; Fujita, Hiroshi

2013-01-01

This paper proposes a novel semiautomatic method to extract the pancreas from abdominal CT images. Traditional level set and region growing methods that request locating initial contour near the final boundary of object have problem of leakage to nearby tissues of pancreas region. The proposed method consists of a customized fast-marching level set method which generates an optimal initial pancreas region to solve the problem that the level set method is sensitive to the initial contour location and a modified distance regularized level set method which extracts accurate pancreas. The novelty in our method is the proper selection and combination of level set methods, furthermore an energy-decrement algorithm and an energy-tune algorithm are proposed to reduce the negative impact of bonding force caused by connected tissue whose intensity is similar with pancreas. As a result, our method overcomes the shortages of oversegmentation at weak boundary and can accurately extract pancreas from CT images. The proposed method is compared to other five state-of-the-art medical image segmentation methods based on a CT image dataset which contains abdominal images from 10 patients. The evaluated results demonstrate that our method outperforms other methods by achieving higher accuracy and making less false segmentation in pancreas extraction. PMID:24066016

Multi-technique hybrid imaging in PET/CT and PET/MR: what does the future hold?

PubMed

de Galiza Barbosa, F; Delso, G; Ter Voert, E E G W; Huellner, M W; Herrmann, K; Veit-Haibach, P

2016-07-01

Integrated positron-emission tomography and computed tomography (PET/CT) is one of the most important imaging techniques to have emerged in oncological practice in the last decade. Hybrid imaging, in general, remains a rapidly growing field, not only in developing countries, but also in western industrialised healthcare systems. A great deal of technological development and research is focused on improving hybrid imaging technology further and introducing new techniques, e.g., integrated PET and magnetic resonance imaging (PET/MRI). Additionally, there are several new PET tracers on the horizon, which have the potential to broaden clinical applications in hybrid imaging for diagnosis as well as therapy. This article aims to highlight some of the major technical and clinical advances that are currently taking place in PET/CT and PET/MRI that will potentially maintain the position of hybrid techniques at the forefront of medical imaging technologies. Copyright © 2016 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Hybrid SPECT/CT imaging in neurology.

PubMed

Ciarmiello, Andrea; Giovannini, Elisabetta; Meniconi, Martina; Cuccurullo, Vincenzo; Gaeta, Maria Chiara

2014-01-01

In recent years, the SPECT/CT hybrid modality has led to a rapid development of imaging techniques in nuclear medicine, opening new perspectives for imaging staff and patients as well. However, while, the clinical role of positron emission tomography-computed tomography (PET-CT) is well consolidated, the diffusion and the consequent value of single-photon emission tomography-computed tomography (SPECT-CT) has yet to be weighed, Hence, there is a need for a careful analysis, comparing the "potential" benefits of the hybrid modality with the "established" ones of the standalone machine. The aim of this article is to analyze the impact of this hybrid tool on the diagnosis of diseases of the central nervous system, comparing strengths and weaknesses of both modalities through the use of SWOT analysis.

Three modality image registration of brain SPECT/CT and MR images for quantitative analysis of dopamine transporter imaging

NASA Astrophysics Data System (ADS)

Yamaguchi, Yuzuho; Takeda, Yuta; Hara, Takeshi; Zhou, Xiangrong; Matsusako, Masaki; Tanaka, Yuki; Hosoya, Kazuhiko; Nihei, Tsutomu; Katafuchi, Tetsuro; Fujita, Hiroshi

2016-03-01

Important features in Parkinson's disease (PD) are degenerations and losses of dopamine neurons in corpus striatum. 123I-FP-CIT can visualize activities of the dopamine neurons. The activity radio of background to corpus striatum is used for diagnosis of PD and Dementia with Lewy Bodies (DLB). The specific activity can be observed in the corpus striatum on SPECT images, but the location and the shape of the corpus striatum on SPECT images only are often lost because of the low uptake. In contrast, MR images can visualize the locations of the corpus striatum. The purpose of this study was to realize a quantitative image analysis for the SPECT images by using image registration technique with brain MR images that can determine the region of corpus striatum. In this study, the image fusion technique was used to fuse SPECT and MR images by intervening CT image taken by SPECT/CT. The mutual information (MI) for image registration between CT and MR images was used for the registration. Six SPECT/CT and four MR scans of phantom materials are taken by changing the direction. As the results of the image registrations, 16 of 24 combinations were registered within 1.3mm. By applying the approach to 32 clinical SPECT/CT and MR cases, all of the cases were registered within 0.86mm. In conclusions, our registration method has a potential in superimposing MR images on SPECT images.

CT Image Sequence Restoration Based on Sparse and Low-Rank Decomposition

PubMed Central

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

Dual scan CT image recovery from truncated projections

NASA Astrophysics Data System (ADS)

Sarkar, Shubhabrata; Wahi, Pankaj; Munshi, Prabhat

2017-12-01

There are computerized tomography (CT) scanners available commercially for imaging small objects and they are often categorized as mini-CT X-ray machines. One major limitation of these machines is their inability to scan large objects with good image quality because of the truncation of projection data. An algorithm is proposed in this work which enables such machines to scan large objects while maintaining the quality of the recovered image.

Medical Image Compression Using a New Subband Coding Method

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Smith, Mark J. T.; Scales, Allen; Tucker, Doug

1995-01-01

A recently introduced iterative complexity- and entropy-constrained subband quantization design algorithm is generalized and applied to medical image compression. In particular, the corresponding subband coder is used to encode Computed Tomography (CT) axial slice head images, where statistical dependencies between neighboring image subbands are exploited. Inter-slice conditioning is also employed for further improvements in compression performance. The subband coder features many advantages such as relatively low complexity and operation over a very wide range of bit rates. Experimental results demonstrate that the performance of the new subband coder is relatively good, both objectively and subjectively.

Open-source software platform for medical image segmentation applications

NASA Astrophysics Data System (ADS)

Namías, R.; D'Amato, J. P.; del Fresno, M.

2017-11-01

Segmenting 2D and 3D images is a crucial and challenging problem in medical image analysis. Although several image segmentation algorithms have been proposed for different applications, no universal method currently exists. Moreover, their use is usually limited when detection of complex and multiple adjacent objects of interest is needed. In addition, the continually increasing volumes of medical imaging scans require more efficient segmentation software design and highly usable applications. In this context, we present an extension of our previous segmentation framework which allows the combination of existing explicit deformable models in an efficient and transparent way, handling simultaneously different segmentation strategies and interacting with a graphic user interface (GUI). We present the object-oriented design and the general architecture which consist of two layers: the GUI at the top layer, and the processing core filters at the bottom layer. We apply the framework for segmenting different real-case medical image scenarios on public available datasets including bladder and prostate segmentation from 2D MRI, and heart segmentation in 3D CT. Our experiments on these concrete problems show that this framework facilitates complex and multi-object segmentation goals while providing a fast prototyping open-source segmentation tool.

Cone-Beam CT with a Flat-Panel Detector: From Image Science to Image-Guided Surgery

PubMed Central

Siewerdsen, Jeffrey H.

2011-01-01

The development of large-area flat-panel x-ray detectors (FPDs) has spurred investigation in a spectrum of advanced medical imaging applications, including tomosynthesis and cone-beam CT (CBCT). Recent research has extended image quality metrics and theoretical models to such applications, providing a quantitative foundation for the assessment of imaging performance as well as a general framework for the design, optimization, and translation of such technologies to new applications. For example, cascaded systems models of Fourier domain metrics, such as noise-equivalent quanta (NEQ), have been extended to these modalities to describe the propagation of signal and noise through the image acquisition and reconstruction chain and to quantify the factors that govern spatial resolution, image noise, and detectability. Moreover, such models have demonstrated basic agreement with human observer performance for a broad range of imaging conditions and imaging tasks. These developments in image science have formed a foundation for the knowledgeable development and translation of CBCT to new applications in image-guided interventions - for example, CBCT implemented on a mobile surgical C-arm for intraoperative 3D imaging. The ability to acquire high-quality 3D images on demand during surgical intervention overcomes conventional limitations of surgical guidance in the context of preoperative images alone. A prototype mobile C-arm developed in academic-industry partnership demonstrates CBCT with low radiation dose, sub-mm spatial resolution, and soft-tissue visibility potentially approaching that of diagnostic CT. Integration of the 3D imaging system with real-time tracking, deformable registration, endoscopic video, and 3D visualization offers a promising addition to the surgical arsenal in interventions ranging from head-and-neck / skull base surgery to spine, orthopaedic, thoracic, and abdominal surgeries. Cadaver studies show the potential for significant boosts in surgical

Lung cancer mimicking lung abscess formation on CT images.

PubMed

Taira, Naohiro; Kawabata, Tsutomu; Gabe, Atsushi; Ichi, Takaharu; Kushi, Kazuaki; Yohena, Tomofumi; Kawasaki, Hidenori; Yamashiro, Toshimitsu; Ishikawa, Kiyoshi

2014-01-01

Male, 64 FINAL DIAGNOSIS: Lung pleomorphic carcinoma Symptoms: Cough • fever - Clinical Procedure: - Specialty: Oncology. Unusual clinical course. The diagnosis of lung cancer is often made based on computed tomography (CT) image findings if it cannot be confirmed on pathological examinations, such as bronchoscopy. However, the CT image findings of cancerous lesions are similar to those of abscesses.We herein report a case of lung cancer that resembled a lung abscess on CT. We herein describe the case of 64-year-old male who was diagnosed with lung cancer using surgery. In this case, it was quite difficult to distinguish between the lung cancer and a lung abscess on CT images, and a lung abscess was initially suspected due to symptoms, such as fever and coughing, contrast-enhanced CT image findings showing a ring-enhancing mass in the right upper lobe and the patient's laboratory test results. However, a pathological diagnosis of lung cancer was confirmed according to the results of a rapid frozen section biopsy of the lesion. This case suggests that physicians should not suspect both a lung abscesses and malignancy in cases involving masses presenting as ring-enhancing lesions on contrast-enhanced CT.

Denoising of polychromatic CT images based on their own noise properties

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Ji Hye; Chang, Yongjin; Ra, Jong Beom, E-mail: jbra@kaist.ac.kr

Purpose: Because of high diagnostic accuracy and fast scan time, computed tomography (CT) has been widely used in various clinical applications. Since the CT scan introduces radiation exposure to patients, however, dose reduction has recently been recognized as an important issue in CT imaging. However, low-dose CT causes an increase of noise in the image and thereby deteriorates the accuracy of diagnosis. In this paper, the authors develop an efficient denoising algorithm for low-dose CT images obtained using a polychromatic x-ray source. The algorithm is based on two steps: (i) estimation of space variant noise statistics, which are uniquely determinedmore » according to the system geometry and scanned object, and (ii) subsequent novel conversion of the estimated noise to Gaussian noise so that an existing high performance Gaussian noise filtering algorithm can be directly applied to CT images with non-Gaussian noise. Methods: For efficient polychromatic CT image denoising, the authors first reconstruct an image with the iterative maximum-likelihood polychromatic algorithm for CT to alleviate the beam-hardening problem. We then estimate the space-variant noise variance distribution on the image domain. Since there are many high performance denoising algorithms available for the Gaussian noise, image denoising can become much more efficient if they can be used. Hence, the authors propose a novel conversion scheme to transform the estimated space-variant noise to near Gaussian noise. In the suggested scheme, the authors first convert the image so that its mean and variance can have a linear relationship, and then produce a Gaussian image via variance stabilizing transform. The authors then apply a block matching 4D algorithm that is optimized for noise reduction of the Gaussian image, and reconvert the result to obtain a final denoised image. To examine the performance of the proposed method, an XCAT phantom simulation and a physical phantom experiment were

Safety Precautions and Operating Procedures in an (A)BSL-4 Laboratory: 4. Medical Imaging Procedures.

PubMed

Byrum, Russell; Keith, Lauren; Bartos, Christopher; St Claire, Marisa; Lackemeyer, Matthew G; Holbrook, Michael R; Janosko, Krisztina; Barr, Jason; Pusl, Daniela; Bollinger, Laura; Wada, Jiro; Coe, Linda; Hensley, Lisa E; Jahrling, Peter B; Kuhn, Jens H; Lentz, Margaret R

2016-10-03

Medical imaging using animal models for human diseases has been utilized for decades; however, until recently, medical imaging of diseases induced by high-consequence pathogens has not been possible. In 2014, the National Institutes of Health, National Institute of Allergy and Infectious Diseases, Integrated Research Facility at Fort Detrick opened an Animal Biosafety Level 4 (ABSL-4) facility to assess the clinical course and pathology of infectious diseases in experimentally infected animals. Multiple imaging modalities including computed tomography (CT), magnetic resonance imaging, positron emission tomography, and single photon emission computed tomography are available to researchers for these evaluations. The focus of this article is to describe the workflow for safely obtaining a CT image of a live guinea pig in an ABSL-4 facility. These procedures include animal handling, anesthesia, and preparing and monitoring the animal until recovery from sedation. We will also discuss preparing the imaging equipment, performing quality checks, communication methods from "hot side" (containing pathogens) to "cold side," and moving the animal from the holding room to the imaging suite.

Evaluation of an attenuation correction method for PET/MR imaging of the head based on substitute CT images.

PubMed

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.

Prostate seed implant quality assessment using MR and CT image fusion.

PubMed

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).

Flat-panel cone-beam CT: a novel imaging technology for image-guided procedures

NASA Astrophysics Data System (ADS)

Siewerdsen, Jeffrey H.; Jaffray, David A.; Edmundson, Gregory K.; Sanders, W. P.; Wong, John W.; Martinez, Alvaro A.

2001-05-01

The use of flat-panel imagers for cone-beam CT signals the emergence of an attractive technology for volumetric imaging. Recent investigations demonstrate volume images with high spatial resolution and soft-tissue visibility and point to a number of logistical characteristics (e.g., open geometry, volume acquisition in a single rotation about the patient, and separation of the imaging and patient support structures) that are attractive to a broad spectrum of applications. Considering application to image-guided (IG) procedures - specifically IG therapies - this paper examines the performance of flat-panel cone-beam CT in relation to numerous constraints and requirements, including time (i.e., speed of image acquisition), dose, and field-of-view. The imaging and guidance performance of a prototype flat panel cone-beam CT system is investigated through the construction of procedure-specific tasks that test the influence of image artifacts (e.g., x-ray scatter and beam-hardening) and volumetric imaging performance (e.g., 3D spatial resolution, noise, and contrast) - taking two specific examples in IG brachytherapy and IG vertebroplasty. For IG brachytherapy, a procedure-specific task is constructed which tests the performance of flat-panel cone-beam CT in measuring the volumetric distribution of Pd-103 permanent implant seeds in relation to neighboring bone and soft-tissue structures in a pelvis phantom. For IG interventional procedures, a procedure-specific task is constructed in the context of vertebroplasty performed on a cadaverized ovine spine, demonstrating the volumetric image quality in pre-, intra-, and post-therapeutic images of the region of interest and testing the performance of the system in measuring the volumetric distribution of bone cement (PMMA) relative to surrounding spinal anatomy. Each of these tasks highlights numerous promising and challenging aspects of flat-panel cone-beam CT applied to IG procedures.

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

Dedicated Cone-Beam CT System for Extremity Imaging

PubMed Central

Al Muhit, Abdullah; Zbijewski, Wojciech; Thawait, Gaurav K.; Stayman, J. Webster; Packard, Nathan; Senn, Robert; Yang, Dong; Foos, David H.; Yorkston, John; Siewerdsen, Jeffrey H.

2014-01-01

Purpose To provide initial assessment of image quality and dose for a cone-beam computed tomographic (CT) scanner dedicated to extremity imaging. Materials and Methods A prototype cone-beam CT scanner has been developed for imaging the extremities, including the weight-bearing lower extremities. Initial technical assessment included evaluation of radiation dose measured as a function of kilovolt peak and tube output (in milliampere seconds), contrast resolution assessed in terms of the signal difference–to-noise ratio (SDNR), spatial resolution semiquantitatively assessed by using a line-pair module from a phantom, and qualitative evaluation of cadaver images for potential diagnostic value and image artifacts by an expert CT observer (musculoskeletal radiologist). Results The dose for a nominal scan protocol (80 kVp, 108 mAs) was 9 mGy (absolute dose measured at the center of a CT dose index phantom). SDNR was maximized with the 80-kVp scan technique, and contrast resolution was sufficient for visualization of muscle, fat, ligaments and/or tendons, cartilage joint space, and bone. Spatial resolution in the axial plane exceeded 15 line pairs per centimeter. Streaks associated with x-ray scatter (in thicker regions of the patient—eg, the knee), beam hardening (about cortical bone—eg, the femoral shaft), and cone-beam artifacts (at joint space surfaces oriented along the scanning plane—eg, the interphalangeal joints) presented a slight impediment to visualization. Cadaver images (elbow, hand, knee, and foot) demonstrated excellent visibility of bone detail and good soft-tissue visibility suitable to a broad spectrum of musculoskeletal indications. Conclusion A dedicated extremity cone-beam CT scanner capable of imaging upper and lower extremities (including weight-bearing examinations) provides sufficient image quality and favorable dose characteristics to warrant further evaluation for clinical use. © RSNA, 2013 Online supplemental material is available for

Wide coverage by volume CT: benefits for cardiac imaging

NASA Astrophysics Data System (ADS)

Sablayrolles, Jean-Louis; Cesmeli, Erdogan; Mintandjian, Laura; Adda, Olivier; Dessalles-Martin, Diane

2005-04-01

With the development of new technologies, computed tomography (CT) is becoming a strong candidate for non-invasive imaging based tool for cardiac disease assessment. One of the challenges of cardiac CT is that a typical scan involves a breath hold period consisting of several heartbeats, about 20 sec with scanners having a longitudinal coverage of 2 cm, and causing the image quality (IQ) to be negatively impacted since beat to beat variation is high likely to occur without any medication, e.g. beta blockers. Because of this and the preference for shorter breath hold durations, a CT scanner with a wide coverage without the compromise in the spatial and temporal resolution of great clinical value. In this study, we aimed at determining the optimum scan duration and the delay relative to beginning of breath hold, to achieve high IQ. We acquired EKG data from 91 consecutive patients (77 M, 14 F; Age: 57 +/- 14) undergoing cardiac CT exams with contrast, performed on LightSpeed 16 and LightSpeed Pro16. As an IQ metric, we adopted the standard deviation of "beat-to-beat variation" (stdBBV) within a virtual scan period. Two radiologists evaluated images by assigning a score of 1 (worst) to 4 best). We validated stdBBV with the radiologist scores, which resulted in a population distribution of 9.5, 9.5, 31, and 50% for the score groups 1, 2, 3, and 4, respectively. Based on the scores, we defined a threshold for stdBBV and identified an optimum combination of virtual scan period and a delay. With the assumption that the relationship between the stdBBV and diagnosable scan IQ holds, our analysis suggested that the success rate can be improved to 100% with scan durations equal or less than 5 sec with a delay of 1 - 2 sec. We confirmed the suggested conclusion with LightSpeed VCT (GE Healthcare Technologies, Waukesha, WI), which has a wide longitudinal coverage, fine isotropic spatial resolution, and high temporal resolution, e.g. 40 mm coverage per rotation of 0.35 sec

Non-rigid registration between 3D ultrasound and CT images of the liver based on intensity and gradient information

NASA Astrophysics Data System (ADS)

Lee, Duhgoon; Nam, Woo Hyun; Lee, Jae Young; Ra, Jong Beom

2011-01-01

In order to utilize both ultrasound (US) and computed tomography (CT) images of the liver concurrently for medical applications such as diagnosis and image-guided intervention, non-rigid registration between these two types of images is an essential step, as local deformation between US and CT images exists due to the different respiratory phases involved and due to the probe pressure that occurs in US imaging. This paper introduces a voxel-based non-rigid registration algorithm between the 3D B-mode US and CT images of the liver. In the proposed algorithm, to improve the registration accuracy, we utilize the surface information of the liver and gallbladder in addition to the information of the vessels inside the liver. For an effective correlation between US and CT images, we treat those anatomical regions separately according to their characteristics in US and CT images. Based on a novel objective function using a 3D joint histogram of the intensity and gradient information, vessel-based non-rigid registration is followed by surface-based non-rigid registration in sequence, which improves the registration accuracy. The proposed algorithm is tested for ten clinical datasets and quantitative evaluations are conducted. Experimental results show that the registration error between anatomical features of US and CT images is less than 2 mm on average, even with local deformation due to different respiratory phases and probe pressure. In addition, the lesion registration error is less than 3 mm on average with a maximum of 4.5 mm that is considered acceptable for clinical applications.

Modeling respiratory motion for reducing motion artifacts in 4D CT images.

PubMed

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

A novel concept for CT with fixed anodes (FACT): Medical imaging based on the feasibility of thermal load capacity.

PubMed

Kellermeier, Markus; Bert, Christoph; Müller, Reinhold G

2015-07-01

Focussing primarily on thermal load capacity, we describe the performance of a novel fixed anode CT (FACT) compared with a 100 kW reference CT. Being a fixed system, FACT has no focal spot blurring of the X-ray source during projection. Monte Carlo and finite element methods were used to determine the fluence proportional to thermal capacity. Studies of repeated short-time exposures showed that FACT could operate in pulsed mode for an unlimited period. A virtual model for FACT was constructed to analyse various temporal sequences for the X-ray source ring, representing a circular array of 1160 fixed anodes in the gantry. Assuming similar detector properties at a very small integration time, image quality was investigated using an image reconstruction library. Our model showed that approximately 60 gantry rounds per second, i.e. 60 sequential targetings of the 1160 anodes per second, were required to achieve a performance level equivalent to that of the reference CT (relative performance, RP = 1) at equivalent image quality. The optimal projection duration in each direction was about 10 μs. With a beam pause of 1 μs between projections, 78.4 gantry rounds per second with consecutive source activity were thermally possible at a given thermal focal spot. The settings allowed for a 1.3-fold (RP = 1.3) shorter scan time than conventional CT while maintaining radiation exposure and image quality. Based on the high number of rounds, FACT supports a high image frame rate at low doses, which would be beneficial in a wide range of diagnostic and technical applications. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Cross-modality PET/CT and contrast-enhanced CT imaging for pancreatic cancer

PubMed Central

Zhang, Jian; Zuo, Chang-Jing; Jia, Ning-Yang; Wang, Jian-Hua; Hu, Sheng-Ping; Yu, Zhong-Fei; Zheng, Yuan; Zhang, An-Yu; Feng, Xiao-Yuan

2015-01-01

AIM: To explore the diagnostic value of the cross-modality fusion images provided by positron emission tomography/computed tomography (PET/CT) and contrast-enhanced CT (CECT) for pancreatic cancer (PC). METHODS: Data from 70 patients with pancreatic lesions who underwent CECT and PET/CT examinations at our hospital from August 2010 to October 2012 were analyzed. PET/CECT for the cross-modality image fusion was obtained using TureD software. The diagnostic efficiencies of PET/CT, CECT and PET/CECT were calculated and compared with each other using a χ2 test. P < 0.05 was considered to indicate statistical significance. RESULTS: Of the total 70 patients, 50 had PC and 20 had benign lesions. The differences in the sensitivity, negative predictive value (NPV), and accuracy between CECT and PET/CECT in detecting PC were statistically significant (P < 0.05 for each). In 15 of the 31 patients with PC who underwent a surgical operation, peripancreatic vessel invasion was verified. The differences in the sensitivity, positive predictive value, NPV, and accuracy of CECT vs PET/CT and PET/CECT vs PET/CT in diagnosing peripancreatic vessel invasion were statistically significant (P < 0.05 for each). In 19 of the 31 patients with PC who underwent a surgical operation, regional lymph node metastasis was verified by postsurgical histology. There was no statistically significant difference among the three methods in detecting regional lymph node metastasis (P > 0.05 for each). In 17 of the 50 patients with PC confirmed by histology or clinical follow-up, distant metastasis was confirmed. The differences in the sensitivity and NPV between CECT and PET/CECT in detecting distant metastasis were statistically significant (P < 0.05 for each). CONCLUSION: Cross-modality image fusion of PET/CT and CECT is a convenient and effective method that can be used to diagnose and stage PC, compensating for the defects of PET/CT and CECT when they are conducted individually. PMID:25780297

Design of CT reconstruction kernel specifically for clinical lung imaging

NASA Astrophysics Data System (ADS)

Cody, Dianna D.; Hsieh, Jiang; Gladish, Gregory W.

2005-04-01

In this study we developed a new reconstruction kernel specifically for chest CT imaging. An experimental flat-panel CT scanner was used on large dogs to produce 'ground-truth" reference chest CT images. These dogs were also examined using a clinical 16-slice CT scanner. We concluded from the dog images acquired on the clinical scanner that the loss of subtle lung structures was due mostly to the presence of the background noise texture when using currently available reconstruction kernels. This qualitative evaluation of the dog CT images prompted the design of a new recon kernel. This new kernel consisted of the combination of a low-pass and a high-pass kernel to produce a new reconstruction kernel, called the 'Hybrid" kernel. The performance of this Hybrid kernel fell between the two kernels on which it was based, as expected. This Hybrid kernel was also applied to a set of 50 patient data sets; the analysis of these clinical images is underway. We are hopeful that this Hybrid kernel will produce clinical images with an acceptable tradeoff of lung detail, reliable HU, and image noise.

3D SPECT/CT fusion using image data projection of bone SPECT onto 3D volume-rendered CT images: feasibility and clinical impact in the diagnosis of bone metastasis.

PubMed

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�

A region-based segmentation of tumour from brain CT images using nonlinear support vector machine classifier.

PubMed

Nanthagopal, A Padma; Rajamony, R Sukanesh

2012-07-01

The proposed system provides new textural information for segmenting tumours, efficiently and accurately and with less computational time, from benign and malignant tumour images, especially in smaller dimensions of tumour regions of computed tomography (CT) images. Region-based segmentation of tumour from brain CT image data is an important but time-consuming task performed manually by medical experts. The objective of this work is to segment brain tumour from CT images using combined grey and texture features with new edge features and nonlinear support vector machine (SVM) classifier. The selected optimal features are used to model and train the nonlinear SVM classifier to segment the tumour from computed tomography images and the segmentation accuracies are evaluated for each slice of the tumour image. The method is applied on real data of 80 benign, malignant tumour images. The results are compared with the radiologist labelled ground truth. Quantitative analysis between ground truth and the segmented tumour is presented in terms of segmentation accuracy and the overlap similarity measure dice metric. From the analysis and performance measures such as segmentation accuracy and dice metric, it is inferred that better segmentation accuracy and higher dice metric are achieved with the normalized cut segmentation method than with the fuzzy c-means clustering method.

Progress in SPECT/CT imaging of prostate cancer.

PubMed

Seo, Youngho; Franc, Benjamin L; Hawkins, Randall A; Wong, Kenneth H; Hasegawa, Bruce H

2006-08-01

Prostate cancer is the most common type of cancer (other than skin cancer) among men in the United States. Although prostate cancer is one of the few cancers that grow so slowly that it may never threaten the lives of some patients, it can be lethal once metastasized. Indium-111 capromab pendetide (ProstaScint, Cytogen Corporation, Princeton, NJ) imaging is indicated for staging and recurrence detection of the disease, and is particularly useful to determine whether or not the disease has spread to distant metastatic sites. However, the interpretation of 111In-capromab pendetide is challenging without correlated structural information mostly because the radiopharmaceutical demonstrates nonspecific uptake in the normal vasculature, bowel, bone marrow, and the prostate gland. We developed an improved method of imaging and localizing 111In-Capromab pendetide using a SPECT/CT imaging system. The specific goals included: i) development and application of a novel iterative SPECT reconstruction algorithm that utilizes a priori information from coregistered CT; and ii) assessment of clinical impact of adding SPECT/CT for prostate cancer imaging with capromab pendetide utilizing the standard and novel reconstruction techniques. Patient imaging studies with capromab pendetide were performed from 1999 to 2004 using two different SPECT/CT scanners, a prototype SPECT/CT system and a commercial SPECT/CT system (Discovery VH, GE Healthcare, Waukesha, WI). SPECT projection data from both systems were reconstructed using an experimental iterative algorithm that compensates for both photon attenuation and collimator blurring. In addition, the data obtained from the commercial system were reconstructed with attenuation correction using an OSEM reconstruction supplied by the camera manufacturer for routine clinical interpretation. For 12 sets of patient data, SPECT images reconstructed using the experimental algorithm were interpreted separately and compared with interpretation of

Simulation of pseudo-CT images based on deformable image registration of ultrasound images: A proof of concept for transabdominal ultrasound imaging of the prostate during radiotherapy

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

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 automatic end-to-end method for content-based image retrieval of CT scans with similar liver lesion annotations.

PubMed

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.

Enhancing 18F-FDG-PET/CT analysis in lung cancer patients. Is CT-CT image fusion helpful in predicting pleural involvement? A pilot study.

PubMed

Kapfhammer, A; Winkens, T; Lesser, T; Reissig, A; Steinert, M; Freesmeyer, M

2015-01-01

To retrospectively evaluate the feasibility and value of CT-CT image fusion to assess the shift of peripheral lung cancers with/-out chest wall infiltration, comparing computed tomography acquisitions in shallow-breathing (SB-CT) and deep-inspiration breath-hold (DIBH-CT) in patients undergoing FDG-PET/CT for lung cancer staging. Image fusion of SB-CT and DIBH-CT was performed with a multimodal workstation used for nuclear medicine fusion imaging. The distance of intrathoracic landmarks and the positional shift of tumours were measured using semi-transparent overlay of both CT series. Statistical analyses were adjusted for confounders of tumour infiltration. Cutoff levels were calculated for prediction of no-/infiltration. Lateral pleural recessus and diaphragm showed the largest respiratory excursions. Infiltrating lung cancers showed more limited respiratory shifts than non-infiltrating tumours. A large respiratory tumour-motility accurately predicted non-infiltration. However, the tumour shifts were limited and variable, limiting the accuracy of prediction. This pilot fusion study proved feasible and allowed a simple analysis of the respiratory shifts of peripheral lung tumours using CT-CT image fusion in a PET/CT setting. The calculated cutoffs were useful in predicting the exclusion of chest wall infiltration but did not accurately predict tumour infiltration. This method can provide additional qualitative information in patients with lung cancers with contact to the chest wall but unclear CT evidence of infiltration undergoing PET/CT without the need of additional investigations. Considering the small sample size investigated, further studies are necessary to verify the obtained results.

Medical imaging.

PubMed Central

Kreel, L.

1991-01-01

There is now a wide choice of medical imaging to show both focal and diffuse pathologies in various organs. Conventional radiology with plain films, fluoroscopy and contrast medium have many advantages, being readily available with low-cost apparatus and a familiarity that almost leads to contempt. The use of plain films in chest disease and in trauma does not need emphasizing, yet there are still too many occasions when the answer obtainable from a plain radiograph has not been available. The film may have been mislaid, or the examination was not requested, or the radiograph had been misinterpreted. The converse is also quite common. Examinations are performed that add nothing to patient management, such as skull films when CT will in any case be requested or views of the internal auditory meatus and heal pad thickness in acromegaly, to quote some examples. Other issues are more complicated. Should the patient who clinically has gall-bladder disease have more than a plain film that shows gall-stones? If the answer is yes, then why request a plain film if sonography will in any case be required to 'exclude' other pathologies especially of the liver or pancreas? But then should cholecystography, CT or scintigraphy be added for confirmation? Quite clearly there will be individual circumstances to indicate further imaging after sonography but in the vast majority of patients little or no extra information will be added. Statistics on accuracy and specificity will, in the case of gall-bladder pathology, vary widely if adenomyomatosis is considered by some to be a cause of symptoms or if sonographic examinations 'after fatty meals' are performed. The arguments for or against routine contrast urography rather than sonography are similar but the possibility of contrast reactions and the need to limit ionizing radiation must be borne in mind. These diagnostic strategies are also being influenced by their cost and availability; purely pragmatic considerations are not

Multimodality and nanoparticles in medical imaging

PubMed Central

Huang, Wen-Yen; Davis, Jason J.

2015-01-01

A number of medical imaging techniques are used heavily in the provision of spatially resolved information on disease and physiological status and accordingly play a critical role in clinical diagnostics and subsequent treatment. Though, for most imaging modes, contrast is potentially enhanced through the use of contrast agents or improved hardware or imaging protocols, no single methodology provides, in isolation, a detailed mapping of anatomy, disease markers or physiological status. In recent years, the concept of complementing the strengths of one imaging modality with those of another has come to the fore and been further bolstered by the development of fused instruments such as PET/CT and PET/MRI stations. Coupled with the continual development in imaging hardware has been a surge in reports of contrast agents bearing multiple functionality, potentially providing not only a powerful and highly sensitised means of co-localising physiological/disease status and anatomy, but also the tracking and delineation of multiple markers and indeed subsequent or simultaneous highly localized therapy (“theragnostics”). PMID:21409202

Convolutional auto-encoder for image denoising of ultra-low-dose CT.

PubMed

Nishio, Mizuho; Nagashima, Chihiro; Hirabayashi, Saori; Ohnishi, Akinori; Sasaki, Kaori; Sagawa, Tomoyuki; Hamada, Masayuki; Yamashita, Tatsuo

2017-08-01

The purpose of this study was to validate a patch-based image denoising method for ultra-low-dose CT images. Neural network with convolutional auto-encoder and pairs of standard-dose CT and ultra-low-dose CT image patches were used for image denoising. The performance of the proposed method was measured by using a chest phantom. Standard-dose and ultra-low-dose CT images of the chest phantom were acquired. The tube currents for standard-dose and ultra-low-dose CT were 300 and 10 mA, respectively. Ultra-low-dose CT images were denoised with our proposed method using neural network, large-scale nonlocal mean, and block-matching and 3D filtering. Five radiologists and three technologists assessed the denoised ultra-low-dose CT images visually and recorded their subjective impressions of streak artifacts, noise other than streak artifacts, visualization of pulmonary vessels, and overall image quality. For the streak artifacts, noise other than streak artifacts, and visualization of pulmonary vessels, the results of our proposed method were statistically better than those of block-matching and 3D filtering (p-values < 0.05). On the other hand, the difference in the overall image quality between our proposed method and block-matching and 3D filtering was not statistically significant (p-value = 0.07272). The p-values obtained between our proposed method and large-scale nonlocal mean were all less than 0.05. Neural network with convolutional auto-encoder could be trained using pairs of standard-dose and ultra-low-dose CT image patches. According to the visual assessment by radiologists and technologists, the performance of our proposed method was superior to that of large-scale nonlocal mean and block-matching and 3D filtering.

The LISS--a public database of common imaging signs of lung diseases for computer-aided detection and diagnosis research and medical education.

PubMed

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.

Lab-based x-ray nanoCT imaging

NASA Astrophysics Data System (ADS)

Müller, Mark; Allner, Sebastian; Ferstl, Simone; Dierolf, Martin; Tuohimaa, Tomi; Pfeiffer, Franz

2017-03-01

Due to the recent development of transmission X-ray tubes with very small focal spot sizes, laboratory-based CT imaging with sub-micron resolutions is nowadays possible. We recently developed a novel X-ray nanoCT setup featuring a prototype nanofocus X-ray source and a single-photon counting detector. The system is based on mere geometrical magnification and can reach resolutions of 200 nm. To demonstrate the potential of the nanoCT system for biomedical applications we show high resolution nanoCT data of a small piece of human tooth comprising coronal dentin. The reconstructed CT data clearly visualize the dentin tubules within the tooth piece.

Three-dimensional murine airway segmentation in micro-CT images

NASA Astrophysics Data System (ADS)

Shi, Lijun; Thiesse, Jacqueline; McLennan, Geoffrey; Hoffman, Eric A.; Reinhardt, Joseph M.

2007-03-01

Thoracic imaging for small animals has emerged as an important tool for monitoring pulmonary disease progression and therapy response in genetically engineered animals. Micro-CT is becoming the standard thoracic imaging modality in small animal imaging because it can produce high-resolution images of the lung parenchyma, vasculature, and airways. Segmentation, measurement, and visualization of the airway tree is an important step in pulmonary image analysis. However, manual analysis of the airway tree in micro-CT images can be extremely time-consuming since a typical dataset is usually on the order of several gigabytes in size. Automated and semi-automated tools for micro-CT airway analysis are desirable. In this paper, we propose an automatic airway segmentation method for in vivo micro-CT images of the murine lung and validate our method by comparing the automatic results to manual tracing. Our method is based primarily on grayscale morphology. The results show good visual matches between manually segmented and automatically segmented trees. The average true positive volume fraction compared to manual analysis is 91.61%. The overall runtime for the automatic method is on the order of 30 minutes per volume compared to several hours to a few days for manual analysis.

SU-F-J-161: Prostate Contouring in Patients with Bilateral Hip Prostheses: Impact of Using Artifact-Reduced CT Images and MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elzibak, A; Loblaw, A; Morton, G

Purpose: To investigate the usefulness of metal artifact reduction in CT images of patients with bilateral hip prostheses (BHP) for contouring the prostate and determine if the inclusion of MR images provides additional benefits. Methods: Five patients with BHP were CT scanned using our clinical protocol (140kV, 300mAs, 3mm slices, 1.5mm increment, Philips Medical Systems, OH). Images were reconstructed with the orthopaedic metal artifact reduction (O-MAR) algorithm. MRI scanning was then performed (1.5T, GE Healthcare, WI) with a flat table-top (T{sub 2}-weighted, inherent body coil, FRFSE, 3mm slices with 0mm gap). All images were transferred to Pinnacle (Version 9.2, Philipsmore » Medical Systems). For each patient, two data sets were produced: one containing the O-MAR-corrected CT images and another containing fused MRI and O-MAR-corrected CT images. Four genito-urinary radiation oncologists contoured the prostate of each patient on the O-MAR-corrected CT data. Two weeks later, they contoured the prostate on the fused data set, blinded to all other contours. During each contouring session, the oncologists reported their confidence in the contours (1=very confident, 3=not confident) and the contouring difficulty that they experienced (1=really easy, 4=very challenging). Prostate volumes were computed from the contours and the conformity index was used to evaluate inter-observer variability. Results: Larger prostate volumes were found on the O-MAR-corrected CT set than on the fused set (p< 0.05, median=36.9cm{sup 3} vs. 26.63 cm{sup 3}). No significant differences were noted in the inter-observer variability between the two data sets (p=0.3). Contouring difficulty decreased with the addition of MRI (p<0.05) while the radiation oncologists reported more confidence in their contours when MRI was fused with the O-MAR-corrected CT data (p<0.05). Conclusion: This preliminary work demonstrated that, while O-MAR correction to CT images improves visualization of

Low-cost printing of computerised tomography (CT) images where there is no dedicated CT camera.

PubMed

Tabari, Abdulkadir M

2007-01-01

Many developing countries still rely on conventional hard copy images to transfer information among physicians. We have developed a low-cost alternative method of printing computerised tomography (CT) scan images where there is no dedicated camera. A digital camera is used to photograph images from the CT scan screen monitor. The images are then transferred to a PC via a USB port, before being printed on glossy paper using an inkjet printer. The method can be applied to other imaging modalities like ultrasound and MRI and appears worthy of emulation elsewhere in the developing world where resources and technical expertise are scarce.

Recent Advances in Cardiac Computed Tomography: Dual Energy, Spectral and Molecular CT Imaging

PubMed Central

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

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.

Enabling image fusion for a CT guided needle placement robot

NASA Astrophysics Data System (ADS)

Seifabadi, Reza; Xu, Sheng; Aalamifar, Fereshteh; Velusamy, Gnanasekar; Puhazhendi, Kaliyappan; Wood, Bradford J.

2017-03-01

Purpose: This study presents development and integration of hardware and software that enables ultrasound (US) and computer tomography (CT) fusion for a FDA-approved CT-guided needle placement robot. Having real-time US image registered to a priori-taken intraoperative CT image provides more anatomic information during needle insertion, in order to target hard-to-see lesions or avoid critical structures invisible to CT, track target motion, and to better monitor ablation treatment zone in relation to the tumor location. Method: A passive encoded mechanical arm is developed for the robot in order to hold and track an abdominal US transducer. This 4 degrees of freedom (DOF) arm is designed to attach to the robot end-effector. The arm is locked by default and is released by a press of button. The arm is designed such that the needle is always in plane with US image. The articulated arm is calibrated to improve its accuracy. Custom designed software (OncoNav, NIH) was developed to fuse real-time US image to a priori-taken CT. Results: The accuracy of the end effector before and after passive arm calibration was 7.07mm +/- 4.14mm and 1.74mm +/-1.60mm, respectively. The accuracy of the US image to the arm calibration was 5mm. The feasibility of US-CT fusion using the proposed hardware and software was demonstrated in an abdominal commercial phantom. Conclusions: Calibration significantly improved the accuracy of the arm in US image tracking. Fusion of US to CT using the proposed hardware and software was feasible.

DICOM image integration into an electronic medical record using thin viewing clients

NASA Astrophysics Data System (ADS)

Stewart, Brent K.; Langer, Steven G.; Taira, Ricky K.

1998-07-01

Purpose -- To integrate radiological DICOM images into our currently existing web-browsable Electronic Medical Record (MINDscape). Over the last five years the University of Washington has created a clinical data repository combining in a distributed relational database information from multiple departmental databases (MIND). A text-based view of this data called the Mini Medical Record (MMR) has been available for three years. MINDscape, unlike the text based MMR, provides a platform independent, web browser view of the MIND dataset that can easily be linked to other information resources on the network. We have now added the integration of radiological images into MINDscape through a DICOM webserver. Methods/New Work -- we have integrated a commercial webserver that acts as a DICOM Storage Class Provider to our, computed radiography (CR), computed tomography (CT), digital fluoroscopy (DF), magnetic resonance (MR) and ultrasound (US) scanning devices. These images can be accessed through CGI queries or by linking the image server database using ODBC or SQL gateways. This allows the use of dynamic HTML links to the images on the DICOM webserver from MINDscape, so that the radiology reports already resident in the MIND repository can be married with the associated images through the unique examination accession number generated by our Radiology Information System (RIS). The web browser plug-in used provides a wavelet decompression engine (up to 16-bits per pixel) and performs the following image manipulation functions: window/level, flip, invert, sort, rotate, zoom, cine-loop and save as JPEG. Results -- Radiological DICOM image sets (CR, CT, MR and US) are displayed with associated exam reports for referring physician and clinicians anywhere within the widespread academic medical center on PCs, Macs, X-terminals and Unix computers. This system is also being used for home teleradiology application. Conclusion -- Radiological DICOM images can be made available

SU-C-17A-03: Evaluation of Deformable Image Registration Methods Between MRI and CT for Prostate Cancer Radiotherapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wen, N; Glide-Hurst, C; Zhong, H

2014-06-15

Purpose: We evaluated the performance of two commercially available and one open source B-Spline deformable image registration (DIR) algorithms between T2-weighted MRI and treatment planning CT using the DICE indices. Methods: CT simulation (CT-SIM) and MR simulation (MR-SIM) for four prostate cancer patients were conducted on the same day using the same setup and immobilization devices. CT images (120 kVp, 500 mAs, voxel size = 1.1x1.1x3.0 mm3) were acquired using an open-bore CT scanner. T2-weighted Turbo Spine Echo (T2W-TSE) images (TE/TR/α = 80/4560 ms/90°, voxel size = 0.7×0.7×2.5 mm3) were scanned on a 1.0T high field open MR-SIM. Prostates, seminalmore » vesicles, rectum and bladders were delineated on both T2W-TSE and CT images by the attending physician. T2W-TSE images were registered to CT images using three DIR algorithms, SmartAdapt (Varian), Velocity AI (Velocity) and Elastix (Klein et al 2010) and contours were propagated. DIR results were evaluated quantitatively or qualitatively by image comparison and calculating organ DICE indices. Results: Significant differences in the contours of prostate and seminal vesicles were observed between MR and CT. On average, volume changes of the propagated contours were 5%, 2%, 160% and 8% for the prostate, seminal vesicles, bladder and rectum respectively. Corresponding mean DICE indices were 0.7, 0.5, 0.8, and 0.7. The intraclass correlation coefficient (ICC) was 0.9 among three algorithms for the Dice indices. Conclusion: Three DIR algorithms for CT/MR registration yielded similar results for organ propagation. Due to the different soft tissue contrasts between MRI and CT, organ delineation of prostate and SVs varied significantly, thus efforts to develop other DIR evaluation metrics are warranted. Conflict of interest: Submitting institution has research agreements with Varian Medical System and Philips Healthcare.« less

CT vaginography: a new CT technique for imaging of upper and middle vaginal fistulas.

PubMed

Botsikas, Diomidis; Pluchino, Nicola; Kalovidouri, Anastasia; Platon, Alexandra; Montet, Xavier; Dallenbach, Patrick; Poletti, Pierre-Alexandre

2017-05-01

Different types of vaginal fistulas is a relatively uncommon condition in the Western world but very frequent in developing countries. In the past, conventional vaginography was the radiological examination of choice for exploring this condition. CT and MRI are now both used for this purpose. Our objective was to test the feasibility and to explore the potential role of a new CT imaging technique implementing vaginal introitus obstruction and opacification of the vagina with iodine contrast agent, to show patency of a fistula. We describe the technical protocol of CT-vaginography as performed in Geneva University Hospitals, including vaginal catheterization with a Foley catheter and obstruction of the introitus by inflating the balloon of the catheter. We also report three cases of patients with suspected vaginal fistula who underwent CT-vaginography. The examinations were technically successful. In one patient, it revealed the presence of fistulous pathways from the vaginal fornix along the bilateral infected surgical prostheses. In a second patient, it showed a fistula between the vagina and the necrotic cavity of a recurrent cervical cancer. In a third patient, it proved the absence of a suspected vaginal fistula. CT-vaginography is a technically feasible CT protocol that provides anatomical and functional information on clinically suspected vaginal fistulas. Advances in knowledge: After the abandon of conventional vaginography in the era of transaxial imaging, the current modalities of imaging vaginal fistulas provide excellent anatomical detail but less functional information concerning the permeability of a vaginal fistulous pathway. We propose the use of CT-vaginography, a technical protocol that we describe in detail.

X-ray detectors in medical imaging

NASA Astrophysics Data System (ADS)

Spahn, Martin

2013-12-01

Healthcare systems are subject to continuous adaptation, following trends such as the change of demographic structures, the rise of life-style related and chronic diseases, and the need for efficient and outcome-oriented procedures. This also influences the design of new imaging systems as well as their components. The applications of X-ray imaging in the medical field are manifold and have led to dedicated modalities supporting specific imaging requirements, for example in computed tomography (CT), radiography, angiography, surgery or mammography, delivering projection or volumetric imaging data. Depending on the clinical needs, some X-ray systems enable diagnostic imaging while others support interventional procedures. X-ray detector design requirements for the different medical applications can vary strongly with respect to size and shape, spatial resolution, frame rates and X-ray flux, among others. Today, integrating X-ray detectors are in common use. They are predominantly based on scintillators (e.g. CsI or Gd2O2S) and arrays of photodiodes made from crystalline silicon (Si) or amorphous silicon (a-Si) or they employ semiconductors (e.g. Se) with active a-Si readout matrices. Ongoing and future developments of X-ray detectors will include optimization of current state-of-the-art integrating detectors in terms of performance and cost, will enable the usage of large size CMOS-based detectors, and may facilitate photon counting techniques with the potential to further enhance performance characteristics and foster the prospect of new clinical applications.

Technical aspects of CT imaging of the spine.

PubMed

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.

Nondestructive Evaluation of Hardwood Logs Using Automated Interpretation of CT Images

Treesearch

Daniel L. Schmoldt; Dongping Zhu; Richard W. Conners

1993-01-01

Computed tomography (CT) imaging is being used to examine the internal structure of hardwood logs. The following steps are used to automatically interpret CT images: (1) preprocessing to remove unwanted portions of the image, e.g., annual ring structure, (2) image-by-image segmentation to produce relatively homogeneous image areas, (3) volume growing to create volumes...

Automated volumetric lung segmentation of thoracic CT images using fully convolutional neural network

NASA Astrophysics Data System (ADS)

Negahdar, Mohammadreza; Beymer, David; Syeda-Mahmood, Tanveer

2018-02-01

Deep Learning models such as Convolutional Neural Networks (CNNs) have achieved state-of-the-art performance in 2D medical image analysis. In clinical practice; however, most analyzed and acquired medical data are formed of 3D volumes. In this paper, we present a fast and efficient 3D lung segmentation method based on V-net: a purely volumetric fully CNN. Our model is trained on chest CT images through volume to volume learning, which palliates overfitting problem on limited number of annotated training data. Adopting a pre-processing step and training an objective function based on Dice coefficient addresses the imbalance between the number of lung voxels against that of background. We have leveraged Vnet model by using batch normalization for training which enables us to use higher learning rate and accelerates the training of the model. To address the inadequacy of training data and obtain better robustness, we augment the data applying random linear and non-linear transformations. Experimental results on two challenging medical image data show that our proposed method achieved competitive result with a much faster speed.

Intra-operative adjustment of standard planes in C-arm CT image data.

PubMed

Brehler, Michael; Görres, Joseph; Franke, Jochen; Barth, Karl; Vetter, Sven Y; Grützner, Paul A; Meinzer, Hans-Peter; Wolf, Ivo; Nabers, Diana

2016-03-01

With the help of an intra-operative mobile C-arm CT, medical interventions can be verified and corrected, avoiding the need for a post-operative CT and a second intervention. An exact adjustment of standard plane positions is necessary for the best possible assessment of the anatomical regions of interest but the mobility of the C-arm causes the need for a time-consuming manual adjustment. In this article, we present an automatic plane adjustment at the example of calcaneal fractures. We developed two feature detection methods (2D and pseudo-3D) based on SURF key points and also transferred the SURF approach to 3D. Combined with an atlas-based registration, our algorithm adjusts the standard planes of the calcaneal C-arm images automatically. The robustness of the algorithms is evaluated using a clinical data set. Additionally, we tested the algorithm's performance for two registration approaches, two resolutions of C-arm images and two methods for metal artifact reduction. For the feature extraction, the novel 3D-SURF approach performs best. As expected, a higher resolution ([Formula: see text] voxel) leads also to more robust feature points and is therefore slightly better than the [Formula: see text] voxel images (standard setting of device). Our comparison of two different artifact reduction methods and the complete removal of metal in the images shows that our approach is highly robust against artifacts and the number and position of metal implants. By introducing our fast algorithmic processing pipeline, we developed the first steps for a fully automatic assistance system for the assessment of C-arm CT images.

Characterisation of Geiger-mode avalanche photodiodes for medical imaging applications

NASA Astrophysics Data System (ADS)

Britvitch, I.; Johnson, I.; Renker, D.; Stoykov, A.; Lorenz, E.

2007-02-01

Recently developed multipixel Geiger-mode avalanche photodiodes (G-APDs) are very promising candidates for the detection of light in medical imaging instruments (e.g. positron emission tomography) as well as in high-energy physics experiments and astrophysical applications. G-APDs are especially well suited for morpho-functional imaging (multimodality PET/CT, SPECT/CT, PET/MRI, SPECT/MRI). G-APDs have many advantages compared to conventional photosensors such as photomultiplier tubes because of their compact size, low-power consumption, high quantum efficiency and insensitivity to magnetic fields. Compared to avalanche photodiodes and PIN diodes, they are advantageous because of their high gain, reduced sensitivity to pick up and the so-called nuclear counter effect and lower noise. We present measurements of the basic G-APD characteristics: photon detection efficiency, gain, inter-cell crosstalk, dynamic range, recovery time and dark count rate.

Development of a fluorescent x-ray source for medical imaging

NASA Astrophysics Data System (ADS)

Toyofuku, F.; Tokumori, K.; Nishimura, K.; Saito, T.; Takeda, T.; Itai, Y.; Hyodo, K.; Ando, M.; Endo, M.; Naito, H.; Uyama, C.

1995-02-01

A fluorescent x-ray source for medical imaging, such as K-edge subtraction angiography and monochromatic x-ray CT, has been developed. Using a 6.5 GeV accumulation ring in Tsukuba, fluorescent x rays, which range from about 30 to 70 keV are generated by irradiating several target materials. Measurements have been made of output intensities and energy spectra for different target angles and extraction angles. The intensities of fluorescent x rays at a 30 mA beam current are on the order of 1-3×106 photons/mm2/s at 30 cm from the local spot where the incident beam is collimated to 1 mm2. A phantom which contains three different contrast media (iodine, barium, gadolinium) was used for the K-edge energy subtraction, and element selective CT images were obtained.

Automatic coronary calcium scoring using noncontrast and contrast CT images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Guanyu, E-mail: yang.list@seu.edu.cn; Chen, Yang; Shu, Huazhong

Purpose: Calcium scoring is widely used to assess the risk of coronary heart disease (CHD). Accurate coronary artery calcification detection in noncontrast CT image is a prerequisite step for coronary calcium scoring. Currently, calcified lesions in the coronary arteries are manually identified by radiologists in clinical practice. Thus, in this paper, a fully automatic calcium scoring method was developed to alleviate the work load of the radiologists or cardiologists. Methods: The challenge of automatic coronary calcification detection is to discriminate the calcification in the coronary arteries from the calcification in the other tissues. Since the anatomy of coronary arteries ismore » difficult to be observed in the noncontrast CT images, the contrast CT image of the same patient is used to extract the regions of the aorta, heart, and coronary arteries. Then, a patient-specific region-of-interest (ROI) is generated in the noncontrast CT image according to the segmentation results in the contrast CT image. This patient-specific ROI focuses on the regions in the neighborhood of coronary arteries for calcification detection, which can eliminate the calcifications in the surrounding tissues. A support vector machine classifier is applied finally to refine the results by removing possible image noise. Furthermore, the calcified lesions in the noncontrast images belonging to the different main coronary arteries are identified automatically using the labeling results of the extracted coronary arteries. Results: Forty datasets from four different CT machine vendors were used to evaluate their algorithm, which were provided by the MICCAI 2014 Coronary Calcium Scoring (orCaScore) Challenge. The sensitivity and positive predictive value for the volume of detected calcifications are 0.989 and 0.948. Only one patient out of 40 patients had been assigned to the wrong risk category defined according to Agatston scores (0, 1–100, 101–300, >300) by comparing with the

Registration of parametric dynamic F-18-FDG PET/CT breast images with parametric dynamic Gd-DTPA breast images

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.

TU-G-BRA-02: Can We Extract Lung Function Directly From 4D-CT Without Deformable Image Registration?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kipritidis, J; Woodruff, H; Counter, W

Purpose: Dynamic CT ventilation imaging (CT-VI) visualizes air volume changes in the lung by evaluating breathing-induced lung motion using deformable image registration (DIR). Dynamic CT-VI could enable functionally adaptive lung cancer radiation therapy, but its sensitivity to DIR parameters poses challenges for validation. We hypothesize that a direct metric using CT parameters derived from Hounsfield units (HU) alone can provide similar ventilation images without DIR. We compare the accuracy of Direct and Dynamic CT-VIs versus positron emission tomography (PET) images of inhaled {sup 68}Ga-labelled nanoparticles (‘Galligas’). Methods: 25 patients with lung cancer underwent Galligas 4D-PET/CT scans prior to radiation therapy.more » For each patient we produced three CT- VIs. (i) Our novel method, Direct CT-VI, models blood-gas exchange as the product of air and tissue density at each lung voxel based on time-averaged 4D-CT HU values. Dynamic CT-VIs were produced by evaluating: (ii) regional HU changes, and (iii) regional volume changes between the exhale and inhale 4D-CT phase images using a validated B-spline DIR method. We assessed the accuracy of each CT-VI by computing the voxel-wise Spearman correlation with free-breathing Galligas PET, and also performed a visual analysis. Results: Surprisingly, Direct CT-VIs exhibited better global correlation with Galligas PET than either of the dynamic CT-VIs. The (mean ± SD) correlations were (0.55 ± 0.16), (0.41 ± 0.22) and (0.29 ± 0.27) for Direct, Dynamic HU-based and Dynamic volume-based CT-VIs respectively. Visual comparison of Direct CT-VI to PET demonstrated similarity for emphysema defects and ventral-to-dorsal gradients, but inability to identify decreased ventilation distal to tumor-obstruction. Conclusion: Our data supports the hypothesis that Direct CT-VIs are as accurate as Dynamic CT-VIs in terms of global correlation with Galligas PET. Visual analysis, however, demonstrated that different CT

Improved proton CT imaging using a bismuth germanium oxide scintillator.

PubMed

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.

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.

The use of a fully integrated electronic medical record to minimize cumulative lifetime radiation exposure from CT scanning to detect urinary tract calculi.

PubMed

Kohler, Steven W; Chen, Richard; Kagan, Alex; Helvey, Dustin W; Buccigrossi, David

2013-06-01

In order to determine the effects of implementation of an electronic medical record on rates of repeat computed tomography (CT) scanning in the emergency department (ED) setting, we analyzed the utilization of CT of the kidneys, ureters, and bladder (CT KUB) for the detection of urinary tract calculi for periods before and after the implementation of a hospital-wide electronic medical record system. Rates of repeat CT scanning within a 6-month period of previous scan were determined pre- and post-implementation and compared. Prior to implementation, there was a 6-month repeat rate of 6.2 % compared with the post-implementation period, which was associated with a 6-month repeat rate of 4.1 %. Statistical analysis using a two-sample, one-tailed t test for difference of means was associated with a p value of 0.00007. This indicates that the implementation of the electronic medical record system was associated with a 34 % decrease in 6-month repeat CT KUB scans. We conclude that the use of an electronic medical record can be associated with a decrease in utilization of unnecessary repeat CT imaging, leading to decreased cumulative lifetime risk for cancer in these patients and more efficient utilization of ED and radiologic resources.

Intra-individual diagnostic image quality and organ-specific-radiation dose comparison between spiral cCT with iterative image reconstruction and z-axis automated tube current modulation and sequential cCT.

PubMed

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.

Efficient iterative image reconstruction algorithm for dedicated breast CT

NASA Astrophysics Data System (ADS)

Antropova, Natalia; Sanchez, Adrian; Reiser, Ingrid S.; Sidky, Emil Y.; Boone, John; Pan, Xiaochuan

2016-03-01

Dedicated breast computed tomography (bCT) is currently being studied as a potential screening method for breast cancer. The X-ray exposure is set low to achieve an average glandular dose comparable to that of mammography, yielding projection data that contains high levels of noise. Iterative image reconstruction (IIR) algorithms may be well-suited for the system since they potentially reduce the effects of noise in the reconstructed images. However, IIR outcomes can be difficult to control since the algorithm parameters do not directly correspond to the image properties. Also, IIR algorithms are computationally demanding and have optimal parameter settings that depend on the size and shape of the breast and positioning of the patient. In this work, we design an efficient IIR algorithm with meaningful parameter specifications and that can be used on a large, diverse sample of bCT cases. The flexibility and efficiency of this method comes from having the final image produced by a linear combination of two separately reconstructed images - one containing gray level information and the other with enhanced high frequency components. Both of the images result from few iterations of separate IIR algorithms. The proposed algorithm depends on two parameters both of which have a well-defined impact on image quality. The algorithm is applied to numerous bCT cases from a dedicated bCT prototype system developed at University of California, Davis.

Medical Image Databases

PubMed Central

Tagare, Hemant D.; Jaffe, C. Carl; Duncan, James

1997-01-01

Abstract Information contained in medical images differs considerably from that residing in alphanumeric format. The difference can be attributed to four characteristics: (1) the semantics of medical knowledge extractable from images is imprecise; (2) image information contains form and spatial data, which are not expressible in conventional language; (3) a large part of image information is geometric; (4) diagnostic inferences derived from images rest on an incomplete, continuously evolving model of normality. This paper explores the differentiating characteristics of text versus images and their impact on design of a medical image database intended to allow content-based indexing and retrieval. One strategy for implementing medical image databases is presented, which employs object-oriented iconic queries, semantics by association with prototypes, and a generic schema. PMID:9147338

Image quality characteristics for virtual monoenergetic images using dual-layer spectral detector CT: Comparison with conventional tube-voltage images.

PubMed

Sakabe, Daisuke; Funama, Yoshinori; Taguchi, Katsuyuki; Nakaura, Takeshi; Utsunomiya, Daisuke; Oda, Seitaro; Kidoh, Masafumi; Nagayama, Yasunori; Yamashita, Yasuyuki

2018-05-01

To investigate the image quality characteristics for virtual monoenergetic images compared with conventional tube-voltage image with dual-layer spectral CT (DLCT). Helical scans were performed using a first-generation DLCT scanner, two different sizes of acrylic cylindrical phantoms, and a Catphan phantom. Three different iodine concentrations were inserted into the phantom center. The single-tube voltage for obtaining virtual monoenergetic images was set to 120 or 140 kVp. Conventional 120- and 140-kVp images and virtual monoenergetic images (40-200-keV images) were reconstructed from slice thicknesses of 1.0 mm. The CT number and image noise were measured for each iodine concentration and water on the 120-kVp images and virtual monoenergetic images. The noise power spectrum (NPS) was also calculated. The iodine CT numbers for the iodinated enhancing materials were similar regardless of phantom size and acquisition method. Compared with the iodine CT numbers of the conventional 120-kVp images, those for the monoenergetic 40-, 50-, and 60-keV images increased by approximately 3.0-, 1.9-, and 1.3-fold, respectively. The image noise values for each virtual monoenergetic image were similar (for example, 24.6 HU at 40 keV and 23.3 HU at 200 keV obtained at 120 kVp and 30-cm phantom size). The NPS curves of the 70-keV and 120-kVp images for a 1.0-mm slice thickness over the entire frequency range were similar. Virtual monoenergetic images represent stable image noise over the entire energy spectrum and improved the contrast-to-noise ratio than conventional tube voltage using the dual-layer spectral detector CT. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

AMIDE: a free software tool for multimodality medical image analysis.

PubMed

Loening, Andreas Markus; Gambhir, Sanjiv Sam

2003-07-01

Amide's a Medical Image Data Examiner (AMIDE) has been developed as a user-friendly, open-source software tool for displaying and analyzing multimodality volumetric medical images. Central to the package's abilities to simultaneously display multiple data sets (e.g., PET, CT, MRI) and regions of interest is the on-demand data reslicing implemented within the program. Data sets can be freely shifted, rotated, viewed, and analyzed with the program automatically handling interpolation as needed from the original data. Validation has been performed by comparing the output of AMIDE with that of several existing software packages. AMIDE runs on UNIX, Macintosh OS X, and Microsoft Windows platforms, and it is freely available with source code under the terms of the GNU General Public License.

Dose and image quality for a cone-beam C-arm CT system.

PubMed

Fahrig, Rebecca; Dixon, Robert; Payne, Thomas; Morin, Richard L; Ganguly, Arundhuti; Strobel, Norbert

2006-12-01

We assess dose and image quality of a state-of-the-art angiographic C-arm system (Axiom Artis dTA, Siemens Medical Solutions, Forchheim, Germany) for three-dimensional neuro-imaging at various dose levels and tube voltages and an associated measurement method. Unlike conventional CT, the beam length covers the entire phantom, hence, the concept of computed tomography dose index (CTDI) is not the metric of choice, and one can revert to conventional dosimetry methods by directly measuring the dose at various points using a small ion chamber. This method allows us to define and compute a new dose metric that is appropriate for a direct comparison with the familiar CTDIw of conventional CT. A perception study involving the CATPHAN 600 indicates that one can expect to see at least the 9 mm inset with 0.5% nominal contrast at the recommended head-scan dose (60 mGy) when using tube voltages ranging from 70 kVp to 125 kVp. When analyzing the impact of tube voltage on image quality at a fixed dose, we found that lower tube voltages gave improved low contrast detectability for small-diameter objects. The relationships between kVp, image noise, dose, and contrast perception are discussed.

Region-of-interest image reconstruction in circular cone-beam microCT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cho, Seungryong; Bian, Junguo; Pelizzari, Charles A.

2007-12-15

Cone-beam microcomputed tomography (microCT) is one of the most popular choices for small animal imaging which is becoming an important tool for studying animal models with transplanted diseases. Region-of-interest (ROI) imaging techniques in CT, which can reconstruct an ROI image from the projection data set of the ROI, can be used not only for reducing imaging-radiation exposure to the subject and scatters to the detector but also for potentially increasing spatial resolution of the reconstructed images. Increasing spatial resolution in microCT images can facilitate improved accuracy in many assessment tasks. A method proposed previously for increasing CT image spatial resolutionmore » entails the exploitation of the geometric magnification in cone-beam CT. Due to finite detector size, however, this method can lead to data truncation for a large geometric magnification. The Feldkamp-Davis-Kress (FDK) algorithm yields images with artifacts when truncated data are used, whereas the recently developed backprojection filtration (BPF) algorithm is capable of reconstructing ROI images without truncation artifacts from truncated cone-beam data. We apply the BPF algorithm to reconstructing ROI images from truncated data of three different objects acquired by our circular cone-beam microCT system. Reconstructed images by use of the FDK and BPF algorithms from both truncated and nontruncated cone-beam data are compared. The results of the experimental studies demonstrate that, from certain truncated data, the BPF algorithm can reconstruct ROI images with quality comparable to that reconstructed from nontruncated data. In contrast, the FDK algorithm yields ROI images with truncation artifacts. Therefore, an implication of the studies is that, when truncated data are acquired with a configuration of a large geometric magnification, the BPF algorithm can be used for effective enhancement of the spatial resolution of a ROI image.« less

CT image reconstruction with half precision floating-point values.

PubMed

Maaß, Clemens; Baer, Matthias; Kachelrieß, Marc

2011-07-01

Analytic CT image reconstruction is a computationally demanding task. Currently, the even more demanding iterative reconstruction algorithms find their way into clinical routine because their image quality is superior to analytic image reconstruction. The authors thoroughly analyze a so far unconsidered but valuable tool of tomorrow's reconstruction hardware (CPU and GPU) that allows implementing the forward projection and backprojection steps, which are the computationally most demanding parts of any reconstruction algorithm, much more efficiently. Instead of the standard 32 bit floating-point values (float), a recently standardized floating-point value with 16 bit (half) is adopted for data representation in image domain and in rawdata domain. The reduction in the total data amount reduces the traffic on the memory bus, which is the bottleneck of today's high-performance algorithms, by 50%. In CT simulations and CT measurements, float reconstructions (gold standard) and half reconstructions are visually compared via difference images and by quantitative image quality evaluation. This is done for analytical reconstruction (filtered backprojection) and iterative reconstruction (ordered subset SART). The magnitude of quantization noise, which is caused by a reduction in the data precision of both rawdata and image data during image reconstruction, is negligible. This is clearly shown for filtered backprojection and iterative ordered subset SART reconstruction. In filtered backprojection, the implementation of the backprojection should be optimized for low data precision if the image data are represented in half format. In ordered subset SART image reconstruction, no adaptations are necessary and the convergence speed remains unchanged. Half precision floating-point values allow to speed up CT image reconstruction without compromising image quality.

Disease quantification on PET/CT images without object delineation

NASA Astrophysics Data System (ADS)

Tong, Yubing; Udupa, Jayaram K.; Odhner, Dewey; Wu, Caiyun; Fitzpatrick, Danielle; Winchell, Nicole; Schuster, Stephen J.; Torigian, Drew A.

2017-03-01

The derivation of quantitative information from images to make quantitative radiology (QR) clinically practical continues to face a major image analysis hurdle because of image segmentation challenges. This paper presents a novel approach to disease quantification (DQ) via positron emission tomography/computed tomography (PET/CT) images that explores how to decouple DQ methods from explicit dependence on object segmentation through the use of only object recognition results to quantify disease burden. The concept of an object-dependent disease map is introduced to express disease severity without performing explicit delineation and partial volume correction of either objects or lesions. The parameters of the disease map are estimated from a set of training image data sets. The idea is illustrated on 20 lung lesions and 20 liver lesions derived from 18F-2-fluoro-2-deoxy-D-glucose (FDG)-PET/CT scans of patients with various types of cancers and also on 20 NEMA PET/CT phantom data sets. Our preliminary results show that, on phantom data sets, "disease burden" can be estimated to within 2% of known absolute true activity. Notwithstanding the difficulty in establishing true quantification on patient PET images, our results achieve 8% deviation from "true" estimates, with slightly larger deviations for small and diffuse lesions where establishing ground truth becomes really questionable, and smaller deviations for larger lesions where ground truth set up becomes more reliable. We are currently exploring extensions of the approach to include fully automated body-wide DQ, extensions to just CT or magnetic resonance imaging (MRI) alone, to PET/CT performed with radiotracers other than FDG, and other functional forms of disease maps.

Registration of multiple video images to preoperative CT for image-guided surgery

NASA Astrophysics Data System (ADS)

Clarkson, Matthew J.; Rueckert, Daniel; Hill, Derek L.; Hawkes, David J.

1999-05-01

In this paper we propose a method which uses multiple video images to establish the pose of a CT volume with respect to video camera coordinates for use in image guided surgery. The majority of neurosurgical procedures require the neurosurgeon to relate the pre-operative MR/CT data to the intra-operative scene. Registration of 2D video images to the pre-operative 3D image enables a perspective projection of the pre-operative data to be overlaid onto the video image. Our registration method is based on image intensity and uses a simple iterative optimization scheme to maximize the mutual information between a video image and a rendering from the pre-operative data. Video images are obtained from a stereo operating microscope, with a field of view of approximately 110 X 80 mm. We have extended an existing information theoretical framework for 2D-3D registration, so that multiple video images can be registered simultaneously to the pre-operative data. Experiments were performed on video and CT images of a skull phantom. We took three video images, and our algorithm registered these individually to the 3D image. The mean projection error varied between 4.33 and 9.81 millimeters (mm), and the mean 3D error varied between 4.47 and 11.92 mm. Using our novel techniques we then registered five video views simultaneously to the 3D model. This produced an accurate and robust registration with a mean projection error of 0.68 mm and a mean 3D error of 1.05 mm.

Comparison of helical and cine acquisitions for 4D-CT imaging with multislice CT.

PubMed

Pan, Tinsu

2005-02-01

We proposed a data sufficiency condition (DSC) for four-dimensional-CT (4D-CT) imaging on a multislice CT scanner, designed a pitch factor for a helical 4D-CT, and compared the acquisition time, slice sensitivity profile (SSP), effective dose, ability to cope with an irregular breathing cycle, and gating technique (retrospective or prospective) of the helical 4D-CT and the cine 4D-CT on the General Electric (GE) LightSpeed RT (4-slice), Plus (4-slice), Ultra (8-slice) and 16 (16-slice) multislice CT scanners. To satisfy the DSC, a helical or cine 4D-CT acquisition has to collect data at each location for the duration of a breathing cycle plus the duration of data acquisition for an image reconstruction. The conditions for the comparison were 20 cm coverage in the cranial-caudal direction, a 4 s breathing cycle, and half-scan reconstruction. We found that the helical 4D-CT has the advantage of a shorter scan time that is 10% shorter than that of the cine 4D-CT, and the disadvantages of 1.8 times broadening of SSP and requires an additional breathing cycle of scanning to ensure an adequate sampling at the start and end locations. The cine 4D-CT has the advantages of maintaining the same SSP as slice collimation (e.g., 8 x 2.5 mm slice collimation generates 2.5 mm SSP in the cine 4D-CT as opposed to 4.5 mm in the helical 4D-CT) and a lower dose by 4% on the 8- and 16-slice systems, and 8% on the 4-slice system. The advantage of faster scanning in the helical 4D-CT will diminish if a repeat scan at the location of a breathing irregularity becomes necessary. The cine 4D-CT performs better than the helical 4D-CT in the repeat scan because it can scan faster and is more dose efficient.

Evaluation of the low dose cardiac CT imaging using ASIR technique

NASA Astrophysics Data System (ADS)

Fan, Jiahua; Hsieh, Jiang; Deubig, Amy; Sainath, Paavana; Crandall, Peter

2010-04-01

Today Cardiac imaging is one of the key driving forces for the research and development activities of Computed Tomography (CT) imaging. It requires high spatial and temporal resolution and is often associated with high radiation dose. The newly introduced ASIR technique presents an efficient method that offers the dose reduction benefits while maintaining image quality and providing fast reconstruction speed. This paper discusses the study of image quality of the ASIR technique for Cardiac CT imaging. Phantoms as well as clinical data have been evaluated to demonstrate the effectiveness of ASIR technique for Cardiac CT applications.

Periosteal ganglia: CT and MR imaging features.

PubMed

Abdelwahab, I F; Kenan, S; Hermann, G; Klein, M J; Lewis, M M

1993-07-01

The imaging features of four cases of periosteal ganglia were studied. Three lesions were located over the proximal shaft of the tibia, in proximity to the pes anserinus. The fourth lesion involved the distal shaft of the ulna. Three lesions had different degrees of external cortical erosion, scalloping, and thick spicules of periosteal bone on plain radiographs. The bone adjacent to the fourth lesion was not involved. Computed tomography (CT) showed these lesions to be sharply defined soft-tissue masses abutting the periosteum. All of the lesions had the same attenuation as fluid. Magnetic resonance (MR) imaging revealed the ganglia to be sharply defined masses that were isointense compared with neighboring muscles on T1-weighted images. There was markedly increased signal intensity compared with that of fat on T2-weighted images. The signal intensity on both types of images was homogeneous. The MR imaging features were consistent with the fluid nature of the lesions. Under the appropriate clinical circumstances, the MR imaging and CT features of periosteal ganglia are diagnostic.

Live minimal path for interactive segmentation of medical images

NASA Astrophysics Data System (ADS)

Chartrand, Gabriel; Tang, An; Chav, Ramnada; Cresson, Thierry; Chantrel, Steeve; De Guise, Jacques A.

2015-03-01

Medical image segmentation is nowadays required for medical device development and in a growing number of clinical and research applications. Since dedicated automatic segmentation methods are not always available, generic and efficient interactive tools can alleviate the burden of manual segmentation. In this paper we propose an interactive segmentation tool based on image warping and minimal path segmentation that is efficient for a wide variety of segmentation tasks. While the user roughly delineates the desired organs boundary, a narrow band along the cursors path is straightened, providing an ideal subspace for feature aligned filtering and minimal path algorithm. Once the segmentation is performed on the narrow band, the path is warped back onto the original image, precisely delineating the desired structure. This tool was found to have a highly intuitive dynamic behavior. It is especially efficient against misleading edges and required only coarse interaction from the user to achieve good precision. The proposed segmentation method was tested for 10 difficult liver segmentations on CT and MRI images, and the resulting 2D overlap Dice coefficient was 99% on average..

A 4D global respiratory motion model of the thorax based on CT images: A proof of concept.

PubMed

Fayad, Hadi; Gilles, Marlene; Pan, Tinsu; Visvikis, Dimitris

2018-05-17

Respiratory motion reduces the sensitivity and specificity of medical images especially in the thoracic and abdominal areas. It may affect applications such as cancer diagnostic imaging and/or radiation therapy (RT). Solutions to this issue include modeling of the respiratory motion in order to optimize both diagnostic and therapeutic protocols. Personalized motion modeling required patient-specific four-dimensional (4D) imaging which in the case of 4D computed tomography (4D CT) acquisition is associated with an increased dose. The goal of this work was to develop a global respiratory motion model capable of relating external patient surface motion to internal structure motion without the need for a patient-specific 4D CT acquisition. The proposed global model is based on principal component analysis and can be adjusted to a given patient anatomy using only one or two static CT images in conjunction with a respiratory synchronized patient external surface motion. It is based on the relation between the internal motion described using deformation fields obtained by registering 4D CT images and patient surface maps obtained either from optical imaging devices or extracted from CT image-based patient skin segmentation. 4D CT images of six patients were used to generate the global motion model which was validated by adapting it on four different patients having skin segmented surfaces and two other patients having time of flight camera acquired surfaces. The reproducibility of the proposed model was also assessed on two patients with two 4D CT series acquired within 2 weeks of each other. Profile comparison shows the efficacy of the global respiratory motion model and an improvement while using two CT images in order to adapt the model. This was confirmed by the correlation coefficient with a mean correlation of 0.9 and 0.95 while using one or two CT images respectively and when comparing acquired to model generated 4D CT images. For the four patients with segmented

Automatic anatomy recognition on CT images with pathology

NASA Astrophysics Data System (ADS)

Huang, Lidong; Udupa, Jayaram K.; Tong, Yubing; Odhner, Dewey; Torigian, Drew A.

2016-03-01

Body-wide anatomy recognition on CT images with pathology becomes crucial for quantifying body-wide disease burden. This, however, is a challenging problem because various diseases result in various abnormalities of objects such as shape and intensity patterns. We previously developed an automatic anatomy recognition (AAR) system [1] whose applicability was demonstrated on near normal diagnostic CT images in different body regions on 35 organs. The aim of this paper is to investigate strategies for adapting the previous AAR system to diagnostic CT images of patients with various pathologies as a first step toward automated body-wide disease quantification. The AAR approach consists of three main steps - model building, object recognition, and object delineation. In this paper, within the broader AAR framework, we describe a new strategy for object recognition to handle abnormal images. In the model building stage an optimal threshold interval is learned from near-normal training images for each object. This threshold is optimally tuned to the pathological manifestation of the object in the test image. Recognition is performed following a hierarchical representation of the objects. Experimental results for the abdominal body region based on 50 near-normal images used for model building and 20 abnormal images used for object recognition show that object localization accuracy within 2 voxels for liver and spleen and 3 voxels for kidney can be achieved with the new strategy.

Quantitation of clinical feedback on image quality differences between two CT scanner models.

PubMed

Bache, Steven T; Stauduhar, Paul J; Liu, Xinming; Loyer, Evelyne M; John, Rong X

2017-03-01

The aim of this work was to quantitate differences in image quality between two GE CT scanner models - the LightSpeed VCT ("VCT") and Discovery HD750 ("HD") - based upon feedback from radiologists at our institution. First, 3 yrs of daily QC images of the manufacturer-provided QC phantom from 10 scanners - five of each model - were analyzed for both noise magnitude, measured as CT-number standard deviation, and noise power spectrum within the uniform water section. The same phantom was then scanned on four of each model and analyzed for low contrast detectability (LCD) using a built-in LCD tool at the scanner console. An anthropomorphic phantom was scanned using the same eight scanners. A slice within the abdomen section was chosen and three ROIs were placed in regions representing liver, stomach, and spleen. Both standard deviation of CT-number and LCD value was calculated for each image. Noise magnitude was 8.5% higher in HD scanners compared to VCT scanners. An associated increase in the magnitude of the noise power spectra were also found, but both peak and mean NPS frequency were not different between the two models. VCT scanners outperformed HD scanners with respect to LCD by an average of 13.1% across all scanners and phantoms. Our results agree with radiologist feedback, and necessitate a closer look at our body CT protocols among different scanner models at our institution. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Multi-energy spectral CT: adding value in emergency body imaging.

PubMed

Punjabi, Gopal V

2018-04-01

Most vendors offer scanners capable of dual- or multi-energy computed tomography (CT) imaging. Advantages of multi-energy CT scanning include superior tissue characterization, detection of subtle iodine uptake differences, and opportunities to reduce contrast dose. However, utilization of this technology in the emergency department (ED) remains low. The purpose of this pictorial essay is to illustrate the value of multi-energy CT scanning in emergency body imaging.

A software tool for automatic classification and segmentation of 2D/3D medical images

NASA Astrophysics Data System (ADS)

Strzelecki, Michal; Szczypinski, Piotr; Materka, Andrzej; Klepaczko, Artur

2013-02-01

Modern medical diagnosis utilizes techniques of visualization of human internal organs (CT, MRI) or of its metabolism (PET). However, evaluation of acquired images made by human experts is usually subjective and qualitative only. Quantitative analysis of MR data, including tissue classification and segmentation, is necessary to perform e.g. attenuation compensation, motion detection, and correction of partial volume effect in PET images, acquired with PET/MR scanners. This article presents briefly a MaZda software package, which supports 2D and 3D medical image analysis aiming at quantification of image texture. MaZda implements procedures for evaluation, selection and extraction of highly discriminative texture attributes combined with various classification, visualization and segmentation tools. Examples of MaZda application in medical studies are also provided.

Evaluation of portable CT scanners for otologic image-guided surgery

PubMed Central

Balachandran, Ramya; Schurzig, Daniel; Fitzpatrick, J Michael; Labadie, Robert F

2011-01-01

Purpose Portable CT scanners are beneficial for diagnosis in the intensive care unit, emergency room, and operating room. Portable fixed-base versus translating-base CT systems were evaluated for otologic image-guided surgical (IGS) applications based on geometric accuracy and utility for percutaneous cochlear implantation. Methods Five cadaveric skulls were fitted with fiducial markers and scanned using both a translating-base, 8-slice CT scanner (CereTom®) and a fixed-base, flat-panel, volume-CT (fpVCT) scanner (Xoran xCAT®). Images were analyzed for: (a) subjective quality (i.e. noise), (b) consistency of attenuation measurements (Hounsfield units) across similar tissue, and (c) geometric accuracy of fiducial marker positions. The utility of these scanners in clinical IGS cases was tested. Results Five cadaveric specimens were scanned using each of the scanners. The translating-base, 8-slice CT scanner had spatially consistent Hounsfield units, and the image quality was subjectively good. However, because of movement variations during scanning, the geometric accuracy of fiducial marker positions was low. The fixed-base, fpVCT system had high spatial resolution, but the images were noisy and had spatially inconsistent attenuation measurements; while the geometric representation of the fiducial markers was highly accurate. Conclusion Two types of portable CT scanners were evaluated for otologic IGS. The translating-base, 8-slice CT scanner provided better image quality than a fixed-base, fpVCT scanner. However, the inherent error in three-dimensional spatial relationships by the translating-based system makes it suboptimal for otologic IGS use. PMID:21779768

A review of GPU-based medical image reconstruction.

PubMed

Després, Philippe; Jia, Xun

2017-10-01

Tomographic image reconstruction is a computationally demanding task, even more so when advanced models are used to describe a more complete and accurate picture of the image formation process. Such advanced modeling and reconstruction algorithms can lead to better images, often with less dose, but at the price of long calculation times that are hardly compatible with clinical workflows. Fortunately, reconstruction tasks can often be executed advantageously on Graphics Processing Units (GPUs), which are exploited as massively parallel computational engines. This review paper focuses on recent developments made in GPU-based medical image reconstruction, from a CT, PET, SPECT, MRI and US perspective. Strategies and approaches to get the most out of GPUs in image reconstruction are presented as well as innovative applications arising from an increased computing capacity. The future of GPU-based image reconstruction is also envisioned, based on current trends in high-performance computing. Copyright © 2017 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Hounsfield unit recovery in clinical cone beam CT images of the thorax acquired for image guided radiation therapy

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.

Imaging of acute mesenteric ischemia using multidetector CT and CT angiography in a porcine model.

PubMed

Rosow, David E; Sahani, Dushyant; Strobel, Oliver; Kalva, Sanjeeva; Mino-Kenudson, Mari; Holalkere, Nagaraj S; Alsfasser, Guido; Saini, Sanjay; Lee, Susanna I; Mueller, Peter R; Fernández-del Castillo, Carlos; Warshaw, Andrew L; Thayer, Sarah P

2005-12-01

Acute mesenteric ischemia, a frequently lethal disease, requires prompt diagnosis and intervention for favorable clinical outcomes. This goal remains elusive due, in part, to lack of a noninvasive and accurate imaging study. Traditional angiography is the diagnostic gold standard but is invasive and costly. Computed tomography (CT) is readily available and noninvasive but has shown variable success in diagnosing this disease. The faster scanning time of multidetector row CT (M.D.CT) greatly facilitates the use of CT angiography (CTA) in the clinical setting. We sought to determine whether M.D.CT-CTA could accurately demonstrate vascular anatomy and capture the earliest stages of mesenteric ischemia in a porcine model. Pigs underwent embolization of branches of the superior mesenteric artery, then imaging by M.D.CT-CTA with three-dimensional reconstruction protocols. After scanning, diseased bowel segments were surgically resected and pathologically examined. Multidetector row CT and CT angiography reliably defined normal and occluded mesenteric vessels in the pig. It detected early changes of ischemia including poor arterial enhancement and venous dilatation, which were seen in all ischemic animals. The radiographic findings--compared with pathologic diagnoses-- predicted ischemia, with a positive predictive value of 92%. These results indicate that M.D.CT-CTA holds great promise for the early detection necessary for successful treatment of acute mesenteric ischemia.

SU-E-I-23: Design and Clinical Application of External Marking Body in Multi- Mode Medical Images Registration and Fusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Z; Gong, G

2014-06-01

Purpose: To design an external marking body (EMB) that could be visible on computed tomography (CT), magnetic resonance (MR), positron emission tomography (PET) and single-photon emission computed tomography (SPECT) images and to investigate the use of the EMB for multiple medical images registration and fusion in the clinic. Methods: We generated a solution containing paramagnetic metal ions and iodide ions (CT'MR dual-visible solution) that could be viewed on CT and MR images and multi-mode image visible solution (MIVS) that could be obtained by mixing radioactive nuclear material. A globular plastic theca (diameter: 3–6 mm) that mothball the MIVS and themore » EMB was brought by filling MIVS. The EMBs were fixed on the patient surface and CT, MR, PET and SPECT scans were obtained. The feasibility of clinical application and the display and registration error of EMB among different image modalities were investigated. Results: The dual-visible solution was highly dense on CT images (HU>700). A high signal was also found in all MR scanning (T1, T2, STIR and FLAIR) images, and the signal was higher than subcutaneous fat. EMB with radioactive nuclear material caused a radionuclide concentration area on PET and SPECT images, and the signal of EMB was similar to or higher than tumor signals. The theca with MIVS was clearly visible on all the images without artifact, and the shape was round or oval with a sharp edge. The maximum diameter display error was 0.3 ± 0.2mm on CT and MRI images, and 1.0 ± 0.3mm on PET and SPECT images. In addition, the registration accuracy of the theca center among multi-mode images was less than 1mm. Conclusion: The application of EMB with MIVS improves the registration and fusion accuracy of multi-mode medical images. Furthermore, it has the potential to ameliorate disease diagnosis and treatment outcome.« less

CT, MRI and PET imaging in peritoneal malignancy

PubMed Central

Sahdev, Anju; Reznek, Rodney H.

2011-01-01

Abstract Imaging plays a vital role in the evaluation of patients with suspected or proven peritoneal malignancy. Nevertheless, despite significant advances in imaging technology and protocols, assessment of peritoneal pathology remains challenging. The combination of complex peritoneal anatomy, an extensive surface area that may host tumour deposits and the considerable overlap of imaging appearances of various peritoneal diseases often makes interpretation difficult. Contrast-enhanced multidetector computed tomography (MDCT) remains the most versatile tool in the imaging of peritoneal malignancy. However, conventional and emerging magnetic resonance imaging (MRI) and positron emission tomography (PET)/CT techniques offer significant advantages over MDCT in detection and surveillance. This article reviews established and new techniques in CT, MRI and PET imaging in both primary and secondary peritoneal malignancies and provides an overview of peritoneal anatomy, function and modes of disease dissemination with illustration of common sites and imaging features of peritoneal malignancy. PMID:21865109

A denoising algorithm for CT image using low-rank sparse coding

NASA Astrophysics Data System (ADS)

Lei, Yang; Xu, Dong; Zhou, Zhengyang; Wang, Tonghe; Dong, Xue; Liu, Tian; Dhabaan, Anees; Curran, Walter J.; Yang, Xiaofeng

2018-03-01

We propose a denoising method of CT image based on low-rank sparse coding. The proposed method constructs an adaptive dictionary of image patches and estimates the sparse coding regularization parameters using the Bayesian interpretation. A low-rank approximation approach is used to simultaneously construct the dictionary and achieve sparse representation through clustering similar image patches. A variable-splitting scheme and a quadratic optimization are used to reconstruct CT image based on achieved sparse coefficients. We tested this denoising technology using phantom, brain and abdominal CT images. The experimental results showed that the proposed method delivers state-of-art denoising performance, both in terms of objective criteria and visual quality.

Multi-layer cube sampling for liver boundary detection in PET-CT images.

PubMed

Liu, Xinxin; Yang, Jian; Song, Shuang; Song, Hong; Ai, Danni; Zhu, Jianjun; Jiang, Yurong; Wang, Yongtian

2018-06-01

Liver metabolic information is considered as a crucial diagnostic marker for the diagnosis of fever of unknown origin, and liver recognition is the basis of automatic diagnosis of metabolic information extraction. However, the poor quality of PET and CT images is a challenge for information extraction and target recognition in PET-CT images. The existing detection method cannot meet the requirement of liver recognition in PET-CT images, which is the key problem in the big data analysis of PET-CT images. A novel texture feature descriptor called multi-layer cube sampling (MLCS) is developed for liver boundary detection in low-dose CT and PET images. The cube sampling feature is proposed for extracting more texture information, which uses a bi-centric voxel strategy. Neighbour voxels are divided into three regions by the centre voxel and the reference voxel in the histogram, and the voxel distribution information is statistically classified as texture feature. Multi-layer texture features are also used to improve the ability and adaptability of target recognition in volume data. The proposed feature is tested on the PET and CT images for liver boundary detection. For the liver in the volume data, mean detection rate (DR) and mean error rate (ER) reached 95.15 and 7.81% in low-quality PET images, and 83.10 and 21.08% in low-contrast CT images. The experimental results demonstrated that the proposed method is effective and robust for liver boundary detection.

Utility of Intermediate-Delay Washout CT Images for Differentiation of Malignant and Benign Adrenal Lesions: A Multivariate Analysis.

PubMed

Ng, Chaan S; Altinmakas, Emre; Wei, Wei; Ghosh, Payel; Li, Xiao; Grubbs, Elizabeth G; Perrier, Nancy D; Lee, Jeffrey E; Prieto, Victor G; Hobbs, Brian P

2018-06-27

The objective of this study was to identify features that impact the diagnostic performance of intermediate-delay washout CT for distinguishing malignant from benign adrenal lesions. This retrospective study evaluated 127 pathologically proven adrenal lesions (82 malignant, 45 benign) in 126 patients who had undergone portal venous phase and intermediate-delay washout CT (1-3 minutes after portal venous phase) with or without unenhanced images. Unenhanced images were available for 103 lesions. Quantitatively, lesion CT attenuation on unenhanced (UA) and delayed (DL) images, absolute and relative percentage of enhancement washout (APEW and RPEW, respectively), descriptive CT features (lesion size, margin characteristics, heterogeneity or homogeneity, fat, calcification), patient demographics, and medical history were evaluated for association with lesion status using multiple logistic regression with stepwise model selection. Area under the ROC curve (A z ) was calculated from both univariate and multivariate analyses. The predictive diagnostic performance of multivariate evaluations was ascertained through cross-validation. A z for DL, APEW, RPEW, and UA was 0.751, 0.795, 0.829, and 0.839, respectively. Multivariate analyses yielded the following significant CT quantitative features and associated A z when combined: RPEW and DL (A z = 0.861) when unenhanced images were not available and APEW and UA (A z = 0.889) when unenhanced images were available. Patient demographics and presence of a prior malignancy were additional significant factors, increasing A z to 0.903 and 0.927, respectively. The combined predictive classifier, without and with UA available, yielded 85.7% and 87.3% accuracies with cross-validation, respectively. When appropriately combined with other CT features, washout derived from intermediate-delay CT with or without additional clinical data has potential utility in differentiating malignant from benign adrenal lesions.

Texture-preserved penalized weighted least-squares reconstruction of low-dose CT image via image segmentation and high-order MRF modeling

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.

Digital management and regulatory submission of medical images from clinical trials: role and benefits of the core laboratory

NASA Astrophysics Data System (ADS)

Robbins, William L.; Conklin, James J.

1995-10-01

Medical images (angiography, CT, MRI, nuclear medicine, ultrasound, x ray) play an increasingly important role in the clinical development and regulatory review process for pharmaceuticals and medical devices. Since medical images are increasingly acquired and archived digitally, or are readily digitized from film, they can be visualized, processed and analyzed in a variety of ways using digital image processing and display technology. Moreover, with image-based data management and data visualization tools, medical images can be electronically organized and submitted to the U.S. Food and Drug Administration (FDA) for review. The collection, processing, analysis, archival, and submission of medical images in a digital format versus an analog (film-based) format presents both challenges and opportunities for the clinical and regulatory information management specialist. The medical imaging 'core laboratory' is an important resource for clinical trials and regulatory submissions involving medical imaging data. Use of digital imaging technology within a core laboratory can increase efficiency and decrease overall costs in the image data management and regulatory review process.

A QR Code Based Zero-Watermarking Scheme for Authentication of Medical Images in Teleradiology Cloud

PubMed Central

Seenivasagam, V.; Velumani, R.

2013-01-01

Healthcare institutions adapt cloud based archiving of medical images and patient records to share them efficiently. Controlled access to these records and authentication of images must be enforced to mitigate fraudulent activities and medical errors. This paper presents a zero-watermarking scheme implemented in the composite Contourlet Transform (CT)—Singular Value Decomposition (SVD) domain for unambiguous authentication of medical images. Further, a framework is proposed for accessing patient records based on the watermarking scheme. The patient identification details and a link to patient data encoded into a Quick Response (QR) code serves as the watermark. In the proposed scheme, the medical image is not subjected to degradations due to watermarking. Patient authentication and authorized access to patient data are realized on combining a Secret Share with the Master Share constructed from invariant features of the medical image. The Hu's invariant image moments are exploited in creating the Master Share. The proposed system is evaluated with Checkmark software and is found to be robust to both geometric and non geometric attacks. PMID:23970943

A QR code based zero-watermarking scheme for authentication of medical images in teleradiology cloud.

PubMed

Seenivasagam, V; Velumani, R

2013-01-01

Healthcare institutions adapt cloud based archiving of medical images and patient records to share them efficiently. Controlled access to these records and authentication of images must be enforced to mitigate fraudulent activities and medical errors. This paper presents a zero-watermarking scheme implemented in the composite Contourlet Transform (CT)-Singular Value Decomposition (SVD) domain for unambiguous authentication of medical images. Further, a framework is proposed for accessing patient records based on the watermarking scheme. The patient identification details and a link to patient data encoded into a Quick Response (QR) code serves as the watermark. In the proposed scheme, the medical image is not subjected to degradations due to watermarking. Patient authentication and authorized access to patient data are realized on combining a Secret Share with the Master Share constructed from invariant features of the medical image. The Hu's invariant image moments are exploited in creating the Master Share. The proposed system is evaluated with Checkmark software and is found to be robust to both geometric and non geometric attacks.

High dose microCT does not contribute towards improved microPET/CT image quantitative accuracy and can limit longitudinal scanning of small animals

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.

A combined learning algorithm for prostate segmentation on 3D CT images.

PubMed

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

The Role of 18F-FDG PET/CT Integrated Imaging in Distinguishing Malignant from Benign Pleural Effusion.

PubMed

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

The Role of 18F-FDG PET/CT Integrated Imaging in Distinguishing Malignant from Benign Pleural Effusion

PubMed Central

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

The role of pubic symphyseal CT arthrography in the imaging of athletic pubalgia.

PubMed

McArthur, Tatum A; Narducci, Carl A; Lopez-Ben, Robert R

2014-11-01

The purpose of this article is to describe the results of pubic symphyseal CT arthrography compared with MRI in patients with suspected athletic pubalgia. In this study, two musculoskeletal radiologists retrospectively searched our department's PACS to identify patients who had undergone CT-guided injection with concurrent pubic symphyseal CT arthrography for evaluation and treatment of groin pain, sports hernia, or athletic pubalgia over a 5.5-year period (January 1, 2007-July 1, 2012). The MR and CT arthrography images and reports, clinical findings at presentation, pain response to injection, and operative findings were reviewed using the electronic medical record. Twelve patients underwent CT-guided injection and pubic symphyseal CT arthrography at our institution during the 5.5-year study period. Nine of the 12 patients had undergone MRI before the procedure. In two of the three patients who had not undergone MRI, CT arthrography revealed secondary clefts. Three of four patients who had secondary clefts on MRI had contrast extravasation reproducing the cleft at CT. Three patients had MRI findings suggestive of athletic pubalgia without MRI evidence of a secondary cleft; in all three of these patients, CT arthrography showed a secondary cleft. In four patients, CT arthrography revealed tendon tears at the adductor origin that were not apparent on MRI. All 12 patients reported decreased groin pain after injection. Pubic symphyseal CT arthrography is a useful technique for the diagnosis and short-term pain relief of athletic pubalgia. It can be used to identify secondary clefts and to detect tendon tears that can potentially be overlooked on MRI.

Initial observations of electronic medical record usage during CT and MRI interpretation: Frequency of use and impact on workflow.

PubMed

Lin, Abraham; Harris, Mitchell; Zalis, Michael

2010-07-01

Electronic medical record (EMR) systems permit integration of contextual nonimaging EMR data into examination interpretation; however, the extra effort required to search and review these nonradiologic data are not well characterized. We assessed the gross frequency and pattern of EMR usage in the interpretation of diagnostic CT and MRI examinations. We defined nonradiologic EMR data as laboratory data, nonimaging specialty report, clinical note, and administrative data not available on PACS. For abdominal, neuroradiologic, and musculoskeletal CT and MRI, we prospectively recorded the time required for image analysis (including prior imaging studies and their reports), nonradiologic EMR use, and initial report drafting by fellows and staff in randomized sessions. We assessed EMR use as a fraction of work activity and according to technique, subspecialty, inpatient status, and radiologist experience. We observed 372 CT and MRI interpretations by 33 radiologists. For CT, radiologists used the EMR in 34% of abdominal, 57% of neuroradiologic, and 38% of musculoskeletal interpretations. For MRI, EMR was used in 73% of abdominal, 56% of neuroradiologic, and 33% of musculoskeletal interpretations. For CT, EMR usage comprised 18%, 14%, and 18% of diagnostic effort (image analysis plus EMR use) for abdominal, neuroradiologic, and musculoskeletal interpretations, respectively; for MRI, EMR usage comprised 21%, 16%, and 15% of diagnostic effort for abdominal, neuroradiologic, and musculoskeletal interpretations, respectively. Frequency of EMR use was significantly greater for neuroradiology CT and abdominal MRI (p < 0.05, Fisher's test). EMR usage was not consistently related to inpatient status for CT or radiologist experience. For CT and MRI interpretation, EMR usage is frequent and comprises a significant fraction of diagnostic effort.

TH-C-18A-06: Combined CT Image Quality and Radiation Dose Monitoring Program Based On Patient Data to Assess Consistency of Clinical Imaging Across Scanner Models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Christianson, O; Winslow, J; Samei, E

2014-06-15

Purpose: One of the principal challenges of clinical imaging is to achieve an ideal balance between image quality and radiation dose across multiple CT models. The number of scanners and protocols at large medical centers necessitates an automated quality assurance program to facilitate this objective. Therefore, the goal of this work was to implement an automated CT image quality and radiation dose monitoring program based on actual patient data and to use this program to assess consistency of protocols across CT scanner models. Methods: Patient CT scans are routed to a HIPPA compliant quality assurance server. CTDI, extracted using opticalmore » character recognition, and patient size, measured from the localizers, are used to calculate SSDE. A previously validated noise measurement algorithm determines the noise in uniform areas of the image across the scanned anatomy to generate a global noise level (GNL). Using this program, 2358 abdominopelvic scans acquired on three commercial CT scanners were analyzed. Median SSDE and GNL were compared across scanner models and trends in SSDE and GNL with patient size were used to determine the impact of differing automatic exposure control (AEC) algorithms. Results: There was a significant difference in both SSDE and GNL across scanner models (9–33% and 15–35% for SSDE and GNL, respectively). Adjusting all protocols to achieve the same image noise would reduce patient dose by 27–45% depending on scanner model. Additionally, differences in AEC methodologies across vendors resulted in disparate relationships of SSDE and GNL with patient size. Conclusion: The difference in noise across scanner models indicates that protocols are not optimally matched to achieve consistent image quality. Our results indicated substantial possibility for dose reduction while achieving more consistent image appearance. Finally, the difference in AEC methodologies suggests the need for size-specific CT protocols to minimize variability in

Correction of nonuniform attenuation and image fusion in SPECT imaging by means of separate X-ray CT.

PubMed

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

Radiotherapy treatment planning: benefits of CT-MR image registration and fusion in tumor volume delineation.

PubMed

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.

Why do commercial CT scanners still employ traditional, filtered back-projection for image reconstruction?

PubMed Central

Pan, Xiaochuan; Sidky, Emil Y; Vannier, Michael

2010-01-01

Despite major advances in x-ray sources, detector arrays, gantry mechanical design and especially computer performance, one component of computed tomography (CT) scanners has remained virtually constant for the past 25 years—the reconstruction algorithm. Fundamental advances have been made in the solution of inverse problems, especially tomographic reconstruction, but these works have not been translated into clinical and related practice. The reasons are not obvious and seldom discussed. This review seeks to examine the reasons for this discrepancy and provides recommendations on how it can be resolved. We take the example of field of compressive sensing (CS), summarizing this new area of research from the eyes of practical medical physicists and explaining the disconnection between theoretical and application-oriented research. Using a few issues specific to CT, which engineers have addressed in very specific ways, we try to distill the mathematical problem underlying each of these issues with the hope of demonstrating that there are interesting mathematical problems of general importance that can result from in depth analysis of specific issues. We then sketch some unconventional CT-imaging designs that have the potential to impact on CT applications, if the link between applied mathematicians and engineers/physicists were stronger. Finally, we close with some observations on how the link could be strengthened. There is, we believe, an important opportunity to rapidly improve the performance of CT and related tomographic imaging techniques by addressing these issues. PMID:20376330

Dual-energy CT and ceramic or titanium prostheses material reduce CT artifacts and provide superior image quality of total knee arthroplasty.

PubMed

Kasparek, Maximilian F; Töpker, Michael; Lazar, Mathias; Weber, Michael; Kasparek, Michael; Mang, Thomas; Apfaltrer, Paul; Kubista, Bernd; Windhager, Reinhard; Ringl, Helmut

2018-06-07

To evaluate the influence of different scan parameters for single-energy CT and dual-energy CT, as well as the impact of different material used in a TKA prosthesis on image quality and the extent of metal artifacts. Eight pairs of TKA prostheses from different vendors were examined in a phantom set-up. Each pair consisted of a conventional CoCr prosthesis and the corresponding anti-allergic prosthesis (full titanium, ceramic, or ceramic-coated) from the same vendor. Nine different (seven dual-energy CT and two single-energy CT) scan protocols with different characteristics were used to determine the most suitable CT protocol for TKA imaging. Quantitative image analysis included assessment of blooming artifacts (metal implants appear thicker on CT than they are, given as virtual growth in mm in this paper) and streak artifacts (thick dark lines around metal). Qualitative image analysis was used to investigate the bone-prosthesis interface. The full titanium prosthesis and full ceramic knee showed significantly fewer blooming artifacts compared to the standard CoCr prosthesis (mean virtual growth 0.6-2.2 mm compared to 2.9-4.6 mm, p < 0.001). Dual-energy CT protocols showed less blooming (range 3.3-3.8 mm) compared to single-energy protocols (4.6-5.5 mm). The full titanium and full ceramic prostheses showed significantly fewer streak artifacts (mean standard deviation 77-86 Hounsfield unit (HU)) compared to the standard CoCr prosthesis (277-334 HU, p < 0.001). All dual-energy CT protocols had fewer metal streak artifacts (215-296 HU compared to single-energy CT protocols (392-497 HU)). Full titanium and ceramic prostheses were ranked superior with regard to the image quality at the bone/prosthesis interface compared to a standard CoCr prosthesis, and all dual-energy CT protocols were ranked better than single-energy protocols. Dual-energy CT and ceramic or titanium prostheses reduce CT artifacts and provide superior image quality of total knee

Improving the imaging of calcifications in CT by histogram-based selective deblurring

NASA Astrophysics Data System (ADS)

Rollano-Hijarrubia, Empar; van der Meer, Frits; van der Lugt, Add; Weinans, Harrie; Vrooman, Henry; Vossepoel, Albert; Stokking, Rik

2005-04-01

Imaging of small high-density structures, such as calcifications, with computed tomography (CT) is limited by the spatial resolution of the system. Blur causes small calcifications to be imaged with lower contrast and overestimated volume, thereby hampering the analysis of vessels. The aim of this work is to reduce the blur of calcifications by applying three-dimensional (3D) deconvolution. Unfortunately, the high-frequency amplification of the deconvolution produces edge-related ring artifacts and enhances noise and original artifacts, which degrades the imaging of low-density structures. A method, referred to as Histogram-based Selective Deblurring (HiSD), was implemented to avoid these negative effects. HiSD uses the histogram information to generate a restored image in which the low-intensity voxel information of the observed image is combined with the high-intensity voxel information of the deconvolved image. To evaluate HiSD we scanned four in-vitro atherosclerotic plaques of carotid arteries with a multislice spiral CT and with a microfocus CT (μCT), used as reference. Restored images were generated from the observed images, and qualitatively and quantitatively compared with their corresponding μCT images. Transverse views and maximum-intensity projections of restored images show the decrease of blur of the calcifications in 3D. Measurements of the areas of 27 calcifications and total volumes of calcification of 4 plaques show that the overestimation of calcification was smaller for restored images (mean-error: 90% for area; 92% for volume) than for observed images (143%; 213%, respectively). The qualitative and quantitative analyses show that the imaging of calcifications in CT can be improved considerably by applying HiSD.

Validating and improving CT ventilation imaging by correlating with ventilation 4D-PET/CT using {sup 68}Ga-labeled nanoparticles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kipritidis, John, E-mail: john.kipritidis@sydney.edu.au; Keall, Paul J.; Siva, Shankar

Purpose: CT ventilation imaging is a novel functional lung imaging modality based on deformable image registration. The authors present the first validation study of CT ventilation using positron emission tomography with{sup 68}Ga-labeled nanoparticles (PET-Galligas). The authors quantify this agreement for different CT ventilation metrics and PET reconstruction parameters. Methods: PET-Galligas ventilation scans were acquired for 12 lung cancer patients using a four-dimensional (4D) PET/CT scanner. CT ventilation images were then produced by applying B-spline deformable image registration between the respiratory correlated phases of the 4D-CT. The authors test four ventilation metrics, two existing and two modified. The two existing metricsmore » model mechanical ventilation (alveolar air-flow) based on Hounsfield unit (HU) change (V{sub HU}) or Jacobian determinant of deformation (V{sub Jac}). The two modified metrics incorporate a voxel-wise tissue-density scaling (ρV{sub HU} and ρV{sub Jac}) and were hypothesized to better model the physiological ventilation. In order to assess the impact of PET image quality, comparisons were performed using both standard and respiratory-gated PET images with the former exhibiting better signal. Different median filtering kernels (σ{sub m} = 0 or 3 mm) were also applied to all images. As in previous studies, similarity metrics included the Spearman correlation coefficient r within the segmented lung volumes, and Dice coefficient d{sub 20} for the (0 − 20)th functional percentile volumes. Results: The best agreement between CT and PET ventilation was obtained comparing standard PET images to the density-scaled HU metric (ρV{sub HU}) with σ{sub m} = 3 mm. This leads to correlation values in the ranges 0.22 ⩽ r ⩽ 0.76 and 0.38 ⩽ d{sub 20} ⩽ 0.68, with r{sup ¯}=0.42±0.16 and d{sup ¯}{sub 20}=0.52±0.09 averaged over the 12 patients. Compared to Jacobian-based metrics, HU-based metrics lead to statistically

Simultaneous reconstruction of the activity image and registration of the CT image in TOF-PET

NASA Astrophysics Data System (ADS)

Rezaei, Ahmadreza; Michel, Christian; Casey, Michael E.; Nuyts, Johan

2016-02-01

Previously, maximum-likelihood methods have been proposed to jointly estimate the activity image and the attenuation image or the attenuation sinogram from time-of-flight (TOF) positron emission tomography (PET) data. In this contribution, we propose a method that addresses the possible alignment problem of the TOF-PET emission data and the computed tomography (CT) attenuation data, by combining reconstruction and registration. The method, called MLRR, iteratively reconstructs the activity image while registering the available CT-based attenuation image, so that the pair of activity and attenuation images maximise the likelihood of the TOF emission sinogram. The algorithm is slow to converge, but some acceleration could be achieved by using Nesterov’s momentum method and by applying a multi-resolution scheme for the non-rigid displacement estimation. The latter also helps to avoid local optima, although convergence to the global optimum cannot be guaranteed. The results are evaluated on 2D and 3D simulations as well as a respiratory gated clinical scan. Our experiments indicate that the proposed method is able to correct for possible misalignment of the CT-based attenuation image, and is therefore a very promising approach to suppressing attenuation artefacts in clinical PET/CT. When applied to respiratory gated data of a patient scan, it produced deformations that are compatible with breathing motion and which reduced the well known attenuation artefact near the dome of the liver. Since the method makes use of the energy-converted CT attenuation image, the scale problem of joint reconstruction is automatically solved.

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

Biopsy of CT-Occult Bone Lesions Using Anatomic Landmarks for CT Guidance.

PubMed

Hillen, Travis J; Talbert, Robert J; Friedman, Michael V; Long, Jeremiah R; Jennings, Jack W; Wessell, Daniel E; Baker, Jonathan C

2017-07-01

The purpose of this study is to evaluate the histopathologic diagnostic yield, sample size, procedural time, and dose-length product (DLP) for the biopsy of CT-occult lesions found at MRI or PET or both. A retrospective review of our radiology information system for biopsies of CT-occult lesions using CT guidance from January 1, 2010, through December 31, 2014, was performed and compared with a selection of CT-guided biopsies of CT-evident bone lesions during the same period. The data were then evaluated for diagnostic yield of histopathologic diagnosis, procedural time, use of sedation medication, DLP, and size of specimens obtained. A total of 30 CT-occult biopsies met the inclusion criteria. Twenty-seven of those biopsies had results that were concordant with the patient's primary histopathologic diagnosis, imaging findings, and clinical course. In the CT-evident lesion group, concordant histopathologic abnormalities were identified in 27 of 30 patients. There was a statistically significant increase in number of samples obtained for the CT-evident lesions compared with CT-occult lesions. There was no statistically significant difference in total specimen length, DLP, number of CT scans, procedural time, or use of sedation medication between the CT-occult and CT-evident biopsy groups. Biopsy of CT-occult lesions using anatomic landmarks achieves diagnostic yields similar to those for CT-guided biopsy of CT-evident lesions.

Tailoring protocols for chest CT applications: when and how?

PubMed Central

Iezzi, Roberto; Larici, Anna Rita; Franchi, Paola; Marano, Riccardo; Magarelli, Nicola; Posa, Alessandro; Merlino, Biagio; Manfredi, Riccardo; Colosimo, Cesare

2017-01-01

In the medical era of early detection of diseases and tailored therapies, an accurate characterization and staging of the disease is pivotal for treatment planning. The widespread use of computed tomography (CT)—often with the use of contrast material (CM)—probably represents the most important advance in diagnostic radiology. The result is a marked increase in radiation exposure of the population for medical purposes, with its intrinsic carcinogenic potential, and CM affecting kidney function. The radiologists should aim to minimize patient’s risk by reducing radiation exposure and CM amount, while maintaining the highest image quality. To achieve this goal, it is necessary to perform “patient-centric imaging”. The purpose of this review is to provide radiologists with “tips and tricks” to control radiation dose at CT, summarizing technical artifices in order to reduce image noise and increase image contrast. Also chest CT tailored protocols are supplied, with particular attention to three most common thoracic CT protocols: aortic/cardiac CT angiography (CTA), pulmonary CTA, and routine chest CT. PMID:29097345

Three-dimensional CT enterography using oral gastrografin in patients with small bowel obstruction: comparison with axial CT images or fluoroscopic findings.

PubMed

Hong, Seong Sook; Kim, Ah Young; Kwon, Seok Beom; Kim, Pyo Nyun; Lee, Moon-Gyu; Ha, Hyun Kwon

2010-10-01

To evaluate the feasibility of 3D CT enterography using oral gastrografin in patients with small bowel obstruction (SBO), focusing on improving diagnostic performance as compared with the use of axial CT imagings and fluoroscopic findings. For a 10-month period, 18 patients with known SBO detected clinically and radiologically were enrolled. In all patients, gastrografin was ingested prior to CT enterography. Twelve patients underwent a fluoroscopic examination. Images were randomly assessed for confidence for the level, for the cause of SBO, and for the assessment of the interpretability of each image by two gastrointestinal radiologists. The results were considered statistically significant using the Wilcoxon rank sum test. All patients (100%) well tolerated the administration of oral gastrografin. The use of 3D CT enterography significantly improved diagnostic confidence for the interpretation of the level, cause of SBO, and the assessment of the interpretability of each image as compared with the use of axial CT images (P < 0.05). 3D CT enterography was superior as compared to fluoroscopic examination (P < 0.05). The use of gastrografin for 3D CT enterography is a safe and feasible technique for precise evaluation of known or suspected SBO.

Automated extraction of radiation dose information from CT dose report images.

PubMed

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.

Automated movement correction for dynamic PET/CT images: evaluation with phantom and patient data.

PubMed

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

PubMed Central

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

Anomaly detection for medical images based on a one-class classification

NASA Astrophysics Data System (ADS)

Wei, Qi; Ren, Yinhao; Hou, Rui; Shi, Bibo; Lo, Joseph Y.; Carin, Lawrence

2018-02-01

Detecting an anomaly such as a malignant tumor or a nodule from medical images including mammogram, CT or PET images is still an ongoing research problem drawing a lot of attention with applications in medical diagnosis. A conventional way to address this is to learn a discriminative model using training datasets of negative and positive samples. The learned model can be used to classify a testing sample into a positive or negative class. However, in medical applications, the high unbalance between negative and positive samples poses a difficulty for learning algorithms, as they will be biased towards the majority group, i.e., the negative one. To address this imbalanced data issue as well as leverage the huge amount of negative samples, i.e., normal medical images, we propose to learn an unsupervised model to characterize the negative class. To make the learned model more flexible and extendable for medical images of different scales, we have designed an autoencoder based on a deep neural network to characterize the negative patches decomposed from large medical images. A testing image is decomposed into patches and then fed into the learned autoencoder to reconstruct these patches themselves. The reconstruction error of one patch is used to classify this patch into a binary class, i.e., a positive or a negative one, leading to a one-class classifier. The positive patches highlight the suspicious areas containing anomalies in a large medical image. The proposed method has been tested on InBreast dataset and achieves an AUC of 0.84. The main contribution of our work can be summarized as follows. 1) The proposed one-class learning requires only data from one class, i.e., the negative data; 2) The patch-based learning makes the proposed method scalable to images of different sizes and helps avoid the large scale problem for medical images; 3) The training of the proposed deep convolutional neural network (DCNN) based auto-encoder is fast and stable.

A study on quantifying COPD severity by combining pulmonary function tests and CT image analysis

NASA Astrophysics Data System (ADS)

Nimura, Yukitaka; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku

2011-03-01

This paper describes a novel method that can evaluate chronic obstructive pulmonary disease (COPD) severity by combining measurements of pulmonary function tests and measurements obtained from CT image analysis. There is no cure for COPD. However, with regular medical care and consistent patient compliance with treatments and lifestyle changes, the symptoms of COPD can be minimized and progression of the disease can be slowed. Therefore, many diagnosis methods based on CT image analysis have been proposed for quantifying COPD. Most of diagnosis methods for COPD extract the lesions as low-attenuation areas (LAA) by thresholding and evaluate the COPD severity by calculating the LAA in the lung (LAA%). However, COPD is usually the result of a combination of two conditions, emphysema and chronic obstructive bronchitis. Therefore, the previous methods based on only LAA% do not work well. The proposed method utilizes both of information including the measurements of pulmonary function tests and the results of the chest CT image analysis to evaluate the COPD severity. In this paper, we utilize a multi-class AdaBoost to combine both of information and classify the COPD severity into five stages automatically. The experimental results revealed that the accuracy rate of the proposed method was 88.9% (resubstitution scheme) and 64.4% (leave-one-out scheme).

SU-F-J-114: On-Treatment Imagereconstruction Using Transit Images of Treatment Beams Through Patient and Thosethrough Planning CT Images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, H; Cho, S; Cheong, K

Purpose: To reconstruct patient images at the time of radiation delivery using measured transit images of treatment beams through patient and calculated transit images through planning CT images. Methods: We hypothesize that the ratio of the measured transit images to the calculated images may provide changed amounts of the patient image between times of planning CT and treatment. To test, we have devised lung phantoms with a tumor object (3-cm diameter) placed at iso-center (simulating planning CT) and off-center by 1 cm (simulating treatment). CT images of the two phantoms were acquired; the image of the off-centered phantom, unavailable clinically,more » represents the reference on-treatment image in the image quality of planning CT. Cine-transit images through the two phantoms were also acquired in EPID from a non-modulated 6 MV beam when the gantry was rotated 360 degrees; the image through the centered phantom simulates calculated image. While the current study is a feasibility study, in reality our computational EPID model can be applicable in providing accurate transit image from MC simulation. Changed MV HU values were reconstructed from the ratio between two EPID projection data, converted to KV HU values, and added to the planning CT, thereby reconstructing the on-treatment image of the patient limited to the irradiated region of the phantom. Results: The reconstructed image was compared with the reference image. Except for local HU differences>200 as a maximum, excellent agreement was found. The average difference across the entire image was 16.2 HU. Conclusion: We have demonstrated the feasibility of a method of reconstructing on-treatment images of a patient using EPID image and planning CT images. Further studies will include resolving the local HU differences and investigation on the dosimetry impact of the reconstructed image.« less

Advantages of semiconductor CZT for medical imaging

NASA Astrophysics Data System (ADS)

Wagenaar, Douglas J.; Parnham, Kevin; Sundal, Bjorn; Maehlum, Gunnar; Chowdhury, Samir; Meier, Dirk; Vandehei, Thor; Szawlowski, Marek; Patt, Bradley E.

2007-09-01

Cadmium zinc telluride (CdZnTe, or CZT) is a room-temperature semiconductor radiation detector that has been developed in recent years for a variety of applications. CZT has been investigated for many potential uses in medical imaging, especially in the field of single photon emission computed tomography (SPECT). CZT can also be used in positron emission tomography (PET) as well as photon-counting and integration-mode x-ray radiography and computed tomography (CT). The principal advantages of CZT are 1) direct conversion of x-ray or gamma-ray energy into electron-hole pairs; 2) energy resolution; 3) high spatial resolution and hence high space-bandwidth product; 4) room temperature operation, stable performance, high density, and small volume; 5) depth-of-interaction (DOI) available through signal processing. These advantages will be described in detail with examples from our own CZT systems. The ability to operate at room temperature, combined with DOI and very small pixels, make the use of multiple, stationary CZT "mini-gamma cameras" a realistic alternative to today's large Anger-type cameras that require motion to obtain tomographic sampling. The compatibility of CZT with Magnetic Resonance Imaging (MRI)-fields is demonstrated for a new type of multi-modality medical imaging, namely SPECT/MRI. For pre-clinical (i.e., laboratory animal) imaging, the advantages of CZT lie in spatial and energy resolution, small volume, automated quality control, and the potential for DOI for parallax removal in pinhole imaging. For clinical imaging, the imaging of radiographically dense breasts with CZT enables scatter rejection and hence improved contrast. Examples of clinical breast images with a dual-head CZT system are shown.

Morphology filter bank for extracting nodular and linear patterns in medical images.

PubMed

Hashimoto, Ryutaro; Uchiyama, Yoshikazu; Uchimura, Keiichi; Koutaki, Gou; Inoue, Tomoki

2017-04-01

Using image processing to extract nodular or linear shadows is a key technique of computer-aided diagnosis schemes. This study proposes a new method for extracting nodular and linear patterns of various sizes in medical images. We have developed a morphology filter bank that creates multiresolution representations of an image. Analysis bank of this filter bank produces nodular and linear patterns at each resolution level. Synthesis bank can then be used to perfectly reconstruct the original image from these decomposed patterns. Our proposed method shows better performance based on a quantitative evaluation using a synthesized image compared with a conventional method based on a Hessian matrix, often used to enhance nodular and linear patterns. In addition, experiments show that our method can be applied to the followings: (1) microcalcifications of various sizes in mammograms can be extracted, (2) blood vessels of various sizes in retinal fundus images can be extracted, and (3) thoracic CT images can be reconstructed while removing normal vessels. Our proposed method is useful for extracting nodular and linear shadows or removing normal structures in medical images.

Interactive machine learning for postprocessing CT images of hardwood logs

Treesearch

Erol Sarigul; A. Lynn Abbott; Daniel L. Schmoldt

2003-01-01

This paper concerns the nondestructive evaluation of hardwood logs through the analysis of computed tomography (CT) images. Several studies have shown that the commercial value of resulting boards can be increased substantially if log sawing strategies are chosen using prior knowledge of internal log defects. Although CT imaging offers a potential means of obtaining...

A comparative study of deep learning models for medical image classification

NASA Astrophysics Data System (ADS)

Dutta, Suvajit; Manideep, B. C. S.; Rai, Shalva; Vijayarajan, V.

2017-11-01

Deep Learning(DL) techniques are conquering over the prevailing traditional approaches of neural network, when it comes to the huge amount of dataset, applications requiring complex functions demanding increase accuracy with lower time complexities. Neurosciences has already exploited DL techniques, thus portrayed itself as an inspirational source for researchers exploring the domain of Machine learning. DL enthusiasts cover the areas of vision, speech recognition, motion planning and NLP as well, moving back and forth among fields. This concerns with building models that can successfully solve variety of tasks requiring intelligence and distributed representation. The accessibility to faster CPUs, introduction of GPUs-performing complex vector and matrix computations, supported agile connectivity to network. Enhanced software infrastructures for distributed computing worked in strengthening the thought that made researchers suffice DL methodologies. The paper emphases on the following DL procedures to traditional approaches which are performed manually for classifying medical images. The medical images are used for the study Diabetic Retinopathy(DR) and computed tomography (CT) emphysema data. Both DR and CT data diagnosis is difficult task for normal image classification methods. The initial work was carried out with basic image processing along with K-means clustering for identification of image severity levels. After determining image severity levels ANN has been applied on the data to get the basic classification result, then it is compared with the result of DNNs (Deep Neural Networks), which performed efficiently because of its multiple hidden layer features basically which increases accuracy factors, but the problem of vanishing gradient in DNNs made to consider Convolution Neural Networks (CNNs) as well for better results. The CNNs are found to be providing better outcomes when compared to other learning models aimed at classification of images. CNNs are

Edge-oriented dual-dictionary guided enrichment (EDGE) for MRI-CT image reconstruction.

PubMed

Li, Liang; Wang, Bigong; Wang, Ge

2016-01-01

In this paper, we formulate the joint/simultaneous X-ray CT and MRI image reconstruction. In particular, a novel algorithm is proposed for MRI image reconstruction from highly under-sampled MRI data and CT images. It consists of two steps. First, a training dataset is generated from a series of well-registered MRI and CT images on the same patients. Then, an initial MRI image of a patient can be reconstructed via edge-oriented dual-dictionary guided enrichment (EDGE) based on the training dataset and a CT image of the patient. Second, an MRI image is reconstructed using the dictionary learning (DL) algorithm from highly under-sampled k-space data and the initial MRI image. Our algorithm can establish a one-to-one correspondence between the two imaging modalities, and obtain a good initial MRI estimation. Both noise-free and noisy simulation studies were performed to evaluate and validate the proposed algorithm. The results with different under-sampling factors show that the proposed algorithm performed significantly better than those reconstructed using the DL algorithm from MRI data alone.

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.

Application of Super-Resolution Convolutional Neural Network for Enhancing Image Resolution in Chest CT.

PubMed

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.

Contrast-enhanced ultrasound (CEUS) liver imaging reporting and data system (LI-RADS) 2017 – a review of important differences compared to the CT/MRI system

PubMed Central

Noh, Seung Yeon; Wilson, Stephanie R; Kono, Yuko; Piscaglia, Fabio; Jang, Hyun-Jung; Lyshchik, Andrej; Dietrich, Christoph F.; Willmann, Juergen K.; Vezeridis, Alexander; Sirlin, Claude B

2017-01-01

Medical imaging plays an important role in the diagnosis and management of hepatocellular carcinoma (HCC). The Liver Imaging Reporting and Data System (LI-RADS) was initially created to standardize the reporting and data collection of CT and MR imaging for patients at risk for HCC. As contrast-enhanced ultrasound (CEUS) has been widely used in clinical practice, it has recently been added to the LI-RADS. While CEUS LI-RADS shares fundamental concepts with CT/MRI LI-RADS, there are key differences between the modalities reflecting dissimilarities in the underlying methods of image acquisition and types of contrast material. This review introduces a recent update of CEUS LI-RADS and explains the key differences from CT/MRI LI-RADS. PMID:28911220

An algorithm for 4D CT image sorting using spatial continuity.

PubMed

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.

Accurate registration of temporal CT images for pulmonary nodules detection

NASA Astrophysics Data System (ADS)

Yan, Jichao; Jiang, Luan; Li, Qiang

2017-02-01

Interpretation of temporal CT images could help the radiologists to detect some subtle interval changes in the sequential examinations. The purpose of this study was to develop a fully automated scheme for accurate registration of temporal CT images for pulmonary nodule detection. Our method consisted of three major registration steps. Firstly, affine transformation was applied in the segmented lung region to obtain global coarse registration images. Secondly, B-splines based free-form deformation (FFD) was used to refine the coarse registration images. Thirdly, Demons algorithm was performed to align the feature points extracted from the registered images in the second step and the reference images. Our database consisted of 91 temporal CT cases obtained from Beijing 301 Hospital and Shanghai Changzheng Hospital. The preliminary results showed that approximately 96.7% cases could obtain accurate registration based on subjective observation. The subtraction images of the reference images and the rigid and non-rigid registered images could effectively remove the normal structures (i.e. blood vessels) and retain the abnormalities (i.e. pulmonary nodules). This would be useful for the screening of lung cancer in our future study.

Are CT Scans Safe? Is It True That CT Scans May Increase My Risk of Cancer?

MedlinePlus

... products: Computed tomography (CT). U.S. Food and Drug Administration. http://www.fda.gov/Radiation-EmittingProducts/RadiationEmittingProductsandProcedures/MedicalImaging/MedicalX-Rays/ucm115317.htm. Accessed Jan. 19, 2018. Lee C, et al. Radiation-related risks of ...

Carbon nanotube based respiratory gated micro-CT imaging of a murine model of lung tumors with optical imaging correlation

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.

SPECT/CT imaging in general orthopedic practice.

PubMed

Scharf, Stephen

2009-09-01

The availability of hybrid devices that combine the latest single-photon emission computed tomography (SPECT) imaging technology with multislice computed tomography (CT) scanning has allowed us to detect subtle, nonspecific abnormalities on bone scans and interpret them as specific focal areas of pathology. Abnormalities in the spine can be separated into those caused by pars fractures, facet joint arthritis, or osteophyte formation on vertebral bodies. Compression fractures can be distinguished from severe degenerative disease, both of which can cause intense activity across the spine on either planar or SPECT imaging. Localizing activity in patients who have had spinal fusion can provide tremendous insight into the causes of therapeutic failures. Infections of the spine now can be diagnosed with gallium SPECT/CT, despite the fact that gallium has long been abandoned because of its failure to detect spine infection on either planar or SPECT imaging. Small focal abnormalities in the feet and ankles can be localized well enough to make specific orthopedic diagnoses on the basis of their location. Moreover, when radiographic imaging provides equivocal or inadequate information, SPECT/CT can provide a road map for further diagnostic studies and has been invaluable in planning surgery. Our ability to localize activity within a bone or at an articular surface has allowed us to distinguish between fractures and joint disease. Increased activity associated with congenital anomalies, such as tarsal coalition and Bertolotti's syndrome have allowed us to understand the pathophysiology of these conditions, to confirm them as the cause of the patient's symptoms, and to provide information that is useful in determining appropriate clinical management. As our experience broadens, SPECT/CT will undoubtedly become an important tool in the evaluation and management of a wider variety of orthopedic patients.

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

TH-E-202-01: Pitfalls and Remedies in PET/CT Imaging for RT Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pan, T.

2016-06-15

PET/CT is a very important imaging tool in the management of oncology patients. PET/CT has been applied for treatment planning and response evaluation in radiation therapy. This educational session will discuss: Pitfalls and remedies in PET/CT imaging for RT planning The use of hypoxia PET imaging for radiotherapy PET for tumor response evaluation The first presentation will address the issue of mis-registration between the CT and PET images in the thorax and the abdomen. We will discuss the challenges of respiratory gating and introduce an average CT technique to improve the registration for dose calculation and image-guidance in radiation therapy.more » The second presentation will discuss the use of hypoxia PET Imaging for radiation therapy. We will discuss various hypoxia radiotracers, the choice of clinical acquisition protocol (in particular a single late static acquisition versus a dynamic acquisition), and the compartmental modeling with different transfer rate constants explained. We will demonstrate applications of hypoxia imaging for dose escalation/de-escalation in clinical trials. The last presentation will discuss the use of PET/CT for tumor response evaluation. We will discuss anatomic response assessment vs. metabolic response assessment, visual evaluation and semi-quantitative evaluation, and limitations of current PET/CT assessment. We will summarize clinical trials using PET response in guiding adaptive radiotherapy. Finally, we will summarize recent advancements in PET/CT radiomics and non-FDG PET tracers for response assessment. Learning Objectives: Identify the causes of mis-registration of CT and PET images in PET/CT, and review the strategies to remedy the issue. Understand the basics of PET imaging of tumor hypoxia (radiotracers, how PET measures the hypoxia selective uptake, imaging protocols, applications in chemo-radiation therapy). Understand the basics of dynamic PET imaging, compartmental modeling and parametric images. Understand

Assessment of CT image quality using a Bayesian approach

NASA Astrophysics Data System (ADS)

Reginatto, M.; Anton, M.; Elster, C.

2017-08-01

One of the most promising approaches for evaluating CT image quality is task-specific quality assessment. This involves a simplified version of a clinical task, e.g. deciding whether an image belongs to the class of images that contain the signature of a lesion or not. Task-specific quality assessment can be done by model observers, which are mathematical procedures that carry out the classification task. The most widely used figure of merit for CT image quality is the area under the ROC curve (AUC), a quantity which characterizes the performance of a given model observer. In order to estimate AUC from a finite sample of images, different approaches from classical statistics have been suggested. The goal of this paper is to introduce task-specific quality assessment of CT images to metrology and to propose a novel Bayesian estimation of AUC for the channelized Hotelling observer (CHO) applied to the task of detecting a lesion at a known image location. It is assumed that signal-present and signal-absent images follow multivariate normal distributions with the same covariance matrix. The Bayesian approach results in a posterior distribution for the AUC of the CHO which provides in addition a complete characterization of the uncertainty of this figure of merit. The approach is illustrated by its application to both simulated and experimental data.

Globally optimal tumor segmentation in PET-CT images: a graph-based co-segmentation method.

PubMed

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.

Integrated image presentation of transmission and fluorescent X-ray CT using synchrotron radiation

NASA Astrophysics Data System (ADS)

Zeniya, T.; Takeda, T.; Yu, Q.; Hasegawa, Y.; Hyodo, K.; Yuasa, T.; Hiranaka, Y.; Itai, Y.; Akatsuka, T.

2001-07-01

We have developed a computed tomography (CT) system with synchrotron radiation (SR) to detect fluorescent X-rays and transmitted X-rays simultaneously. Both SR transmission X-ray CT (SR-TXCT) and SR fluorescent X-ray CT (SR-FXCT) can describe cross-sectional images with high spatial and contrast resolutions as compared to conventional CT. TXCT gives morphological information and FXCT gives functional information of organs. So, superposed display system for SR-FXCT and SR-TXCT images has been developed for clinical diagnosis with higher reliability. Preliminary experiment with brain phantom was carried out and the superposition of both images was performed. The superposed SR-CT image gave us both functional and morphological information easily with high reliability, thus demonstrating the usefulness of this system.

Automatic seed picking for brachytherapy postimplant validation with 3D CT images.

PubMed

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.

Temporal Characteristics of Radiologists' and Novices' Lesion Detection in Viewing Medical Images Presented Rapidly and Sequentially.

PubMed

Nakashima, Ryoichi; Komori, Yuya; Maeda, Eriko; Yoshikawa, Takeharu; Yokosawa, Kazuhiko

2016-01-01

Although viewing multiple stacks of medical images presented on a display is a relatively new but useful medical task, little is known about this task. Particularly, it is unclear how radiologists search for lesions in this type of image reading. When viewing cluttered and dynamic displays, continuous motion itself does not capture attention. Thus, it is effective for the target detection that observers' attention is captured by the onset signal of a suddenly appearing target among the continuously moving distractors (i.e., a passive viewing strategy). This can be applied to stack viewing tasks, because lesions often show up as transient signals in medical images which are sequentially presented simulating a dynamic and smoothly transforming image progression of organs. However, it is unclear whether observers can detect a target when the target appears at the beginning of a sequential presentation where the global apparent motion onset signal (i.e., signal of the initiation of the apparent motion by sequential presentation) occurs. We investigated the ability of radiologists to detect lesions during such tasks by comparing the performances of radiologists and novices. Results show that overall performance of radiologists is better than novices. Furthermore, the temporal locations of lesions in CT image sequences, i.e., when a lesion appears in an image sequence, does not affect the performance of radiologists, whereas it does affect the performance of novices. Results indicate that novices have greater difficulty in detecting a lesion appearing early than late in the image sequence. We suggest that radiologists have other mechanisms to detect lesions in medical images with little attention which novices do not have. This ability is critically important when viewing rapid sequential presentations of multiple CT images, such as stack viewing tasks.

Temporal Characteristics of Radiologists' and Novices' Lesion Detection in Viewing Medical Images Presented Rapidly and Sequentially

PubMed Central

Nakashima, Ryoichi; Komori, Yuya; Maeda, Eriko; Yoshikawa, Takeharu; Yokosawa, Kazuhiko

2016-01-01

Although viewing multiple stacks of medical images presented on a display is a relatively new but useful medical task, little is known about this task. Particularly, it is unclear how radiologists search for lesions in this type of image reading. When viewing cluttered and dynamic displays, continuous motion itself does not capture attention. Thus, it is effective for the target detection that observers' attention is captured by the onset signal of a suddenly appearing target among the continuously moving distractors (i.e., a passive viewing strategy). This can be applied to stack viewing tasks, because lesions often show up as transient signals in medical images which are sequentially presented simulating a dynamic and smoothly transforming image progression of organs. However, it is unclear whether observers can detect a target when the target appears at the beginning of a sequential presentation where the global apparent motion onset signal (i.e., signal of the initiation of the apparent motion by sequential presentation) occurs. We investigated the ability of radiologists to detect lesions during such tasks by comparing the performances of radiologists and novices. Results show that overall performance of radiologists is better than novices. Furthermore, the temporal locations of lesions in CT image sequences, i.e., when a lesion appears in an image sequence, does not affect the performance of radiologists, whereas it does affect the performance of novices. Results indicate that novices have greater difficulty in detecting a lesion appearing early than late in the image sequence. We suggest that radiologists have other mechanisms to detect lesions in medical images with little attention which novices do not have. This ability is critically important when viewing rapid sequential presentations of multiple CT images, such as stack viewing tasks. PMID:27774080

Emergency Department Patients’ Perceptions of Radiation from Medical Imaging

PubMed Central

Repplinger, Michael D.; Li, Annabel J.; Svenson, James E.; Ehlehbach, William J.; Westergaard, Ryan P.; Reeder, Scott B.; Jacobs, Elizabeth A.

2016-01-01

Objective To evaluate emergency department patients’ knowledge of radiation exposure and subsequent risks from CT and MRI scans. Methods This is a cross-sectional survey study of adult, English-speaking patients from 6/2011-8/2011 at two emergency departments, one academic and one community-based, in the upper Midwest. The survey consisted of two sets of three questions evaluating patients’ knowledge of radiation exposure from medical imaging and subsequent radiation-induced malignancies, and was based on a previously published survey. The question sets paralleled each other, but one pertained to CT and the other to MRI. Questions in the survey ascertained patients’ understanding of: 1) the relative amount of radiation exposed from CT/MRI compared with a single chest x-ray, 2) the relative amount of radiation exposed from CT/MRI compared with a nuclear power plant accident, and 3) the possibility of radiation-induced malignancies from CT/MRI. Sociodemographic data were also gathered. The primary outcome measure was the proportion of correct answers to each question of the survey. Multiple logistic regression was then used to examine the relationship between the percentage correct for each question and sociodemographic variables, using odds ratios with 95% confidence intervals. P-values less than 0.05 were considered statistically significant. Results There were 500 participants in this study, 315 from the academic center and 185 from the community hospital. Overall, 14.1% (95% CI 11.0%-17.2%) of participants understood the relative radiation exposure of a CT scan compared with a chest x-ray while 22.8% (95% CI 18.9%-26.7%) of respondents understood the lack of ionizing radiation use with MRI. 25.6% (95% CI 21.8%-29.4%) believed that there was an increased risk of developing cancer from repeated abdominal CTs while 55.6% (95% CI 51.1%-60.1%) believed this to be true of abdominal MRI. Higher educational level and identification as a healthcare professional were

Objective image characterization of a spectral CT scanner with dual-layer detector

NASA Astrophysics Data System (ADS)

Ozguner, Orhan; Dhanantwari, Amar; Halliburton, Sandra; Wen, Gezheng; Utrup, Steven; Jordan, David

2018-01-01

This work evaluated the performance of a detector-based spectral CT system by obtaining objective reference data, evaluating attenuation response of iodine and accuracy of iodine quantification, and comparing conventional CT and virtual monoenergetic images in three common phantoms. Scanning was performed using the hospital’s clinical adult body protocol. Modulation transfer function (MTF) was calculated for a tungsten wire and visual line pair targets were evaluated. Image noise power spectrum (NPS) and pixel standard deviation were calculated. MTF for monoenergetic images agreed with conventional images within 0.05 lp cm-1. NPS curves indicated that noise texture of 70 keV monoenergetic images is similar to conventional images. Standard deviation measurements showed monoenergetic images have lower noise except at 40 keV. Mean CT number and CNR agreed with conventional images at 75 keV. Measured iodine concentration agreed with true concentration within 6% for inserts at the center of the phantom. Performance of monoenergetic images at detector based spectral CT is the same as, or better than, that of conventional images. Spectral acquisition and reconstruction with a detector based platform represents the physical behaviour of iodine as expected and accurately quantifies the material concentration.

SU-E-I-43: Pediatric CT Dose and Image Quality Optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stevens, G; Singh, R

2014-06-01

Purpose: To design an approach to optimize radiation dose and image quality for pediatric CT imaging, and to evaluate expected performance. Methods: A methodology was designed to quantify relative image quality as a function of CT image acquisition parameters. Image contrast and image noise were used to indicate expected conspicuity of objects, and a wide-cone system was used to minimize scan time for motion avoidance. A decision framework was designed to select acquisition parameters as a weighted combination of image quality and dose. Phantom tests were used to acquire images at multiple techniques to demonstrate expected contrast, noise and dose.more » Anthropomorphic phantoms with contrast inserts were imaged on a 160mm CT system with tube voltage capabilities as low as 70kVp. Previously acquired clinical images were used in conjunction with simulation tools to emulate images at different tube voltages and currents to assess human observer preferences. Results: Examination of image contrast, noise, dose and tube/generator capabilities indicates a clinical task and object-size dependent optimization. Phantom experiments confirm that system modeling can be used to achieve the desired image quality and noise performance. Observer studies indicate that clinical utilization of this optimization requires a modified approach to achieve the desired performance. Conclusion: This work indicates the potential to optimize radiation dose and image quality for pediatric CT imaging. In addition, the methodology can be used in an automated parameter selection feature that can suggest techniques given a limited number of user inputs. G Stevens and R Singh are employees of GE Healthcare.« less

PET attenuation coefficients from CT images: experimental evaluation of the transformation of CT into PET 511-keV attenuation coefficients.

PubMed

Burger, C; Goerres, G; Schoenes, S; Buck, A; Lonn, A H R; Von Schulthess, G K

2002-07-01

The CT data acquired in combined PET/CT studies provide a fast and essentially noiseless source for the correction of photon attenuation in PET emission data. To this end, the CT values relating to attenuation of photons in the range of 40-140 keV must be transformed into linear attenuation coefficients at the PET energy of 511 keV. As attenuation depends on photon energy and the absorbing material, an accurate theoretical relation cannot be devised. The transformation implemented in the Discovery LS PET/CT scanner (GE Medical Systems, Milwaukee, Wis.) uses a bilinear function based on the attenuation of water and cortical bone at the CT and PET energies. The purpose of this study was to compare this transformation with experimental CT values and corresponding PET attenuation coefficients. In 14 patients, quantitative PET attenuation maps were calculated from germanium-68 transmission scans, and resolution-matched CT images were generated. A total of 114 volumes of interest were defined and the average PET attenuation coefficients and CT values measured. From the CT values the predicted PET attenuation coefficients were calculated using the bilinear transformation. When the transformation was based on the narrow-beam attenuation coefficient of water at 511 keV (0.096 cm(-1)), the predicted attenuation coefficients were higher in soft tissue than the measured values. This bias was reduced by replacing 0.096 cm(-1) in the transformation by the linear attenuation coefficient of 0.093 cm(-1) obtained from germanium-68 transmission scans. An analysis of the corrected emission activities shows that the resulting transformation is essentially equivalent to the transmission-based attenuation correction for human tissue. For non-human material, however, it may assign inaccurate attenuation coefficients which will also affect the correction in neighbouring tissue.

Assessment of the effects of CT dose in averaged x-ray CT images of a dose-sensitive polymer gel

NASA Astrophysics Data System (ADS)

Kairn, T.; Kakakhel, M. B.; Johnston, H.; Jirasek, A.; Trapp, J. V.

2015-01-01

The signal-to-noise ratio achievable in x-ray computed tomography (CT) images of polymer gels can be increased by averaging over multiple scans of each sample. However, repeated scanning delivers a small additional dose to the gel which may compromise the accuracy of the dose measurement. In this study, a NIPAM-based polymer gel was irradiated and then CT scanned 25 times, with the resulting data used to derive an averaged image and a "zero-scan" image of the gel. Comparison between these two results and the first scan of the gel showed that the averaged and zero-scan images provided better contrast, higher contrast-to- noise and higher signal-to-noise than the initial scan. The pixel values (Hounsfield units, HU) in the averaged image were not noticeably elevated, compared to the zero-scan result and the gradients used in the linear extrapolation of the zero-scan images were small and symmetrically distributed around zero. These results indicate that the averaged image was not artificially lightened by the small, additional dose delivered during CT scanning. This work demonstrates the broader usefulness of the zero-scan method as a means to verify the dosimetric accuracy of gel images derived from averaged x-ray CT data.

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.

Useful diagnostic biometabolic data obtained by PET/CT and MR fusion imaging using open source software.

PubMed

Antonica, Filippo; Asabella, Artor Niccoli; Ferrari, Cristina; Rubini, Domenico; Notaristefano, Antonio; Nicoletti, Adriano; Altini, Corinna; Merenda, Nunzio; Mossa, Emilio; Guarini, Attilio; Rubini, Giuseppe

2014-01-01

poor due to internal organs filling variation and time shifting beetwen examinations. PET/CT images with time of flight reconstruction and real attenuation correction were combined with anatomical detailed MRI images. We used Osirix, an image processing Open Source Software dedicated to DICOM images. No additional costs, to buy and upgrade proprietary software are required for combining data. No high technology or very expensive PET/MR scanner, that requires dedicated shielded room spaces and personnel to be employed or to be trained, are needed. Our method allows to share patient PET/MR fused data with different medical staff using dedicated networks. The proposed method may be applied to every MR sequence (MR-DWI and MR-STIR, magnet enhanced sequences) to characterize soft tissue alterations and improve discrimination diseases. It can be applied not only to PET with MR but virtually to every DICOM study.

Venous air embolism in consecutive balloon kyphoplasties visualised on CT imaging.

PubMed

Tins, Bernhard J; Cassar-Pullicino, Victor N; Lalam, Radhesh; Haddaway, Mike

2012-09-01

We noted a large amount of intravenous gas during balloon kyphoplasty on CT imaging. Formal assessment to understand the extent, possible causes and implications was undertaken. Ten consecutive cases of balloon kyphoplasty were performed under general anaesthesia in the prone position, on a single vertebral level using a two-step technique under combined fluoroscopic and CT guidance. CT of the affected vertebra was performed before, after, and intermittently during the procedure. In 2 cases delayed CT was carried out in the supine position. Gas was seen on CT imaging, but not on conventional fluoroscopy. The gas is most likely to be air introduced during the procedure and was seen in the epidural and paravertebral venous plexus, posterior intercostal veins, renal veins, IVC and azygos vein. The average measured volume of gas seen on the post-procedure CT imaging was 1.07 mL, range 0.16-3.97 mL. There was no correlation of the measured amount of gas to the procedure duration or location, the use of a curette or the injected cement volume. Delayed CT in the supine position no longer showed air in the local venous system. Balloon kyphoplasty is associated with the fluoroscopically invisible introduction of air into the vertebral and paravertebral veins and deep systemic veins and is likely to be much more extensive than identified on CT imaging. There is potential for serious air embolism in kyphoplasty and if there is a sudden deterioration in patient condition during the procedure the possibility of this complication needs to be considered.

Segmentation of deformable organs from medical images using particle swarm optimization and nonlinear shape priors

NASA Astrophysics Data System (ADS)

Afifi, Ahmed; Nakaguchi, Toshiya; Tsumura, Norimichi

2010-03-01

In many medical applications, the automatic segmentation of deformable organs from medical images is indispensable and its accuracy is of a special interest. However, the automatic segmentation of these organs is a challenging task according to its complex shape. Moreover, the medical images usually have noise, clutter, or occlusion and considering the image information only often leads to meager image segmentation. In this paper, we propose a fully automated technique for the segmentation of deformable organs from medical images. In this technique, the segmentation is performed by fitting a nonlinear shape model with pre-segmented images. The kernel principle component analysis (KPCA) is utilized to capture the complex organs deformation and to construct the nonlinear shape model. The presegmentation is carried out by labeling each pixel according to its high level texture features extracted using the overcomplete wavelet packet decomposition. Furthermore, to guarantee an accurate fitting between the nonlinear model and the pre-segmented images, the particle swarm optimization (PSO) algorithm is employed to adapt the model parameters for the novel images. In this paper, we demonstrate the competence of proposed technique by implementing it to the liver segmentation from computed tomography (CT) scans of different patients.

Evaluation of an iterative model-based reconstruction of pediatric abdominal CT with regard to image quality and radiation dose.

PubMed

Aurumskjöld, Marie-Louise; Söderberg, Marcus; Stålhammar, Fredrik; von Steyern, Kristina Vult; Tingberg, Anders; Ydström, Kristina

2018-06-01

Background In pediatric patients, computed tomography (CT) is important in the medical chain of diagnosing and monitoring various diseases. Because children are more radiosensitive than adults, they require minimal radiation exposure. One way to achieve this goal is to implement new technical solutions, like iterative reconstruction. Purpose To evaluate the potential of a new, iterative, model-based method for reconstructing (IMR) pediatric abdominal CT at a low radiation dose and determine whether it maintains or improves image quality, compared to the current reconstruction method. Material and Methods Forty pediatric patients underwent abdominal CT. Twenty patients were examined with the standard dose settings and 20 patients were examined with a 32% lower radiation dose. Images from the standard examination were reconstructed with a hybrid iterative reconstruction method (iDose 4 ), and images from the low-dose examinations were reconstructed with both iDose 4 and IMR. Image quality was evaluated subjectively by three observers, according to modified EU image quality criteria, and evaluated objectively based on the noise observed in liver images. Results Visual grading characteristics analyses showed no difference in image quality between the standard dose examination reconstructed with iDose 4 and the low dose examination reconstructed with IMR. IMR showed lower image noise in the liver compared to iDose 4 images. Inter- and intra-observer variance was low: the intraclass coefficient was 0.66 (95% confidence interval = 0.60-0.71) for the three observers. Conclusion IMR provided image quality equivalent or superior to the standard iDose 4 method for evaluating pediatric abdominal CT, even with a 32% dose reduction.

Comparison of quantitative myocardial perfusion imaging CT to fluorescent microsphere-based flow from high-resolution cryo-images

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.

18F-FDOPA PET/CT imaging of MAX-related pheochromocytoma.

PubMed

Taïeb, David; Jha, Abhishek; Guerin, Carole; Pang, Ying; Adams, Karen T; Chen, Clara C; Romanet, Pauline; Roche, Philippe; Essamet, Wassim; Ling, Alexander; Quezado, Martha M; Castinetti, Frédéric; Sebag, Fréderic; Pacak, Karel

2018-03-08

MYC associated factor X (MAX) has been recently described as a new susceptibility pheochromocytoma (PHEO) gene with a total of approximately 40 reported cases. At present, no study has specifically described the functional imaging phenotype of MAX-related PHEO. The objective of this study was to present our experience with contrast-enhanced CT and 18F-FDOPA PET/CT imaging in 6 consecutive patients (4 at initial diagnosis and 2 at follow-up evaluation) with rare but clinically important MAX-related PHEOs. In 5 patients, 18F-FDOPA was also compared to other radiopharmaceuticals. Patients had 5 different mutations in the MAX gene that caused disruption of Max/Myc interaction and/or abolished interaction with DNA based on in-silico analyses. All but one patient developed bilateral PHEOs during their lifetime. In all cases, 18F-FDOPA PET/CT accurately visualized PHEOs that were often multiple within the same gland or bilateral and detected more adrenal and extradrenal lesions than CT (per lesion sensitivity 90.5% vs 52.4% for CT/MRI). The 2 missed PHEO on 18F-FDOPA PET/CT were <1cm, corresponding to nodular adrenomedullary hyperplasia. 68Ga-DOTATATE PET/CT detected fewer lesions than 18F-FDOPA PET/CT in 1/3 patients and 18F-FDG PET/CT was only faintly positive in 2/4 patients with underestimation of extraadrenal lesions in 1 patient. MAX-related PHEO exihibit a marked 18F-FDOPA uptake, a finding that illustrates the common well-differentiated chromaffin pattern of PHEO associated with activation of kinase signaling pathways. 18F-FDOPA PET/CT should be considered as the first-line functional imaging modality for diagnostic or follow-up evaluation in these patients.

An evaluation of the use of oral contrast media in abdominopelvic CT.

PubMed

Buttigieg, Erica Lauren; Grima, Karen Borg; Cortis, Kelvin; Soler, Sandro Galea; Zarb, Francis

2014-11-01

To evaluate the diagnostic efficacy of different oral contrast media (OCM) for abdominopelvic CT examinations performed for follow-up general oncological indications. The objectives were to establish anatomical image quality criteria for abdominopelvic CT; use these criteria to evaluate and compare image quality using positive OCM, neutral OCM and no OCM; and evaluate possible benefits for the medical imaging department. Forty-six adult patients attending a follow-up abdominopelvic CT for general oncological indications and who had a previous abdominopelvic CT with positive OCM (n = 46) were recruited and prospectively placed into either the water (n = 25) or no OCM (n = 21) group. Three radiologists performed absolute visual grading analysis (VGA) to assess image quality by grading the fulfilment of 24 anatomical image quality criteria. Visual grading characteristics (VGC) analysis of the data showed comparable image quality with regards to reproduction of abdominal structures, bowel discrimination, presence of artefacts, and visualization of the amount of intra-abdominal fat for the three OCM protocols. All three OCM protocols provided similar image quality for follow-up abdominopelvic CT for general oncological indications. • Positive oral contrast media are routinely used for abdominopelvic multidetector computed tomography • Experimental study comparing image quality using three different oral contrast materials • Three different oral contrast materials result in comparable CT image quality • Benefits for patients and medical imaging department.

A Flexible Method for Multi-Material Decomposition of Dual-Energy CT Images.

PubMed

Mendonca, Paulo R S; Lamb, Peter; Sahani, Dushyant V

2014-01-01