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Sample records for ct medical image

  1. An evaluation on CT image acquisition method for medical VR applications

    NASA Astrophysics Data System (ADS)

    Jang, Seong-wook; Ko, Junho; Yoo, Yon-sik; Kim, Yoonsang

    2017-02-01

    Recent medical virtual reality (VR) applications to minimize re-operations are being studied for improvements in surgical efficiency and reduction of operation error. The CT image acquisition method considering three-dimensional (3D) modeling for medical VR applications is important, because the realistic model is required for the actual human organ. However, the research for medical VR applications has focused on 3D modeling techniques and utilized 3D models. In addition, research on a CT image acquisition method considering 3D modeling has never been reported. The conventional CT image acquisition method involves scanning a limited area of the lesion for the diagnosis of doctors once or twice. However, the medical VR application is required to acquire the CT image considering patients' various postures and a wider area than the lesion. A wider area than the lesion is required because of the necessary process of comparing bilateral sides for dyskinesia diagnosis of the shoulder, pelvis, and leg. Moreover, patients' various postures are required due to the different effects on the musculoskeletal system. Therefore, in this paper, we perform a comparative experiment on the acquired CT images considering image area (unilateral/bilateral) and patients' postures (neutral/abducted). CT images are acquired from 10 patients for the experiments, and the acquired CT images are evaluated based on the length per pixel and the morphological deviation. Finally, by comparing the experiment results, we evaluate the CT image acquisition method for medical VR applications.

  2. An active contour model for medical image segmentation with application to brain CT image

    PubMed Central

    Qian, Xiaohua; Wang, Jiahui; Guo, Shuxu; Li, Qiang

    2013-01-01

    Purpose: Cerebrospinal fluid (CSF) segmentation in computed tomography (CT) is a key step in computer-aided detection (CAD) of acute ischemic stroke. Because of image noise, low contrast and intensity inhomogeneity, CSF segmentation has been a challenging task. A region-based active contour model, which is insensitive to contour initialization and robust to intensity inhomogeneity, was developed for segmenting CSF in brain CT images. Methods: The energy function of the region-based active contour model is composed of a range domain kernel function, a space domain kernel function, and an edge indicator function. By minimizing the energy function, the region of edge elements of the target could be automatically identified in images with less dependence on initial contours. The energy function was optimized by means of the deepest descent method with a level set framework. An overlap rate between segmentation results and the reference standard was used to assess the segmentation accuracy. The authors evaluated the performance of the proposed method on both synthetic data and real brain CT images. They also compared the performance level of our method to those of region-scalable fitting (RSF) and global convex segment (GCS) models. Results: For the experiment of CSF segmentation in 67 brain CT images, their method achieved an average overlap rate of 66% compared to the average overlap rates of 16% and 46% from the RSF model and the GCS model, respectively. Conclusions: Their region-based active contour model has the ability to achieve accurate segmentation results in images with high noise level and intensity inhomogeneity. Therefore, their method has great potential in the segmentation of medical images and would be useful for developing CAD schemes for acute ischemic stroke in brain CT images. PMID:23387759

  3. Edge extraction of CT medical image based on wavelet transform algorithm

    NASA Astrophysics Data System (ADS)

    Wang, Xiaojun; Li, Xinzheng; Lai, Weidong

    2011-06-01

    Since computer tomography (CT) image has been widely applied in clinic diagnostics, while for many applications the information directly provided by CT images is incomplete corrupted by noise or instrument defect, there has great demand to further the processing methods for improving the CT image quality. Among all image features, the edge profile of clinic focus has obvious influence on accurately translating CT image. In this paper, the wavelet filtering algorithm based on modulus maximum method is put forward to extract and enhance the CT image edges. Edges in the brain lobe CT image can be outlined after wavelet transform, during which the wavelet assigned as the first order derivative of Gauss function. Further manipulation through maximum threshold checking to the modulus have been attenuated the pseudo-edges. After segmented with the original CT image, the edge structure has been distinctly enhanced, and high contrast is achieved between the brain lobe microstructure and the artificially established edges. The proposed algorithm is more efficient than the common first order differential operator, for the latter it even deteriorates the edge features. The algorithm proposed in this article can be integrated in medical image analyzing software to obtain higher accuracy for symptom interpretation.

  4. A new method of content based medical image retrieval and its applications to CT imaging sign retrieval.

    PubMed

    Ma, Ling; Liu, Xiabi; Gao, Yan; Zhao, Yanfeng; Zhao, Xinming; Zhou, Chunwu

    2017-02-01

    This paper proposes a new method of content based medical image retrieval through considering fused, context-sensitive similarity. Firstly, we fuse the semantic and visual similarities between the query image and each image in the database as their pairwise similarities. Then, we construct a weighted graph whose nodes represent the images and edges measure their pairwise similarities. By using the shortest path algorithm over the weighted graph, we obtain a new similarity measure, context-sensitive similarity measure, between the query image and each database image to complete the retrieval process. Actually, we use the fused pairwise similarity to narrow down the semantic gap for obtaining a more accurate pairwise similarity measure, and spread it on the intrinsic data manifold to achieve the context-sensitive similarity for a better retrieval performance. The proposed method has been evaluated on the retrieval of the Common CT Imaging Signs of Lung Diseases (CISLs) and achieved not only better retrieval results but also the satisfactory computation efficiency.

  5. Medical imaging

    NASA Astrophysics Data System (ADS)

    Elliott, Alex

    2005-07-01

    Diagnostic medical imaging is a fundamental part of the practice of modern medicine and is responsible for the expenditure of considerable amounts of capital and revenue monies in healthcare systems around the world. Much research and development work is carried out, both by commercial companies and the academic community. This paper reviews briefly each of the major diagnostic medical imaging techniques—X-ray (planar and CT), ultrasound, nuclear medicine (planar, SPECT and PET) and magnetic resonance. The technical challenges facing each are highlighted, with some of the most recent developments. In terms of the future, interventional/peri-operative imaging, the advancement of molecular medicine and gene therapy are identified as potential areas of expansion.

  6. MULTIMODALITY IMAGING: BEYOND PET/CT AND SPECT/CT

    PubMed Central

    Cherry, Simon R.

    2009-01-01

    Multimodality imaging with PET/CT and SPECT/CT has become commonplace in clinical practice and in preclinical and basic medical research. Do other combinations of imaging modalities have a similar potential to impact medical science and clinical medicine? The combination of PET or SPECT with MRI is an area of active research at the present time, while other, perhaps less obvious combinations, including CT/MR and PET/optical also are being studied. In addition to the integration of the instrumentation, there are parallel developments in synthesizing imaging agents that can be viewed by multiple imaging modalities. Is the fusion of PET and SPECT with CT the ultimate answer in multimodality imaging, or is it just the first example of a more general trend towards harnessing the complementary nature of the different modalities on integrated imaging platforms? PMID:19646559

  7. Geometry-based vs. intensity-based medical image registration: A comparative study on 3D CT data.

    PubMed

    Savva, Antonis D; Economopoulos, Theodore L; Matsopoulos, George K

    2016-02-01

    Spatial alignment of Computed Tomography (CT) data sets is often required in numerous medical applications and it is usually achieved by applying conventional exhaustive registration techniques, which are mainly based on the intensity of the subject data sets. Those techniques consider the full range of data points composing the data, thus negatively affecting the required processing time. Alternatively, alignment can be performed using the correspondence of extracted data points from both sets. Moreover, various geometrical characteristics of those data points can be used, instead of their chromatic properties, for uniquely characterizing each point, by forming a specific geometrical descriptor. This paper presents a comparative study reviewing variations of geometry-based, descriptor-oriented registration techniques, as well as conventional, exhaustive, intensity-based methods for aligning three-dimensional (3D) CT data pairs. In this context, three general image registration frameworks were examined: a geometry-based methodology featuring three distinct geometrical descriptors, an intensity-based methodology using three different similarity metrics, as well as the commonly used Iterative Closest Point algorithm. All techniques were applied on a total of thirty 3D CT data pairs with both known and unknown initial spatial differences. After an extensive qualitative and quantitative assessment, it was concluded that the proposed geometry-based registration framework performed similarly to the examined exhaustive registration techniques. In addition, geometry-based methods dramatically improved processing time over conventional exhaustive registration.

  8. 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

  9. Image features for misalignment correction in medical flat-detector CT

    SciTech Connect

    Wicklein, Julia; Kunze, Holger; Kalender, Willi A.; Kyriakou, Yiannis

    2012-08-15

    Purpose: Misalignment artifacts are a serious problem in medical flat-detector computed tomography. Generally, the geometrical parameters, which are essential for reconstruction, are provided by preceding calibration routines. These procedures are time consuming and the later use of stored parameters is sensitive toward external impacts or patient movement. The method of choice in a clinical environment would be a markerless online-calibration procedure that allows flexible scan trajectories and simultaneously corrects misalignment and motion artifacts during the reconstruction process. Therefore, different image features were evaluated according to their capability of quantifying misalignment. Methods: Projections of the FORBILD head and thorax phantoms were simulated. Additionally, acquisitions of a head phantom and patient data were used for evaluation. For the reconstruction different sources and magnitudes of misalignment were introduced in the geometry description. The resulting volumes were analyzed by entropy (based on the gray-level histogram), total variation, Gabor filter texture features, Haralick co-occurrence features, and Tamura texture features. The feature results were compared to the back-projection mismatch of the disturbed geometry. Results: The evaluations demonstrate the ability of several well-established image features to classify misalignment. The authors elaborated the particular suitability of the gray-level histogram-based entropy on identifying misalignment artifacts, after applying an appropriate window level (bone window). Conclusions: Some of the proposed feature extraction algorithms show a strong correlation with the misalignment level. Especially, entropy-based methods showed very good correspondence, with the best of these being the type that uses the gray-level histogram for calculation. This makes it a suitable image feature for online-calibration.

  10. Value of a probabilistic atlas in medical image segmentation regarding non-rigid registration of abdominal CT scans

    NASA Astrophysics Data System (ADS)

    Park, Hyunjin; Meyer, Charles R.

    2012-10-01

    A probabilistic atlas provides important information to help segmentation and registration applications in medical image analysis. We construct a probabilistic atlas by picking a target geometry and mapping other training scans onto that target and then summing the results into one probabilistic atlas. By choosing an atlas space close to the desired target, we construct an atlas that represents the population well. Image registration used to map one image geometry onto another is a primary task in atlas building. One of the main parameters of registration is the choice of degrees of freedom (DOFs) of the geometric transform. Herein, we measure the effect of the registration's DOFs on the segmentation performance of the resulting probabilistic atlas. Twenty-three normal abdominal CT scans were used, and four organs (liver, spinal cord, left and right kidneys) were segmented for each scan. A well-known manifold learning method, ISOMAP, was used to find the best target space to build an atlas. In summary, segmentation performance was high for high DOF registrations regardless of the chosen target space, while segmentation performance was lowered for low DOF registrations if a target space was far from the best target space. At the 0.05 level of statistical significance, there were no significant differences at high DOF registrations while there were significant differences at low DOF registrations when choosing different targets.

  11. Automated medical image segmentation techniques

    PubMed Central

    Sharma, Neeraj; Aggarwal, Lalit M.

    2010-01-01

    Accurate segmentation of medical images is a key step in contouring during radiotherapy planning. Computed topography (CT) and Magnetic resonance (MR) imaging are the most widely used radiographic techniques in diagnosis, clinical studies and treatment planning. This review provides details of automated segmentation methods, specifically discussed in the context of CT and MR images. The motive is to discuss the problems encountered in segmentation of CT and MR images, and the relative merits and limitations of methods currently available for segmentation of medical images. PMID:20177565

  12. 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.

  13. NETL CT Imaging Facility

    ScienceCinema

    None

    2016-07-12

    NETL's CT Scanner laboratory is equipped with three CT scanners and a mobile core logging unit that work together to provide characteristic geologic and geophysical information at different scales, non-destructively.

  14. Medical image analysis methods in MR/CT-imaged acute-subacute ischemic stroke lesion: Segmentation, prediction and insights into dynamic evolution simulation models. A critical appraisal☆

    PubMed Central

    Rekik, Islem; Allassonnière, Stéphanie; Carpenter, Trevor K.; Wardlaw, Joanna M.

    2012-01-01

    Over the last 15 years, basic thresholding techniques in combination with standard statistical correlation-based data analysis tools have been widely used to investigate different aspects of evolution of acute or subacute to late stage ischemic stroke in both human and animal data. Yet, a wave of biology-dependent and imaging-dependent issues is still untackled pointing towards the key question: “how does an ischemic stroke evolve?” Paving the way for potential answers to this question, both magnetic resonance (MRI) and CT (computed tomography) images have been used to visualize the lesion extent, either with or without spatial distinction between dead and salvageable tissue. Combining diffusion and perfusion imaging modalities may provide the possibility of predicting further tissue recovery or eventual necrosis. Going beyond these basic thresholding techniques, in this critical appraisal, we explore different semi-automatic or fully automatic 2D/3D medical image analysis methods and mathematical models applied to human, animal (rats/rodents) and/or synthetic ischemic stroke to tackle one of the following three problems: (1) segmentation of infarcted and/or salvageable (also called penumbral) tissue, (2) prediction of final ischemic tissue fate (death or recovery) and (3) dynamic simulation of the lesion core and/or penumbra evolution. To highlight the key features in the reviewed segmentation and prediction methods, we propose a common categorization pattern. We also emphasize some key aspects of the methods such as the imaging modalities required to build and test the presented approach, the number of patients/animals or synthetic samples, the use of external user interaction and the methods of assessment (clinical or imaging-based). Furthermore, we investigate how any key difficulties, posed by the evolution of stroke such as swelling or reperfusion, were detected (or not) by each method. In the absence of any imaging-based macroscopic dynamic model

  15. 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

  16. Medical technology integration: CT, angiography, imaging-capable OR-table, navigation and robotics in a multifunctional sterile suite.

    PubMed

    Jacob, A L; Regazzoni, P; Bilecen, D; Rasmus, M; Huegli, R W; Messmer, P

    2007-01-01

    Technology integration is an enabling technological prerequisite to achieve a major breakthrough in sophisticated intra-operative imaging, navigation and robotics in minimally invasive and/or emergency diagnosis and therapy. Without a high degree of integration and reliability comparable to that achieved in the aircraft industry image guidance in its different facets will not ultimately succeed. As of today technology integration in the field of image-guidance is close to nonexistent. Technology integration requires inter-departmental integration of human and financial resources and of medical processes in a dialectic way. This expanded techno-socio-economic integration has profound consequences for the administration and working conditions in hospitals. At the university hospital of Basel, Switzerland, a multimodality multifunction sterile suite was put into operation after a substantial pre-run. We report the lessons learned during our venture into the world of medical technology integration and describe new possibilities for similar integration projects in the future.

  17. [Influence of "optical illusion" on detectability in diagnosis for head CT images: participation of optical illusion of light perception in medical image reading and diagnosis].

    PubMed

    Henmi, Shuichi

    2006-07-20

    Even if the visual impression of the photographic density of the brain in head CT images is shown as physically the same, it is known that optical illusions of lightness perception (assimilation, contrast, picture frame effect, etc.) occur and that practical density can be observed psychologically differently, according to differences in the color of the skull and background, and differences in cases (differences in picture pattern). Therefore, in this study, in order to clarify the influence of optical illusion on detectability in diagnosis, the author attempted to compare detectability in four sample cases, consisting of acute cerebral infarction (1), acute epidural hematoma (1), and chronic subdural hematoma (2), using visual subjective evaluation. In the case of acute cerebral infarction, there was no significant difference in detectability between the original image and the virtual images. Further, it clarified that the original head CT image (acute epidural hematoma) with the high-density hematoma recognized at the marginal limited part of the brain was inferior to virtual images in detectability, while it clarified that the original head CT image (chronic subdural hematoma) with the low-density hematoma was superior to virtual images in detectability, because of visual psychological emphasis on the difference of the film contrast between the hematoma and white skull.

  18. Medical imaging

    SciTech Connect

    Schneider, R.H.; Dwyer, S.J.

    1987-01-01

    This book contains papers from 26 sessions. Some of the session titles are: Tomographic Reconstruction, Radiography, Fluoro/Angio, Imaging Performance Measures, Perception, Image Processing, 3-D Display, and Printers, Displays, and Digitizers.

  19. Scintillator requirements for medical imaging

    SciTech Connect

    Moses, William W.

    1999-09-01

    Scintillating materials are used in a variety of medical imaging devices. This paper presents a description of four medical imaging modalities that make extensive use of scintillators: planar x-ray imaging, x-ray computed tomography (x-ray CT), SPECT (single photon emission computed tomography) and PET (positron emission tomography). The discussion concentrates on a description of the underlying physical principles by which the four modalities operate. The scintillator requirements for these systems are enumerated and the compromises that are made in order to maximize imaging performance utilizing existing scintillating materials are discussed, as is the potential for improving imaging performance by improving scintillator properties.

  20. Variations in PET/CT Methodology for Oncologic Imaging at U.S. Academic Medical Centers: An Imaging Response Assessment Team Survey

    PubMed Central

    Graham, Michael M.; Badawi, Ramsey D.; Wahl, Richard L.

    2014-01-01

    In 2005, 8 Imaging Response Assessment Teams (IRATs) were funded by the National Cancer Institute (NCI) as supplemental grants to existing NCI Cancer Centers. After discussion among the IRATs regarding the need for increased standardization of clinical and research PET/CT methodology, it became apparent that data acquisition and processing approaches differ considerably among centers. To determine the variability in detail, a survey of IRAT sites and IRAT affiliates was performed. Methods A 34-question instrument evaluating patient preparation, scanner type, performance approach, display, and analysis was developed. Fifteen institutions, including the 8 original IRATs and 7 institutions that had developed affiliate IRATs, were surveyed. Results The major areas of variation were18F-FDG dose (259–740 MBq [7–20 mCi]) uptake time (45–90 min), sedation (never to frequently), handling of diabetic patients, imaging time (2–7 min/bed position), performance of diagnostic CT scans as a part of PET/CT, type of acquisition (2-dimensional vs. 3-dimensional), CT technique, duration of fasting (4 or 6 h), and (varying widely) acquisition, processing, display, and PACS software—with 4 sites stating that poor-quality images appear on PACS. Conclusion There is considerable variability in the way PET/CT scans are performed at academic institutions that are part of the IRAT network. This variability likely makes it difficult to quantitatively compare studies performed at different centers. These data suggest that additional standardization in methodology will be required so that PET/CT studies, especially those performed quantitatively, are more comparable across sites. PMID:21233185

  1. Body-wide anatomy recognition in PET/CT images

    NASA Astrophysics Data System (ADS)

    Wang, Huiqian; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Zhao, Liming; Torigian, Drew A.

    2015-03-01

    With the rapid growth of positron emission tomography/computed tomography (PET/CT)-based medical applications, body-wide anatomy recognition on whole-body PET/CT images becomes crucial for quantifying body-wide disease burden. This, however, is a challenging problem and seldom studied due to unclear anatomy reference frame and low spatial resolution of PET images as well as low contrast and spatial resolution of the associated low-dose CT images. We previously developed an automatic anatomy recognition (AAR) system [15] whose applicability was demonstrated on diagnostic computed tomography (CT) and magnetic resonance (MR) images in different body regions on 35 objects. The aim of the present work is to investigate strategies for adapting the previous AAR system to low-dose CT and PET images toward automated body-wide disease quantification. Our adaptation of the previous AAR methodology to PET/CT images in this paper focuses on 16 objects in three body regions - thorax, abdomen, and pelvis - and consists of the following steps: collecting whole-body PET/CT images from existing patient image databases, delineating all objects in these images, modifying the previous hierarchical models built from diagnostic CT images to account for differences in appearance in low-dose CT and PET images, automatically locating objects in these images following object hierarchy, and evaluating performance. Our preliminary evaluations indicate that the performance of the AAR approach on low-dose CT images achieves object localization accuracy within about 2 voxels, which is comparable to the accuracies achieved on diagnostic contrast-enhanced CT images. Object recognition on low-dose CT images from PET/CT examinations without requiring diagnostic contrast-enhanced CT seems feasible.

  2. Medical Imaging.

    ERIC Educational Resources Information Center

    Jaffe, C. Carl

    1982-01-01

    Describes principle imaging techniques, their applications, and their limitations in terms of diagnostic capability and possible adverse biological effects. Techniques include film radiography, computed tomography, nuclear medicine, positron emission tomography (PET), ultrasonography, nuclear magnetic resonance, and digital radiography. PET has…

  3. Imaging medical imaging

    NASA Astrophysics Data System (ADS)

    Journeau, P.

    2015-03-01

    This paper presents progress on imaging the research field of Imaging Informatics, mapped as the clustering of its communities together with their main results by applying a process to produce a dynamical image of the interactions between their results and their common object(s) of research. The basic side draws from a fundamental research on the concept of dimensions and projective space spanning several streams of research about three-dimensional perceptivity and re-cognition and on their relation and reduction to spatial dimensionality. The application results in an N-dimensional mapping in Bio-Medical Imaging, with dimensions such as inflammatory activity, MRI acquisition sequencing, spatial resolution (voxel size), spatiotemporal dimension inferred, toxicity, depth penetration, sensitivity, temporal resolution, wave length, imaging duration, etc. Each field is represented through the projection of papers' and projects' `discriminating' quantitative results onto the specific N-dimensional hypercube of relevant measurement axes, such as listed above and before reduction. Past published differentiating results are represented as red stars, achieved unpublished results as purple spots and projects at diverse progress advancement levels as blue pie slices. The goal of the mapping is to show the dynamics of the trajectories of the field in its own experimental frame and their direction, speed and other characteristics. We conclude with an invitation to participate and show a sample mapping of the dynamics of the community and a tentative predictive model from community contribution.

  4. Functional Imaging: CT and MRI

    PubMed Central

    van Beek, Edwin JR; Hoffman, Eric A

    2008-01-01

    Synopsis Numerous imaging techniques permit evaluation of regional pulmonary function. Contrast-enhanced CT methods now allow assessment of vasculature and lung perfusion. Techniques using spirometric controlled MDCT allow for quantification of presence and distribution of parenchymal and airway pathology, Xenon gas can be employed to assess regional ventilation of the lungs and rapid bolus injections of iodinated contrast agent can provide quantitative measure of regional parenchymal perfusion. Advances in magnetic resonance imaging (MRI) of the lung include gadolinium-enhanced perfusion imaging and hyperpolarized helium imaging, which can allow imaging of pulmonary ventilation and .measurement of the size of emphysematous spaces. PMID:18267192

  5. 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.

  6. Medical imaging: the radiation issue.

    PubMed

    Einstein, Andrew J

    2009-06-01

    The collective doses of ionizing radiation to Western populations have risen dramatically in the past three decades. Preliminary data on changes in radiation dose to the US population indicate that this increase has been driven largely by medical imaging, to which cardiovascular imaging modalities-such as nuclear stress testing, invasive coronary angiography, and cardiovascular CT-contribute greatly. Given the putative association between low-dose radiation exposure and cancer risk, which most experts agree is supported by the available evidence, the 'radiation issue' in medical imaging has garnered increasing interest. This opinion piece focuses on changes in the use of and doses from medical imaging, the relationship between radiation dose and cancer risk and the controversy surrounding this subject, and clinical implications of radiation exposure from imaging tests.

  7. Medical Imaging System

    NASA Technical Reports Server (NTRS)

    1991-01-01

    The MD Image System, a true-color image processing system that serves as a diagnostic aid and tool for storage and distribution of images, was developed by Medical Image Management Systems, Huntsville, AL, as a "spinoff from a spinoff." The original spinoff, Geostar 8800, developed by Crystal Image Technologies, Huntsville, incorporates advanced UNIX versions of ELAS (developed by NASA's Earth Resources Laboratory for analysis of Landsat images) for general purpose image processing. The MD Image System is an application of this technology to a medical system that aids in the diagnosis of cancer, and can accept, store and analyze images from other sources such as Magnetic Resonance Imaging.

  8. Automated detection of extradural and subdural hematoma for contrast-enhanced CT images in emergency medical care

    NASA Astrophysics Data System (ADS)

    Hara, Takeshi; Matoba, Naoto; Zhou, Xiangrong; Yokoi, Shinya; Aizawa, Hiroaki; Fujita, Hiroshi; Sakashita, Keiji; Matsuoka, Tetsuya

    2007-03-01

    We have been developing the CAD scheme for head and abdominal injuries for emergency medical care. In this work, we have developed an automated method to detect typical head injuries, rupture or strokes of brain. Extradural and subdural hematoma region were detected by comparing technique after the brain areas were registered using warping. We employ 5 normal and 15 stroke cases to estimate the performance after creating the brain model with 50 normal cases. Some of the hematoma regions were detected correctly in all of the stroke cases with no false positive findings on normal cases.

  9. 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.

  10. Image quality assessment for CT used on small animals

    NASA Astrophysics Data System (ADS)

    Cisneros, Isabela Paredes; Agulles-Pedrós, Luis

    2016-07-01

    Image acquisition on a CT scanner is nowadays necessary in almost any kind of medical study. Its purpose, to produce anatomical images with the best achievable quality, implies the highest diagnostic radiation exposure to patients. Image quality can be measured quantitatively based on parameters such as noise, uniformity and resolution. This measure allows the determination of optimal parameters of operation for the scanner in order to get the best diagnostic image. A human Phillips CT scanner is the first one minded for veterinary-use exclusively in Colombia. The aim of this study was to measure the CT image quality parameters using an acrylic phantom and then, using the computational tool MatLab, determine these parameters as a function of current value and window of visualization, in order to reduce dose delivery by keeping the appropriate image quality.

  11. Medical imaging systems

    DOEpatents

    Frangioni, John V

    2013-06-25

    A medical imaging system provides simultaneous rendering of visible light and diagnostic or functional images. The system may be portable, and may include adapters for connecting various light sources and cameras in open surgical environments or laparascopic or endoscopic environments. A user interface provides control over the functionality of the integrated imaging system. In one embodiment, the system provides a tool for surgical pathology.

  12. Iterative image reconstruction in spectral CT

    NASA Astrophysics Data System (ADS)

    Hernandez, Daniel; Michel, Eric; Kim, Hye S.; Kim, Jae G.; Han, Byung H.; Cho, Min H.; Lee, Soo Y.

    2012-03-01

    Scan time of spectral-CTs is much longer than conventional CTs due to limited number of x-ray photons detectable by photon-counting detectors. However, the spectral pixel information in spectral-CT has much richer information on physiological and pathological status of the tissues than the CT-number in conventional CT, which makes the spectral- CT one of the promising future imaging modalities. One simple way to reduce the scan time in spectral-CT imaging is to reduce the number of views in the acquisition of projection data. But, this may result in poorer SNR and strong streak artifacts which can severely compromise the image quality. In this work, spectral-CT projection data were obtained from a lab-built spectral-CT consisting of a single CdTe photon counting detector, a micro-focus x-ray tube and scan mechanics. For the image reconstruction, we used two iterative image reconstruction methods, the simultaneous iterative reconstruction technique (SIRT) and the total variation minimization based on conjugate gradient method (CG-TV), along with the filtered back-projection (FBP) to compare the image quality. From the imaging of the iodine containing phantoms, we have observed that SIRT and CG-TV are superior to the FBP method in terms of SNR and streak artifacts.

  13. CT & CBCT imaging: assessment of the orbits.

    PubMed

    Hatcher, David C

    2012-11-01

    The orbits can be visualized easily on routine or customized protocols for computed tomography (CT) or cone beam CT (CBCT) scans. Detailed orbital investigations are best performed with 3-dimensional imaging methods. CT scans are preferred for visualizing the osseous orbital anatomy and fissures while magnetic resonance imaging is preferred for evaluating tumors and inflammation. CBCT provides high-resolution anatomic data of the sinonasal spaces, airway, soft tissue surfaces, and bones but does not provide much detail within the soft tissues. This article discusses CBCT imaging of the orbits, osseous anatomy of the orbits, and CBCT investigation of selected orbital pathosis.

  14. Performance benchmarking of liver CT image segmentation and volume estimation

    NASA Astrophysics Data System (ADS)

    Xiong, Wei; Zhou, Jiayin; Tian, Qi; Liu, Jimmy J.; Qi, Yingyi; Leow, Wee Kheng; Han, Thazin; Wang, Shih-chang

    2008-03-01

    In recent years more and more computer aided diagnosis (CAD) systems are being used routinely in hospitals. Image-based knowledge discovery plays important roles in many CAD applications, which have great potential to be integrated into the next-generation picture archiving and communication systems (PACS). Robust medical image segmentation tools are essentials for such discovery in many CAD applications. In this paper we present a platform with necessary tools for performance benchmarking for algorithms of liver segmentation and volume estimation used for liver transplantation planning. It includes an abdominal computer tomography (CT) image database (DB), annotation tools, a ground truth DB, and performance measure protocols. The proposed architecture is generic and can be used for other organs and imaging modalities. In the current study, approximately 70 sets of abdominal CT images with normal livers have been collected and a user-friendly annotation tool is developed to generate ground truth data for a variety of organs, including 2D contours of liver, two kidneys, spleen, aorta and spinal canal. Abdominal organ segmentation algorithms using 2D atlases and 3D probabilistic atlases can be evaluated on the platform. Preliminary benchmark results from the liver segmentation algorithms which make use of statistical knowledge extracted from the abdominal CT image DB are also reported. We target to increase the CT scans to about 300 sets in the near future and plan to make the DBs built available to medical imaging research community for performance benchmarking of liver segmentation algorithms.

  15. 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.

  16. Medical CT image reconstruction accuracy in the presence of metal objects using x-rays up to 1 MeV with x-ray targets of beryllium, carbon, aluminum, copper, and tungsten

    NASA Astrophysics Data System (ADS)

    Clayton, James; Ganguly, Arundhuti; Virshup, Gary

    2012-04-01

    Flat panels imagers based on amorphous silicon technology (a-Si) for digital radiography have been accepted by the medical community as having several advantages over film-based systems. Radiotherapy treatment planning systems employ computed tomographic (CT) data sets and projection images to delineate tumor targets and normal structures that are to be spared from radiation treatment. The accuracy of CT numbers is crucial for radiotherapy dose calculations. Conventional CT scanners operating at kilovoltage X-ray energies typically exhibit significant image reconstruction artifacts in the presence of metal implants in human body. Megavoltage X-ray energies have problems maintaining contrast sensitivity for the same dose as kV X-ray systems. We intend to demonstrate significant improvement in metal artifact reductions and electron density measurements using an amorphous silicon a-Si imager obtained with an X-ray source that can operate at energies up to 1 MeV. We will investigate the ability to maintain contrast sensitivity at this higher X-ray energy by using targets with lower atomic numbers and appropriate amounts of Xray filtration than are typically used as X-ray production targets and filters.

  17. [Medical imaging: its medical economics and recent situation in Japan.].

    PubMed

    Imai, Keiko

    2006-01-01

    Two fields of radiology, medical imaging and radiation therapy, are coded separately in medical fee system, and the health care statistics of 2003 shows that expenditure on the former was 5.2% of the whole medical cost and the latter 0.28%. Introduction of DPC, an abbreviation of Diagnostic Procedure Combination, was carried out in 2003, which was an essential reform of medical fee payment system that have been managed on fee-for-service base throughout, and 22% of beds for acute patients care are under the control of DPC payment in 2006. As medical imaging procedures are basically classified in inclusive payment in DPC system, their accurate statistics cannot be figured out because of the lack of description of individual procedures in DPC bills. Policy-making of medical economics will suffer a great loss from the deficiency of detailed data in published statistics. Important role in clinical diagnoses of CT and MR results an increase of fee paid for them up to more than half of total expenditure on medical imaging. So, dominant reduction of examination fee has been done for MR imaging, especially in 2002, to reduce the total cost of medical imaging. Follows could be featured as major topics of medical imaging in health insurance system, (a) fee is newly assigned for electronic handling of CT-and-MR images, and nuclear medicine, and (b) there is still a mismatch between actual payment and quality of medical facilities. As matters related to medical imaging, the followings should be stressed; (a) numbers of CT and MR units per population are dominantly high among OECD countries, but, those controlled by qualified radiologists are at the average level of those countries, (b) there is a big difference of MR examination quality among medical facilities, and (c) 76% of newly-installed high-end MR units are supplied by foreign industries. Hopefully, there will be an increase in the concern to medical fee payment system and health care cost because they possibly

  18. X-ray CT and NMR imaging of rocks

    SciTech Connect

    Vinegar, H.J.

    1986-03-01

    In little more than a decade, X-ray computerized tomography (CT) and nuclear magnetic resonance (NMR) imaging have become the premier modalities of medical radiology. Both of these imaging techniques also promise to be useful tools in petrophysics and reservoir engineering, because CT and NMR can nondestructively image a host of physical and chemical properties of porous rocks and multiple fluid phases contained within their pores. The images are taken within seconds to minutes, at reservoir temperatures and pressures, with spatial resolution on the millimeter and submillimeter level. The physical properties imaged by the two techniques are complementary. CT images bulk density and effective atomic number. NMR images the nuclide concentration, M/sub 0/, of a variety of nuclei (/sup 1/H, /sup 19/F, /sup 23/Na, /sup 31/P, etc.), their longitudinal and transverse relaxation-time curves (t/sub 1/ and t/sub 2/), and their chemical shift spectra. In rocks, CT images both rock matrix and pore fluids, while NMR images only mobile fluids and the interactions of these mobile fluids with the confining surfaces of the pores.

  19. Liver echinococcus - CT scan (image)

    MedlinePlus

    This upper abdominal CT scan shows multiple cysts in the liver, caused by dog tapeworm (echinococcus). Note the large circular cyst (seen on the left side of the screen) and multiple smaller cysts throughout ...

  20. CT image visualization: a conceptual introduction.

    PubMed

    Furlow, Bryant

    2014-01-01

    Computed tomography (CT) postprocessing produces information-rich diagnostic images, transforming enormous amounts of x-ray attenuation data into clinical information that can assist in diagnosis and treatment. This article briefly reviews the history of the technological evolution of CT imaging equipment and provides a conceptual overview of scan data visualization processes. Trends in and examples of image postprocessing, segmentation, registration and fusion techniques, and computer-aided detection are described. Finally, the uses of these visualization algorithms in selected diagnostic imaging applications are discussed.

  1. CT imaging with a mobile C-arm prototype

    NASA Astrophysics Data System (ADS)

    Cheryauka, Arvi; Tubbs, David; Langille, Vinton; Kalya, Prabhanjana; Smith, Brady; Cherone, Rocco

    2008-03-01

    Mobile X-ray imagery is an omnipresent tool in conventional musculoskeletal and soft tissue applications. The next generation of mobile C-arm systems can provide clinicians of minimally-invasive surgery and pain management procedures with both real-time high-resolution fluoroscopy and intra-operative CT imaging modalities. In this study, we research two C-arm CT experimental system configurations and evaluate their imaging capabilities. In a non-destructive evaluation configuration, the X-ray Tube - Detector assembly is stationary while an imaging object is placed on a rotating table. In a medical imaging configuration, the C-arm gantry moves around the patient and the table. In our research setting, we connect the participating devices through a Mobile X-Ray Imaging Environment known as MOXIE. MOXIE is a set of software applications for internal research at GE Healthcare - Surgery and used to examine imaging performance of experimental systems. Anthropomorphic phantom volume renderings and orthogonal slices of reconstructed images are obtained and displayed. The experimental C-arm CT results show CT-like image quality that may be suitable for interventional procedures, real-time data management, and, therefore, have great potential for effective use on the clinical floor.

  2. CT Image Presentations For Oral Surgery

    NASA Astrophysics Data System (ADS)

    Rhodes, Michael L.; Rothman, Stephen L. G.; Schwarz, Melvyn S.; Tivattanasuk, Eva S.

    1988-06-01

    Reformatted CT images of the mandible and maxilla are described as a planning aid to the surgical implantation of dental fixtures. Precisely scaled and cross referenced axial, oblique, CT generated panorex, and 3-D images are generated to help indicate where and how critical anatomic structures are positioned. This information guides the oral surgeon to those sites where dental implants have optimal osteotic support and least risk to sensitive neural tissue. Oblique images are generated at 1-2 mm increments along the arch of the mandible (or maxilla). Each oblique is oriented perpendicular to the local arch curvature. The adjoining five CT generated panorex views match the patient's mandibular (or maxilla) arch, with each of the views separated by twice the distance between axial CT slices. All views are mutually cross-referenced to show fine detail of the underlying mandibular (or maxilla) structure. Several exams are illustrated and benefit to subsequent surgery is assessed.

  3. Overview of Medical Imaging

    NASA Astrophysics Data System (ADS)

    Hendee, William

    2008-03-01

    The use of radiation probes to image tissues in the human body has progressed through an extraordinary evolution in the past three decades. Beginning with transmission computed tomography in the 1970s, this evolution has included real-time ultrasound, emission computed tomography, magnetic resonance imaging and digital radiography. These advances have recently yielded major improvements in imaging such as multi-detector transmission computed tomography, functional magnetic resonance imaging, dual imaging modalities built on a common platform, and image-guided intervention. These improvements and others have accelerated the usefulness of imaging methods in the early detection, definitive diagnosis, and effective intervention of a wide spectrum of diseases and disabilities. They also have led to increases in radiation doses to patients and the population, an issue of major concern to physicists and physicians. At this time there are four major frontiers for research in medical imaging: (1) molecular imaging; (2) functional imaging; (3) multi-modality imaging; and (4) information management. These research frontiers, together with the use of sophisticated imaging technologies in clinical practice, offer rich professional opportunities for physicists.

  4. Characterizing anatomical variability in breast CT images

    PubMed Central

    Metheany, Kathrine G.; Abbey, Craig K.; Packard, Nathan; Boone, John M.

    2008-01-01

    Previous work [Burgess , Med. Phys. 28, 419–437 (2001)] has shown that anatomical noise in projection mammography results in a power spectrum well modeled over a range of frequencies by a power law, and the exponent (β) of this power law plays a critical role in determining the size at which a growing lesion reaches the threshold for detection. In this study, the authors evaluated the power-law model for breast computed tomography (bCT) images, which can be thought of as thin sections through a three-dimensional (3D) volume. Under the assumption of a 3D power law describing the distribution of attenuation coefficients in the breast parenchyma, the authors derived the relationship between the power-law exponents of bCT and projection images and found it to be βsection=βproj−1. They evaluated this relationship on clinical images by comparing bCT images from a set of 43 patients to Burgess’ findings in mammography. They were able to make a direct comparison for 6 of these patients who had both a bCT exam and a digitized film-screen mammogram. They also evaluated segmented bCT images to investigate the extent to which the bCT power-law exponent can be explained by a binary model of attenuation coefficients based on the different attenuation of glandular and adipose tissue. The power-law model was found to be a good fit for bCT data over frequencies from 0.07to0.45cyc∕mm, where anatomical variability dominates the spectrum. The average exponent for bCT images was 1.86. This value is close to the theoretical prediction using Burgess’ published data for projection mammography and for the limited set of mammography data available from the authors’ patient sample. Exponents from the segmented bCT images (average value: 2.06) were systematically slightly higher than bCT images, with substantial correlation between the two (r=0.84). PMID:18975714

  5. 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.

  6. Mobile medical image retrieval

    NASA Astrophysics Data System (ADS)

    Duc, Samuel; Depeursinge, Adrien; Eggel, Ivan; Müller, Henning

    2011-03-01

    Images are an integral part of medical practice for diagnosis, treatment planning and teaching. Image retrieval has gained in importance mainly as a research domain over the past 20 years. Both textual and visual retrieval of images are essential. In the process of mobile devices becoming reliable and having a functionality equaling that of formerly desktop clients, mobile computing has gained ground and many applications have been explored. This creates a new field of mobile information search & access and in this context images can play an important role as they often allow understanding complex scenarios much quicker and easier than free text. Mobile information retrieval in general has skyrocketed over the past year with many new applications and tools being developed and all sorts of interfaces being adapted to mobile clients. This article describes constraints of an information retrieval system including visual and textual information retrieval from the medical literature of BioMedCentral and of the RSNA journals Radiology and Radiographics. Solutions for mobile data access with an example on an iPhone in a web-based environment are presented as iPhones are frequently used and the operating system is bound to become the most frequent smartphone operating system in 2011. A web-based scenario was chosen to allow for a use by other smart phone platforms such as Android as well. Constraints of small screens and navigation with touch screens are taken into account in the development of the application. A hybrid choice had to be taken to allow for taking pictures with the cell phone camera and upload them for visual similarity search as most producers of smart phones block this functionality to web applications. Mobile information access and in particular access to images can be surprisingly efficient and effective on smaller screens. Images can be read on screen much faster and relevance of documents can be identified quickly through the use of images contained in

  7. The conversion of synchrotron radiation biomedical and medical images into DICOM images

    NASA Astrophysics Data System (ADS)

    Wang, Yunling; Sun, Jianyong; Sun, Jianqi; Zhang, Jianguo

    2014-03-01

    With Synchrotron Radiation light source, there was a lot of imaging methods being developed to perform biomedical and medical imaging researches such as X-ray absorption imaging, phase-contrast imaging and micro-CT imaging. In this presentation, we present an approach to transform a various kinds of SR images into proper DICOM images so that to use a rich of medical processing display software to process and display SR biomedical and medical images. The new generated SR DICOM images can be transferred, stored, processed and displayed by using most of commercial medical imaging software.

  8. Application of region selective embedded zerotree wavelet coder in CT image compression.

    PubMed

    Li, Guoli; Zhang, Jian; Wang, Qunjing; Hu, Cungang; Deng, Na; Li, Jianping

    2005-01-01

    Compression is necessary in medical image preservation because of the huge data quantity. Medical images are different from the common images because of their own characteristics, for example, part of information in CT image is useless, and it's a kind of resource waste to save this part information. The region selective EZW coder was proposed with which only useful part of image was selected and compressed, and the test image provides good result.

  9. Medical imaging systems

    SciTech Connect

    Frangioni, John V

    2012-07-24

    A medical imaging system provides simultaneous rendering of visible light and fluorescent images. The system may employ dyes in a small-molecule form that remains in a subject's blood stream for several minutes, allowing real-time imaging of the subject's circulatory system superimposed upon a conventional, visible light image of the subject. The system may also employ dyes or other fluorescent substances associated with antibodies, antibody fragments, or ligands that accumulate within a region of diagnostic significance. In one embodiment, the system provides an excitation light source to excite the fluorescent substance and a visible light source for general illumination within the same optical guide that is used to capture images. In another embodiment, the system is configured for use in open surgical procedures by providing an operating area that is closed to ambient light. More broadly, the systems described herein may be used in imaging applications where a visible light image may be usefully supplemented by an image formed from fluorescent emissions from a fluorescent substance that marks areas of functional interest.

  10. Prior CT imaging history for patients who undergo PAN CT for acute traumatic injury

    PubMed Central

    Kenter, Jeremy; Blow, Osbert; Krall, Scott P.; Gest, Albert; Smith, Cynthia

    2015-01-01

    Objective. A single PAN scan may provide more radiation to a patient than is felt to be safe within a one-year period. Our objective was to determine how many patients admitted to the trauma service following a PAN scan had prior CT imaging within our six-hospital system. Methods. We performed a secondary analysis of a prospectively collected trauma registry. The study was based at a level-two trauma center and five affiliated hospitals, which comprise 70.6% of all Emergency Department visits within a twelve county region of southern Texas. Electronic medical records were reviewed dating from the point of trauma evaluation back to December 5, 2005 to determine evidence of prior CT imaging. Results. There were 867 patients were admitted to the trauma service between January 1, 2012 and December 31, 2012. 460 (53%) received a PAN scan and were included in the study group. The mean age of the study group was 37.7 ± 1.54 years old, 24.8% were female, and the mean ISS score was 13.4 ± 1.07. The most common mechanism of injury was motor vehicle collision (47%). 65 (14%; 95% CI [11–18]%) of the patients had at least one prior CT. The most common prior studies performed were: CT head (29%; 19–42%), CT Face (29%; 19–42%) and CT Abdomen and Pelvis (18%; 11–30%). Conclusion. Within our trauma registry, 14% of patients had prior CT imaging within our hospital system before their traumatic event and PAN scan. PMID:26056616

  11. Glasses-free 3D viewing systems for medical imaging

    NASA Astrophysics Data System (ADS)

    Magalhães, Daniel S. F.; Serra, Rolando L.; Vannucci, André L.; Moreno, Alfredo B.; Li, Li M.

    2012-04-01

    In this work we show two different glasses-free 3D viewing systems for medical imaging: a stereoscopic system that employs a vertically dispersive holographic screen (VDHS) and a multi-autostereoscopic system, both used to produce 3D MRI/CT images. We describe how to obtain a VDHS in holographic plates optimized for this application, with field of view of 7 cm to each eye and focal length of 25 cm, showing images done with the system. We also describe a multi-autostereoscopic system, presenting how it can generate 3D medical imaging from viewpoints of a MRI or CT image, showing results of a 3D angioresonance image.

  12. TU-D-BRB-01: Dual-Energy CT: Techniques in Acquisition and Image Processing.

    PubMed

    Pelc, N

    2016-06-01

    Dual-energy CT technology is becoming increasingly available to the medical imaging community. In addition, several models of CT simulators sold for use in radiation therapy departments now feature dual-energy technology. The images provided by dual-energy CT scanners add new information to the radiation treatment planning process; multiple spectral components can be used to separate and identify material composition as well as generate virtual monoenergetic images. In turn, this information could be used to investigate pathologic processes, separate the properties of contrast agents from soft tissues, assess tissue response to therapy, and other applications of therapeutic interest. Additionally, the decomposition of materials in images could directly integrate with and impact the accuracy of dose calculation algorithms. This symposium will explore methods of generating dual-energy CT images, spectral and image analysis algorithms, current and future applications of interest in oncologic imaging, and unique considerations when using dualenergy CT images in the radiation treatment planning process.

  13. TU-D-BRB-02: Dual-Energy CT: Applications in Oncologic Imaging.

    PubMed

    Schoepf, U

    2016-06-01

    Dual-energy CT technology is becoming increasingly available to the medical imaging community. In addition, several models of CT simulators sold for use in radiation therapy departments now feature dual-energy technology. The images provided by dual-energy CT scanners add new information to the radiation treatment planning process; multiple spectral components can be used to separate and identify material composition as well as generate virtual monoenergetic images. In turn, this information could be used to investigate pathologic processes, separate the properties of contrast agents from soft tissues, assess tissue response to therapy, and other applications of therapeutic interest. Additionally, the decomposition of materials in images could directly integrate with and impact the accuracy of dose calculation algorithms. This symposium will explore methods of generating dual-energy CT images, spectral and image analysis algorithms, current and future applications of interest in oncologic imaging, and unique considerations when using dualenergy CT images in the radiation treatment planning process.

  14. [A novel denoising approach to SVD filtering based on DCT and PCA in CT image].

    PubMed

    Feng, Fuqiang; Wang, Jun

    2013-10-01

    Because of various effects of the imaging mechanism, noises are inevitably introduced in medical CT imaging process. Noises in the images will greatly degrade the quality of images and bring difficulties to clinical diagnosis. This paper presents a new method to improve singular value decomposition (SVD) filtering performance in CT image. Filter based on SVD can effectively analyze characteristics of the image in horizontal (and/or vertical) directions. According to the features of CT image, we can make use of discrete cosine transform (DCT) to extract the region of interest and to shield uninterested region so as to realize the extraction of structure characteristics of the image. Then we transformed SVD to the image after DCT, constructing weighting function for image reconstruction adaptively weighted. The algorithm for the novel denoising approach in this paper was applied in CT image denoising, and the experimental results showed that the new method could effectively improve the performance of SVD filtering.

  15. Wavelets in medical imaging

    SciTech Connect

    Zahra, Noor e; Sevindir, Huliya A.; Aslan, Zafar; Siddiqi, A. H.

    2012-07-17

    The aim of this study is to provide emerging applications of wavelet methods to medical signals and images, such as electrocardiogram, electroencephalogram, functional magnetic resonance imaging, computer tomography, X-ray and mammography. Interpretation of these signals and images are quite important. Nowadays wavelet methods have a significant impact on the science of medical imaging and the diagnosis of disease and screening protocols. Based on our initial investigations, future directions include neurosurgical planning and improved assessment of risk for individual patients, improved assessment and strategies for the treatment of chronic pain, improved seizure localization, and improved understanding of the physiology of neurological disorders. We look ahead to these and other emerging applications as the benefits of this technology become incorporated into current and future patient care. In this chapter by applying Fourier transform and wavelet transform, analysis and denoising of one of the important biomedical signals like EEG is carried out. The presence of rhythm, template matching, and correlation is discussed by various method. Energy of EEG signal is used to detect seizure in an epileptic patient. We have also performed denoising of EEG signals by SWT.

  16. Wavelets in medical imaging

    NASA Astrophysics Data System (ADS)

    Zahra, Noor e.; Sevindir, Hulya Kodal; Aslan, Zafer; Siddiqi, A. H.

    2012-07-01

    The aim of this study is to provide emerging applications of wavelet methods to medical signals and images, such as electrocardiogram, electroencephalogram, functional magnetic resonance imaging, computer tomography, X-ray and mammography. Interpretation of these signals and images are quite important. Nowadays wavelet methods have a significant impact on the science of medical imaging and the diagnosis of disease and screening protocols. Based on our initial investigations, future directions include neurosurgical planning and improved assessment of risk for individual patients, improved assessment and strategies for the treatment of chronic pain, improved seizure localization, and improved understanding of the physiology of neurological disorders. We look ahead to these and other emerging applications as the benefits of this technology become incorporated into current and future patient care. In this chapter by applying Fourier transform and wavelet transform, analysis and denoising of one of the important biomedical signals like EEG is carried out. The presence of rhythm, template matching, and correlation is discussed by various method. Energy of EEG signal is used to detect seizure in an epileptic patient. We have also performed denoising of EEG signals by SWT.

  17. Monte Carlo simulations of medical imaging modalities

    SciTech Connect

    Estes, G.P.

    1998-09-01

    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 computer 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.

  18. CT Image Processing Using Public Digital Networks

    PubMed Central

    Rhodes, Michael L.; Azzawi, Yu-Ming; Quinn, John F.; Glenn, William V.; Rothman, Stephen L.G.

    1984-01-01

    Nationwide commercial computer communication is now commonplace for those applications where digital dialogues are generally short and widely distributed, and where bandwidth does not exceed that of dial-up telephone lines. Image processing using such networks is prohibitive because of the large volume of data inherent to digital pictures. With a blend of increasing bandwidth and distributed processing, network image processing becomes possible. This paper examines characteristics of a digital image processing service for a nationwide network of CT scanner installations. Issues of image transmission, data compression, distributed processing, software maintenance, and interfacility communication are also discussed. Included are results that show the volume and type of processing experienced by a network of over 50 CT scanners for the last 32 months.

  19. CT imaging, then and now: a 30-year review of the economics of computed tomography.

    PubMed

    Stockburger, Wayne T

    2004-01-01

    The first computed tomography (CT) scanner in the US was installed in June 1973 at the Mayo Clinic in Rochester, MN. By the end of 1974, 44 similar systems had been installed at medical facilities around the country. Less than 4 years after the introduction of CT imaging in the US, at least 400 CT systems had been installed. The practice of pneumoencephalography was eliminated. The use of nuclear medicine brain scans significantly diminished. At the time, CT imaging was limited to head studies, but with the introduction of contrast agents and full body CT systems the changes in the practice of medicine became even more significant. CT imaging was hailed by the US medical community as the greatest advance in radiology since the discovery of x-rays. But the rapid spread of CT systems, their frequency of use, and the associated increase in healthcare costs combined to draw the attention of decision-makers within the federal and state governments, specifically to establish policies regarding the acquisition and use of diagnostic technologies. Initially, CT imaging was limited to neurological applications, but in the 30 years since its inception, capabilities and applications have been expanded as a result of the advancements in technology and software development. While neurological disorders are still a common reason for CT imaging, many other medical disciplines (oncology, emergency medicine, orthopedics, etc.) have found CT imaging to be the definitive tool for diagnostic information. As such, the clinical demand for CT imaging has steadily increased. Economically, the development of CT imaging has been one of success, even in the face of governmental action to restrict its acquisition and utilization by healthcare facilities. CTimaging has increased the cost of healthcare, but in turn has added unquantifiable value to the practice of medicine in the US.

  20. CT imaging of enhanced oil recovery experiments

    SciTech Connect

    Gall, B.L.

    1992-12-01

    X-ray computerized tomography (Cr) has been used to study fluid distributions during chemical enhanced oil recovery experiments. Four CT-monitored corefloods were conducted, and oil saturation distributions were calculated at various stages of the experiments. Results suggested that this technique could add significant information toward interpretation and evaluation of surfactant/polymer EOR recovery methods. CT-monitored tracer tests provided information about flow properties in the core samples. Nonuniform fluid advance could be observed, even in core that appeared uniform by visual inspection. Porosity distribution maps based on CT density calculations also showed the presence of different porosity layers that affected fluid movement through the cores. Several types of CT-monitored corefloods were conducted. Comparisons were made for CT-monitored corefloods using chemical systems that were highly successful in reducing residual oil saturations in laboratory experiments and less successful systems. Changes were made in surfactant formulation and in concentration of the mobility control polymer. Use of a poor mobility control agent failed to move oil that was not initially displaced by the injected surfactant solution; even when a good'' surfactant system was used. Use of a less favorable surfactant system with adequate mobility control could produce as much oil as the use of a good surfactant system with inadequate mobility control. The role of mobility control, therefore, becomes a critical parameter for successful application of chemical EOR. Continuation of efforts to use CT imaging in connection with chemical EOR evaluations is recommended.

  1. CT imaging of enhanced oil recovery experiments

    SciTech Connect

    Gall, B.L.

    1992-12-01

    X-ray computerized tomography (Cr) has been used to study fluid distributions during chemical enhanced oil recovery experiments. Four CT-monitored corefloods were conducted, and oil saturation distributions were calculated at various stages of the experiments. Results suggested that this technique could add significant information toward interpretation and evaluation of surfactant/polymer EOR recovery methods. CT-monitored tracer tests provided information about flow properties in the core samples. Nonuniform fluid advance could be observed, even in core that appeared uniform by visual inspection. Porosity distribution maps based on CT density calculations also showed the presence of different porosity layers that affected fluid movement through the cores. Several types of CT-monitored corefloods were conducted. Comparisons were made for CT-monitored corefloods using chemical systems that were highly successful in reducing residual oil saturations in laboratory experiments and less successful systems. Changes were made in surfactant formulation and in concentration of the mobility control polymer. Use of a poor mobility control agent failed to move oil that was not initially displaced by the injected surfactant solution; even when a ``good`` surfactant system was used. Use of a less favorable surfactant system with adequate mobility control could produce as much oil as the use of a good surfactant system with inadequate mobility control. The role of mobility control, therefore, becomes a critical parameter for successful application of chemical EOR. Continuation of efforts to use CT imaging in connection with chemical EOR evaluations is recommended.

  2. Fast parallel algorithm for CT image reconstruction.

    PubMed

    Flores, Liubov A; Vidal, Vicent; Mayo, Patricia; Rodenas, Francisco; Verdú, Gumersindo

    2012-01-01

    In X-ray computed tomography (CT) the X rays are used to obtain the projection data needed to generate an image of the inside of an object. The image can be generated with different techniques. Iterative methods are more suitable for the reconstruction of images with high contrast and precision in noisy conditions and from a small number of projections. Their use may be important in portable scanners for their functionality in emergency situations. However, in practice, these methods are not widely used due to the high computational cost of their implementation. In this work we analyze iterative parallel image reconstruction with the Portable Extensive Toolkit for Scientific computation (PETSc).

  3. SPARSE: Seed Point Auto-Generation for Random Walks Segmentation Enhancement in medical inhomogeneous targets delineation of morphological MR and CT images.

    PubMed

    Chen, Haibin; Zhen, Xin; Gu, Xuejun; Yan, Hao; Cervino, Laura; Xiao, Yang; Zhou, Linghong

    2015-03-08

    In medical image processing, robust segmentation of inhomogeneous targets is a challenging problem. Because of the complexity and diversity in medical images, the commonly used semiautomatic segmentation algorithms usually fail in the segmentation of inhomogeneous objects. In this study, we propose a novel algorithm imbedded with a seed point autogeneration for random walks segmentation enhancement, namely SPARSE, for better segmentation of inhomogeneous objects. With a few user-labeled points, SPARSE is able to generate extended seed points by estimating the probability of each voxel with respect to the labels. The random walks algorithm is then applied upon the extended seed points to achieve improved segmentation result. SPARSE is implemented under the compute unified device architecture (CUDA) programming environment on graphic processing unit (GPU) hardware platform. Quantitative evaluations are performed using clinical homogeneous and inhomogeneous cases. It is found that the SPARSE can greatly decrease the sensitiveness to initial seed points in terms of location and quantity, as well as the freedom of selecting parameters in edge weighting function. The evaluation results of SPARSE also demonstrate substantial improvements in accuracy and robustness to inhomogeneous target segmentation over the original random walks algorithm.

  4. Medical Image Analysis Facility

    NASA Technical Reports Server (NTRS)

    1978-01-01

    To improve the quality of photos sent to Earth by unmanned spacecraft. NASA's Jet Propulsion Laboratory (JPL) developed a computerized image enhancement process that brings out detail not visible in the basic photo. JPL is now applying this technology to biomedical research in its Medical lrnage Analysis Facility, which employs computer enhancement techniques to analyze x-ray films of internal organs, such as the heart and lung. A major objective is study of the effects of I stress on persons with heart disease. In animal tests, computerized image processing is being used to study coronary artery lesions and the degree to which they reduce arterial blood flow when stress is applied. The photos illustrate the enhancement process. The upper picture is an x-ray photo in which the artery (dotted line) is barely discernible; in the post-enhancement photo at right, the whole artery and the lesions along its wall are clearly visible. The Medical lrnage Analysis Facility offers a faster means of studying the effects of complex coronary lesions in humans, and the research now being conducted on animals is expected to have important application to diagnosis and treatment of human coronary disease. Other uses of the facility's image processing capability include analysis of muscle biopsy and pap smear specimens, and study of the microscopic structure of fibroprotein in the human lung. Working with JPL on experiments are NASA's Ames Research Center, the University of Southern California School of Medicine, and Rancho Los Amigos Hospital, Downey, California.

  5. Dynamic CT perfusion image data compression for efficient parallel processing.

    PubMed

    Barros, Renan Sales; Olabarriaga, Silvia Delgado; Borst, Jordi; van Walderveen, Marianne A A; Posthuma, Jorrit S; Streekstra, Geert J; van Herk, Marcel; Majoie, Charles B L M; Marquering, Henk A

    2016-03-01

    The increasing size of medical imaging data, in particular time series such as CT perfusion (CTP), requires new and fast approaches to deliver timely results for acute care. Cloud architectures based on graphics processing units (GPUs) can provide the processing capacity required for delivering fast results. However, the size of CTP datasets makes transfers to cloud infrastructures time-consuming and therefore not suitable in acute situations. To reduce this transfer time, this work proposes a fast and lossless compression algorithm for CTP data. The algorithm exploits redundancies in the temporal dimension and keeps random read-only access to the image elements directly from the compressed data on the GPU. To the best of our knowledge, this is the first work to present a GPU-ready method for medical image compression with random access to the image elements from the compressed data.

  6. Patient position verification using CT images.

    PubMed

    Kress, J; Minohara, S; Endo, M; Debus, J; Kanai, T

    1999-06-01

    The use of ions in the radiotherapy of cancer patients requires an accurate patient positioning in order to exploit its potential benefits. Using CT images as the basis for the setup verification offers the advantage of a high in-plane resolution in combination with a geometrically accurate, volumetric information. Before each fraction a single CT slice is acquired at the isocenter level after the positioning procedure. This single slice is registered to the planning CT cube using automated image registration algorithms. Thus any erreonous translation or rotation can be detected and quantified. The registration process involves the interpolation of the volumetric data, the calculation of an energy function, and the minimization of this energy function. Several data interpolation functions as well as minimization algorithms were compared. CT studies with a head phantom were performed in which defined translations and rotations were simulated by moving a motor-driven treatment chair. Different slice thicknesses and anatomical sites were studied to investigate their potential influence on the registration accuracy. The accuracy of the registration was found to be a fraction of a voxel size for suitable combinations of algorithms (typically better than 0.16 mm/deg). A significant dependancy of the registration accuracy on the CT slice thickness and the anatomical site was found (the accuracy ranges from 0.05 mm/deg to 0.16 mm/deg depending on the site). The calculation time is dependant on the used algorithms and the magnitude of the setup error. For the standard combination of algorithms as proposed by the authors (Downhill Simplex minimization with Trilinear interpolation) the typical calculation time is about 20 s for a Sun UltraSPARC processor. Taking into account the mechanical accuracy of the setup device (motor-driven chair) the registration of CT images is thus a useful tool for detecting and quantifying any significant error in the patient position.

  7. 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.

  8. 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.

  9. Medical alert bracelet (image)

    MedlinePlus

    People with diabetes should always wear a medical alert bracelet or necklace that emergency medical workers will ... People with diabetes should always wear a medical alert bracelet or necklace that emergency medical workers will ...

  10. Morphology supporting function: attenuation correction for SPECT/CT, PET/CT, and PET/MR imaging

    PubMed Central

    Lee, Tzu C.; Alessio, Adam M.; Miyaoka, Robert M.; Kinahan, Paul E.

    2017-01-01

    Both SPECT, and in particular PET, are unique in medical imaging for their high sensitivity and direct link to a physical quantity, i.e. radiotracer concentration. This gives PET and SPECT imaging unique capabilities for accurately monitoring disease activity for the purposes of clinical management or therapy development. However, to achieve a direct quantitative connection between the underlying radiotracer concentration and the reconstructed image values several confounding physical effects have to be estimated, notably photon attenuation and scatter. With the advent of dual-modality SPECT/CT, PET/CT, and PET/MR scanners, the complementary CT or MR image data can enable these corrections, although there are unique challenges for each combination. This review covers the basic physics underlying photon attenuation and scatter and summarizes technical considerations for multimodal imaging with regard to PET and SPECT quantification and methods to address the challenges for each multimodal combination. PMID:26576737

  11. 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.

  12. A cloud-based medical image repository

    NASA Astrophysics Data System (ADS)

    Maeder, Anthony J.; Planitz, Birgit M.; El Rifai, Diaa

    2012-02-01

    Many widely used digital medical image collections have been established but these are generally used as raw data sources without related image analysis toolsets. Providing associated functionality to allow specific types of operations to be performed on these images has proved beneficial in some cases (e.g. brain image registration and atlases). However, toolset development to provide generic image analysis functions on medical images has tended to be ad hoc, with Open Source options proliferating (e.g. ITK). Our Automated Medical Image Collection Annotation (AMICA) system is both an image repository, to which the research community can contribute image datasets, and a search/retrieval system that uses automated image annotation. AMICA was designed for the Windows Azure platform to leverage the flexibility and scalability of the cloud. It is intended that AMICA will expand beyond its initial pilot implementation (for brain CT, MR images) to accommodate a wide range of modalities and anatomical regions. This initiative aims to contribute to advances in clinical research by permitting a broader use and reuse of medical image data than is currently attainable. For example, cohort studies for cases with particular physiological or phenotypical profiles will be able to source and include enough cases to provide high statistical power, allowing more individualised risk factors to be assessed and thus allowing screening and staging processes to be optimised. Also, education, training and credentialing of clinicians in image interpretation, will be more effective because it will be possible to select instances of images with specific visual aspects, or correspond to types of cases where reading performance improvement is desirable.

  13. Dual source CT (DSCT) imaging of obese patients: evaluation of CT number accuracy, uniformity, and noise

    NASA Astrophysics Data System (ADS)

    Walz-Flannigan, A.; Schmidt, B.,; Apel, A.; Eusemann, C.; Yu, L.; McCollough, C. H.

    2009-02-01

    Obese patients present challenges in obtaining sufficient x-ray exposure over reasonable time periods for acceptable CT image quality. To overcome this limitation, the exposure can be divided between two x-ray sources using a dualsource (DS) CT system. However, cross-scatter issues in DS CT may also compromise image quality. We evaluated a DS CT system optimized for imaging obese patients, comparing the CT number accuracy and uniformity to the same images obtained with a single-source (SS) acquisition. The imaging modes were compared using both solid cylindrical PMMA phantoms and a semi-anthropomorphic thorax phantom fitted with extension rings to simulate different size patients. Clinical protocols were used and CTDIvol and kVp were held constant between SS and DS modes. Results demonstrated good agreement in CT number between SS and DS modes in CT number, with the DS mode showing better axial uniformity for the largest phantoms.

  14. Automated Image Retrieval of Chest CT Images Based on Local Grey Scale Invariant Features.

    PubMed

    Arrais Porto, Marcelo; Cordeiro d'Ornellas, Marcos

    2015-01-01

    Textual-based tools are regularly employed to retrieve medical images for reading and interpretation using current retrieval Picture Archiving and Communication Systems (PACS) but pose some drawbacks. All-purpose content-based image retrieval (CBIR) systems are limited when dealing with medical images and do not fit well into PACS workflow and clinical practice. This paper presents an automated image retrieval approach for chest CT images based local grey scale invariant features from a local database. Performance was measured in terms of precision and recall, average retrieval precision (ARP), and average retrieval rate (ARR). Preliminary results have shown the effectiveness of the proposed approach. The prototype is also a useful tool for radiology research and education, providing valuable information to the medical and broader healthcare community.

  15. Intelligent distributed medical image management

    NASA Astrophysics Data System (ADS)

    Garcia, Hong-Mei C.; Yun, David Y.

    1995-05-01

    The rapid advancements in high performance global communication have accelerated cooperative image-based medical services to a new frontier. Traditional image-based medical services such as radiology and diagnostic consultation can now fully utilize multimedia technologies in order to provide novel services, including remote cooperative medical triage, distributed virtual simulation of operations, as well as cross-country collaborative medical research and training. Fast (efficient) and easy (flexible) retrieval of relevant images remains a critical requirement for the provision of remote medical services. This paper describes the database system requirements, identifies technological building blocks for meeting the requirements, and presents a system architecture for our target image database system, MISSION-DBS, which has been designed to fulfill the goals of Project MISSION (medical imaging support via satellite integrated optical network) -- an experimental high performance gigabit satellite communication network with access to remote supercomputing power, medical image databases, and 3D visualization capabilities in addition to medical expertise anywhere and anytime around the country. The MISSION-DBS design employs a synergistic fusion of techniques in distributed databases (DDB) and artificial intelligence (AI) for storing, migrating, accessing, and exploring images. The efficient storage and retrieval of voluminous image information is achieved by integrating DDB modeling and AI techniques for image processing while the flexible retrieval mechanisms are accomplished by combining attribute- based and content-based retrievals.

  16. Functional CT imaging of prostate cancer

    NASA Astrophysics Data System (ADS)

    Henderson, Elizabeth; Milosevic, Michael F.; Haider, Masoom A.; Yeung, Ivan W. T.

    2003-09-01

    The purpose of this paper is to investigate the distribution of blood flow (F), mean capillary transit time (Tc), capillary permeability (PS) and blood volume (vb) in prostate cancer using contrast-enhanced CT. Nine stage T2-T3 prostate cancer patients were enrolled in the study. Following bolus injection of a contrast agent, a time series of CT images of the prostate was acquired. Functional maps showing the distribution of F, Tc, PS and vb within the prostate were generated using a distributed parameter tracer kinetic model, the adiabatic approximation to the tissue homogeneity model. The precision of the maps was assessed using covariance matrix analysis. Finally, maps were compared to the findings of standard clinical investigations. Eight of the functional maps demonstrated regions of increased F, PS and vb, the locations of which were consistent with the results of standard clinical investigations. However, model parameters other than F could only be measured precisely within regions of high F. In conclusion functional CT images of cancer-containing prostate glands demonstrate regions of elevated F, PS and vb. However, caution should be used when applying a complex tracer kinetic model to the study of prostate cancer since not all parameters can be measured precisely in all areas.

  17. Method for transforming CT images for attenuation correction in PET/CT imaging

    SciTech Connect

    Carney, Jonathan P.J.; Townsend, David W.; Rappoport, Vitaliy; Bendriem, Bernard

    2006-04-15

    A tube-voltage-dependent scheme is presented for transforming Hounsfield units (HU) measured by different computed tomography (CT) scanners at different x-ray tube voltages (kVp) to 511 keV linear attenuation values for attenuation correction in positron emission tomography (PET) data reconstruction. A Gammex 467 electron density CT phantom was imaged using a Siemens Sensation 16-slice CT, a Siemens Emotion 6-slice CT, a GE Lightspeed 16-slice CT, a Hitachi CXR 4-slice CT, and a Toshiba Aquilion 16-slice CT at kVp ranging from 80 to 140 kVp. All of these CT scanners are also available in combination with a PET scanner as a PET/CT tomograph. HU obtained for various reference tissue substitutes in the phantom were compared with the known linear attenuation values at 511 keV. The transformation, appropriate for lung, soft tissue, and bone, yields the function 9.6x10{sup -5}{center_dot}(HU+1000) below a threshold of {approx}50 HU and a{center_dot}(HU+1000)+b above the threshold, where a and b are fixed parameters that depend on the kVp setting. The use of the kVp-dependent scaling procedure leads to a significant improvement in reconstructed PET activity levels in phantom measurements, resolving errors of almost 40% otherwise seen for the case of dense bone phantoms at 80 kVp. Results are also presented for patient studies involving multiple CT scans at different kVp settings, which should all lead to the same 511 keV linear attenuation values. A linear fit to values obtained from 140 kVp CT images using the kVp-dependent scaling plotted as a function of the corresponding values obtained from 80 kVp CT images yielded y=1.003x-0.001 with an R{sup 2} value of 0.999, indicating that the same values are obtained to a high degree of accuracy.

  18. MR to CT Registration of Brains using Image Synthesis.

    PubMed

    Roy, Snehashis; Carass, Aaron; Jog, Amod; Prince, Jerry L; Lee, Junghoon

    2014-03-21

    Computed tomography (CT) is the standard 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.

  19. 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.

  20. Combined SPECT/CT and PET/CT for breast imaging

    NASA Astrophysics Data System (ADS)

    Russo, Paolo; Larobina, Michele; Di Lillo, Francesca; Del Vecchio, Silvana; Mettivier, Giovanni

    2016-02-01

    In the field of nuclear medicine imaging, breast imaging for cancer diagnosis is still mainly based on 2D imaging techniques. Three-dimensional tomographic imaging with whole-body PET or SPECT scanners, when used for imaging the breast, has performance limits in terms of spatial resolution and sensitivity, which can be overcome only with a dedicated instrumentation. However, only few hybrid imaging systems for PET/CT or SPECT/CT dedicated to the breast have been developed in the last decade, providing complementary functional and anatomical information on normal breast tissue and lesions. These systems are still under development and clinical trials on just few patients have been reported; no commercial dedicated breast PET/CT or SPECT/CT is available. This paper reviews combined dedicated breast PET/CT and SPECT/CT scanners described in the recent literature, with focus on their technological aspects.

  1. Recommendations of the Spanish Societies of Radiation Oncology (SEOR), Nuclear Medicine & Molecular Imaging (SEMNiM), and Medical Physics (SEFM) on 18F-FDG PET-CT for radiotherapy treatment planning

    PubMed Central

    Caballero Perea, Begoña; Villegas, Antonio Cabrera; Rodríguez, José Miguel Delgado; Velloso, María José García; Vicente, Ana María García; Cabrerizo, Carlos Huerga; López, Rosa Morera; Romasanta, Luis Alberto Pérez; Beltrán, Moisés Sáez

    2012-01-01

    Positron emission tomography (PET) with 18F-fluorodeoxyglucose (FDG) is a valuable tool for diagnosing and staging malignant lesions. The fusion of PET and computed tomography (CT) yields images that contain both metabolic and morphological information, which, taken together, have improved the diagnostic precision of PET in oncology. The main imaging modality for planning radiotherapy treatment is CT. However, PET-CT is an emerging modality for use in planning treatments because it allows for more accurate treatment volume definition. The use of PET-CT for treatment planning is highly complex, and protocols and standards for its use are still being developed. It seems probable that PET-CT will eventually replace current CT-based planning methods, but this will require a full understanding of the relevant technical aspects of PET-CT planning. The aim of the present document is to review these technical aspects and to provide recommendations for clinical use of this imaging modality in the radiotherapy planning process. PMID:24377032

  2. Recommendations of the Spanish Societies of Radiation Oncology (SEOR), Nuclear Medicine & Molecular Imaging (SEMNiM), and Medical Physics (SEFM) on (18)F-FDG PET-CT for radiotherapy treatment planning.

    PubMed

    Caballero Perea, Begoña; Villegas, Antonio Cabrera; Rodríguez, José Miguel Delgado; Velloso, María José García; Vicente, Ana María García; Cabrerizo, Carlos Huerga; López, Rosa Morera; Romasanta, Luis Alberto Pérez; Beltrán, Moisés Sáez

    2012-01-01

    Positron emission tomography (PET) with (18)F-fluorodeoxyglucose (FDG) is a valuable tool for diagnosing and staging malignant lesions. The fusion of PET and computed tomography (CT) yields images that contain both metabolic and morphological information, which, taken together, have improved the diagnostic precision of PET in oncology. The main imaging modality for planning radiotherapy treatment is CT. However, PET-CT is an emerging modality for use in planning treatments because it allows for more accurate treatment volume definition. The use of PET-CT for treatment planning is highly complex, and protocols and standards for its use are still being developed. It seems probable that PET-CT will eventually replace current CT-based planning methods, but this will require a full understanding of the relevant technical aspects of PET-CT planning. The aim of the present document is to review these technical aspects and to provide recommendations for clinical use of this imaging modality in the radiotherapy planning process.

  3. Medical imaging 4

    SciTech Connect

    Loew, M.H. )

    1990-01-01

    This book is covered under the following topics: human visual pattern recognition, fractals, rules, and segments, three-dimensional image processing, MRI, MRI and mammography, clinical applications 1, angiography, image processing systems, image processing poster session.

  4. 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.

  5. 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

  6. 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.

  7. Medical hyperspectral imaging: a review.

    PubMed

    Lu, Guolan; Fei, Baowei

    2014-01-01

    Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application.

  8. Medical hyperspectral imaging: a review

    PubMed Central

    Lu, Guolan; Fei, Baowei

    2014-01-01

    Abstract. Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications, especially in disease diagnosis and image-guided surgery. HSI acquires a three-dimensional dataset called hypercube, with two spatial dimensions and one spectral dimension. Spatially resolved spectral imaging obtained by HSI provides diagnostic information about the tissue physiology, morphology, and composition. This review paper presents an overview of the literature on medical hyperspectral imaging technology and its applications. The aim of the survey is threefold: an introduction for those new to the field, an overview for those working in the field, and a reference for those searching for literature on a specific application. PMID:24441941

  9. Sci—Thur PM: Imaging — 06: Canada's National Computed Tomography (CT) Survey

    SciTech Connect

    Wardlaw, GM; Martel, N; Blackler, W; Asselin, J-F

    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 good 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.

  10. Image quality in CT: From physical measurements to model observers.

    PubMed

    Verdun, F R; Racine, D; Ott, J G; Tapiovaara, M J; Toroi, P; Bochud, F O; Veldkamp, W J H; Schegerer, A; Bouwman, R W; Giron, I Hernandez; Marshall, N W; Edyvean, S

    2015-12-01

    Evaluation of image quality (IQ) in Computed Tomography (CT) is important to ensure that diagnostic questions are correctly answered, whilst keeping radiation dose to the patient as low as is reasonably possible. The assessment of individual aspects of IQ is already a key component of routine quality control of medical x-ray devices. These values together with standard dose indicators can be used to give rise to 'figures of merit' (FOM) to characterise the dose efficiency of the CT scanners operating in certain modes. The demand for clinically relevant IQ characterisation has naturally increased with the development of CT technology (detectors efficiency, image reconstruction and processing), resulting in the adaptation and evolution of assessment methods. The purpose of this review is to present the spectrum of various methods that have been used to characterise image quality in CT: from objective measurements of physical parameters to clinically task-based approaches (i.e. model observer (MO) approach) including pure human observer approach. When combined together with a dose indicator, a generalised dose efficiency index can be explored in a framework of system and patient dose optimisation. We will focus on the IQ methodologies that are required for dealing with standard reconstruction, but also for iterative reconstruction algorithms. With this concept the previously used FOM will be presented with a proposal to update them in order to make them relevant and up to date with technological progress. The MO that objectively assesses IQ for clinically relevant tasks represents the most promising method in terms of radiologist sensitivity performance and therefore of most relevance in the clinical environment.

  11. 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…

  12. Application of curvelet transform for denoising of CT images

    NASA Astrophysics Data System (ADS)

    Ławicki, Tomasz; Zhirnova, Oxana

    2015-09-01

    The paper presents a method of noise reduction in CT images by the curvelet transform. Noise affects the ability to visualize pathologic qualities and the living tissues structure in CT. Noise in CT images depends on the amount of discrete x-ray photons reaching the detector. In the CT images, noise is responsible for visibility reduction the low contrast areas and objects. Noisy picture may not be properly interpreted by a physician, especially for the case of detection of pathological changes in tissues. The tests were performed with the Shepp-Logan test image with additive Gaussian noise.

  13. Neural network and its application to CT imaging

    SciTech Connect

    Nikravesh, M.; Kovscek, A.R.; Patzek, T.W.

    1997-02-01

    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.

  14. 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.

  15. 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.

  16. Automated vertebra identification in CT images

    NASA Astrophysics Data System (ADS)

    Ehm, Matthias; Klinder, Tobias; Kneser, Reinhard; Lorenz, Cristian

    2009-02-01

    In this paper, we describe and compare methods for automatically identifying individual vertebrae in arbitrary CT images. The identification is an essential precondition for a subsequent model-based segmentation, which is used in a wide field of orthopedic, neurological, and oncological applications, e.g., spinal biopsies or the insertion of pedicle screws. Since adjacent vertebrae show similar characteristics, an automated labeling of the spine column is a very challenging task, especially if no surrounding reference structures can be taken into account. Furthermore, vertebra identification is complicated due to the fact that many images are bounded to a very limited field of view and may contain only few vertebrae. We propose and evaluate two methods for automatically labeling the spine column by evaluating similarities between given models and vertebral objects. In one method, object boundary information is taken into account by applying a Generalized Hough Transform (GHT) for each vertebral object. In the other method, appearance models containing mean gray value information are registered to each vertebral object using cross and local correlation as similarity measures for the optimization function. The GHT is advantageous in terms of computational performance but cuts back concerning the identification rate. A correct labeling of the vertebral column has been successfully performed on 93% of the test set consisting of 63 disparate input images using rigid image registration with local correlation as similarity measure.

  17. Compressive sensing in medical imaging

    PubMed Central

    Graff, Christian G.; Sidky, Emil Y.

    2015-01-01

    The promise of compressive sensing, exploitation of compressibility to achieve high quality image reconstructions with less data, has attracted a great deal of attention in the medical imaging community. At the Compressed Sensing Incubator meeting held in April 2014 at OSA Headquarters in Washington, DC, presentations were given summarizing some of the research efforts ongoing in compressive sensing for x-ray computed tomography and magnetic resonance imaging systems. This article provides an expanded version of these presentations. Sparsity-exploiting reconstruction algorithms that have gained popularity in the medical imaging community are studied, and examples of clinical applications that could benefit from compressive sensing ideas are provided. The current and potential future impact of compressive sensing on the medical imaging field is discussed. PMID:25968400

  18. Machine Learning for Medical Imaging.

    PubMed

    Erickson, Bradley J; Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy L

    2017-01-01

    Machine learning is a technique for recognizing patterns that can be applied to medical images. Although it is a powerful tool that can help in rendering medical diagnoses, it can be misapplied. Machine learning typically begins with the machine learning algorithm system computing the image features that are believed to be of importance in making the prediction or diagnosis of interest. The machine learning algorithm system then identifies the best combination of these image features for classifying the image or computing some metric for the given image region. There are several methods that can be used, each with different strengths and weaknesses. There are open-source versions of most of these machine learning methods that make them easy to try and apply to images. Several metrics for measuring the performance of an algorithm exist; however, one must be aware of the possible associated pitfalls that can result in misleading metrics. More recently, deep learning has started to be used; this method has the benefit that it does not require image feature identification and calculation as a first step; rather, features are identified as part of the learning process. Machine learning has been used in medical imaging and will have a greater influence in the future. Those working in medical imaging must be aware of how machine learning works. (©)RSNA, 2017.

  19. 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.

  20. Low dose CT image restoration using a database of image patches.

    PubMed

    Ha, Sungsoo; Mueller, Klaus

    2015-01-21

    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.

  1. Ultra-filtration measurement using CT imaging technology

    NASA Astrophysics Data System (ADS)

    Lu, Junfeng; Lu, Wenqiang

    2009-02-01

    As a functional unit in the hemodialysis process, dialyzer captured quite a few medical research interests since 1980s. In the design of dialyzer or in the ongoing hemodialysis process, to estimate the ultra-filtration amount of a dialyzer, the sideway loss of the running blood flow through hollow fibers or filtration channels should be measured. This further leads to the measurement of the blood flow inside the dialyzer. For this measurement, a non-invasive method is highly desired because of the high-dense bundled hollow fibers or packed channels inside the dialyzer. As non-invasive measurement tools, CT (Computed Tomography) technologies were widely used for tissue, bone, and cancerous clinical analyses etc …. Thus, in this paper, a CT system is adopted to predict the blood flow inside a hollow fiber dialyzer. In view of symmetric property of the hollow fiber dialyzer, the largest cutting plane that parallels to the cylindrical dialyzer was analyzed by the CT system dynamically. And then, a noninvasive image analysis method used to predict the ultra-filtration amount is proposed.

  2. 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

  3. Automatic Lumbar Spondylolisthesis Measurement in CT Images.

    PubMed

    Liao, Shu; Zhan, Yiqiang; Dong, Zhongxing; Yan, Ruyi; Gong, Liyan; Zhou, Xiang Sean; Salganicoff, Marcos; Fei, Jun

    2016-07-01

    Lumbar spondylolisthesis is one of the most common spinal diseases. It is caused by the anterior shift of a lumbar vertebrae relative to subjacent vertebrae. In current clinical practices, staging of spondylolisthesis is often conducted in a qualitative way. Although meyerding grading opens the door to stage spondylolisthesis in a more quantitative way, it relies on the manual measurement, which is time consuming and irreproducible. Thus, an automatic measurement algorithm becomes desirable for spondylolisthesis diagnosis and staging. However, there are two challenges. 1) Accurate detection of the most anterior and posterior points on the superior and inferior surfaces of each lumbar vertebrae. Due to the small size of the vertebrae, slight errors of detection may lead to significant measurement errors, hence, wrong disease stages. 2) Automatic localize and label each lumbar vertebrae is required to provide the semantic meaning of the measurement. It is difficult since different lumbar vertebraes have high similarity of both shape and image appearance. To resolve these challenges, a new auto measurement framework is proposed with two major contributions: First, a learning based spine labeling method that integrates both the image appearance and spine geometry information is designed to detect lumbar vertebrae. Second, a hierarchical method using both the population information from atlases and domain-specific information in the target image is proposed for most anterior and posterior points positioning. Validated on 258 CT spondylolisthesis patients, our method shows very similar results to manual measurements by radiologists and significantly increases the measurement efficiency.

  4. Askin tumor: CT and FDG-PET/CT imaging findings and follow-up.

    PubMed

    Xia, Tingting; Guan, Yubao; Chen, Yongxin; Li, Jingxu

    2014-07-01

    The aim of the study was to describe the imaging findings of Askin tumors on computed tomography (CT) and fluorine 18 fluorodeoxyglucose-positron emission tomography (FDG-PET/CT).Seventeen cases of Askin tumors confirmed by histopathology were retrospectively analyzed in terms of CT (17 cases) and FDG-PET/CT data (6 cases).Fifteen of the tumors were located in the chest wall and the other 2 were in the anterior middle mediastinum. Of the 15 chest wall cases, 13 demonstrated irregular, heterogeneous soft tissue masses with cystic degeneration and necrosis, and 2 demonstrated homogeneous soft tissue masses on unenhanced CT scans. Two mediastinal tumors demonstrated the irregular, heterogeneous soft tissue masses. Calcifications were found in 2 tumors. The tumors demonstrated heterogeneously enhancement in 16 cases and homogeneous enhancement in 1 case on contrast-enhanced scans. FDG-PET/CT images revealed increased metabolic activity in all 6 cases undergone FDG-PET/CT scan, and the lesion SUVmax ranged from 4.0 to 18.6. At initial diagnosis, CT and FDG-PET/CT scans revealed rib destruction in 9 cases, pleural effusion in 9 cases, and lung metastasis in 1 case. At follow-up, 12 cases showed recurrence and/or metastases, 4 cases showed improvement or remained stable, and 1 was lost to follow-up.In summary, CT and FDG-PET/CT images of Askin tumors showed heterogeneous soft tissue masses in the chest wall and the mediastinum, accompanied by rib destruction, pleural effusion, and increased FDG uptake. CT and FDG-PET/CT imaging play important roles in the diagnosis and follow-up of patients with Askin tumors.

  5. 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.

  6. Fast CT-CT fluoroscopy registration with respiratory motion compensation for image-guided lung intervention

    NASA Astrophysics Data System (ADS)

    Su, Po; Xue, Zhong; Lu, Kongkuo; Yang, Jianhua; Wong, Stephen T.

    2012-02-01

    CT-fluoroscopy (CTF) is an efficient imaging method for guiding percutaneous lung interventions such as biopsy. During CTF-guided biopsy procedure, four to ten axial sectional images are captured in a very short time period to provide nearly real-time feedback to physicians, so that they can adjust the needle as it is advanced toward the target lesion. Although popularly used in clinics, this traditional CTF-guided intervention procedure may require frequent scans and cause unnecessary radiation exposure to clinicians and patients. In addition, CTF only generates limited slices of images and provides limited anatomical information. It also has limited response to respiratory movements and has narrow local anatomical dynamics. To better utilize CTF guidance, we propose a fast CT-CTF registration algorithm with respiratory motion estimation for image-guided lung intervention using electromagnetic (EM) guidance. With the pre-procedural exhale and inhale CT scans, it would be possible to estimate a series of CT images of the same patient at different respiratory phases. Then, once a CTF image is captured during the intervention, our algorithm can pick the best respiratory phase-matched 3D CT image and performs a fast deformable registration to warp the 3D CT toward the CTF. The new 3D CT image can be used to guide the intervention by superimposing the EM-guided needle location on it. Compared to the traditional repetitive CTF guidance, the registered CT integrates both 3D volumetric patient data and nearly real-time local anatomy for more effective and efficient guidance. In this new system, CTF is used as a nearly real-time sensor to overcome the discrepancies between static pre-procedural CT and the patient's anatomy, so as to provide global guidance that may be supplemented with electromagnetic (EM) tracking and to reduce the number of CTF scans needed. In the experiments, the comparative results showed that our fast CT-CTF algorithm can achieve better registration

  7. Automatic anatomy recognition in whole-body PET/CT images

    SciTech Connect

    Wang, Huiqian; Udupa, Jayaram K. Odhner, Dewey; Tong, Yubing; Torigian, Drew A.; Zhao, Liming

    2016-01-15

    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 of anatomic details in the PET component. In this paper, the authors demonstrate the adaptation of a recently developed automatic anatomy recognition (AAR) methodology [Udupa et al., “Body-wide hierarchical fuzzy modeling, recognition, and delineation of anatomy in medical images,” Med. Image Anal. 18, 752–771 (2014)] to PET/CT images. Their goal was to test what level of object localization accuracy can be achieved on PET/CT compared to that achieved on diagnostic CT images. Methods: The authors advance the AAR approach in this work in three fronts: (i) from body-region-wise treatment in the work of Udupa et al. to whole body; (ii) from the use of image intensity in optimal object recognition in the work of Udupa et al. to intensity plus object-specific texture properties, and (iii) from the intramodality model-building-recognition strategy to the intermodality approach. The whole-body approach allows consideration of relationships among objects in different body regions, which was previously not possible. Consideration of object texture allows generalizing the previous optimal threshold-based fuzzy model recognition method from intensity images to any derived fuzzy membership image, and in the process

  8. Multi-gamma-source CT imaging system: a feasibility study with the Poisson noise

    NASA Astrophysics Data System (ADS)

    Wi, Sunhee; Cho, Seungryong

    2016-03-01

    This study was performed to test the feasibility of multi-gamma-source CT imaging system. Gamma-source CT employs radioisotopes that emit monochromatic energy gamma-rays. The advantages of gamma-source CT include its immunity to beam hardening artifacts, its capacity of quantitative CT imaging, and its higher performance in low contrast imaging compared to the conventional x-ray CT. Radioisotope should be shielded by use of a pin-hole collimator so as to make a fine focal spot. Due to its low gamma-ray flux in general, the reconstructed image from a single gamma-source CT would suffer from high noise in data. To address this problem, we proposed a multi-gamma source CT imaging system and developed an iterative image reconstruction algorithm accordingly in this work. Conventional imaging model assumes a single linear imaging system typically represented by Mf = g. In a multi-gamma-source CT system however, the inversion problem is not any more based on a single linear system since one cannot separate a detector pixel value into multiple ones that are corresponding to each rays from the sources. Instead, the imaging model can be constructed by a set of linear system models each of which assumes an estimated measurement g. Based on this model, the proposed algorithm has a weighting step which distributes each projection data into multiple estimated measurements. We used two gamma sources at various positions and with varying intensities in this numerical study to demonstrate its feasibility. Therefore, the measured projection data(g) is separated into each estimated projection data(g1, g2) in this study. The proposed imaging protocol is believed to contribute to both medical and industrial applications.

  9. Deformable image registration of CT and truncated cone-beam CT for adaptive radiation therapy

    NASA Astrophysics Data System (ADS)

    Zhen, Xin; Yan, Hao; Zhou, Linghong; Jia, Xun; Jiang, Steve B.

    2013-11-01

    Truncation of a cone-beam computed tomography (CBCT) image, mainly caused by the limited field of view (FOV) of CBCT imaging, poses challenges to the problem of deformable image registration (DIR) between computed tomography (CT) and CBCT images in adaptive radiation therapy (ART). The missing information outside the CBCT FOV usually causes incorrect deformations when a conventional DIR algorithm is utilized, which may introduce significant errors in subsequent operations such as dose calculation. In this paper, based on the observation that the missing information in the CBCT image domain does exist in the projection image domain, we propose to solve this problem by developing a hybrid deformation/reconstruction algorithm. As opposed to deforming the CT image to match the truncated CBCT image, the CT image is deformed such that its projections match all the corresponding projection images for the CBCT image. An iterative forward-backward projection algorithm is developed. Six head-and-neck cancer patient cases are used to evaluate our algorithm, five with simulated truncation and one with real truncation. It is found that our method can accurately register the CT image to the truncated CBCT image and is robust against image truncation when the portion of the truncated image is less than 40% of the total image. Part of this work was presented at the 54th AAPM Annual Meeting (Charlotte, NC, USA, 29 July-2 August 2012).

  10. Deformable Image Registration of CT and Truncated Cone-beam CT for Adaptive Radiation Therapy*

    PubMed Central

    Zhen, Xin; Yan, Hao; Zhou, Linghong; Jia, Xun; Jiang, Steve B.

    2013-01-01

    Truncation of a cone-beam computed tomography (CBCT) image, mainly caused by the limited field of view (FOV) of CBCT imaging, poses challenges to the problem of deformable image registration (DIR) between CT and CBCT images in adaptive radiation therapy (ART). The missing information outside the CBCT FOV usually causes incorrect deformations when a conventional DIR algorithm is utilized, which may introduce significant errors in subsequent operations such as dose calculation. In this paper, based on the observation that the missing information in the CBCT image domain does exist in the projection image domain, we propose to solve this problem by developing a hybrid deformation/reconstruction algorithm. As opposed to deforming the CT image to match the truncated CBCT image, the CT image is deformed such that its projections match all the corresponding projection images for the CBCT image. An iterative forward-backward projection algorithm is developed. Six head-and-neck cancer patient cases are used to evaluate our algorithm, five with simulated truncation and one with real truncation. It is found that our method can accurately register the CT image to the truncated CBCT image and is robust against image truncation when the portion of the truncated image is less than 40% of the total image. PMID:24169817

  11. 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.

  12. Medical imaging V

    SciTech Connect

    Loew, M.H.

    1991-01-01

    This book is covered under the following topics: preprocessing and enhancement 1-3; segmentation, feature extraction, and detection 1-2; hardware and software systems for display; and user interface; MRI; MRI and PET; 3-D; image reconstruction, modeling, description, and coding; and knowledge-based methods.

  13. Medical Imaging Informatics.

    PubMed

    Hsu, William; El-Saden, Suzie; Taira, Ricky K

    2016-01-01

    Imaging is one of the most important sources of clinically observable evidence that provides broad coverage, can provide insight on low-level scale properties, is noninvasive, has few side effects, and can be performed frequently. Thus, imaging data provides a viable observable that can facilitate the instantiation of a theoretical understanding of a disease for a particular patient context by connecting imaging findings to other biologic parameters in the model (e.g., genetic, molecular, symptoms, and patient survival). These connections can help inform their possible states and/or provide further coherent evidence. The field of radiomics is particularly dedicated to this task and seeks to extract quantifiable measures wherever possible. Example properties of investigation include genotype characterization, histopathology parameters, metabolite concentrations, vascular proliferation, necrosis, cellularity, and oxygenation. Important issues within the field include: signal calibration, spatial calibration, preprocessing methods (e.g., noise suppression, motion correction, and field bias correction), segmentation of target anatomic/pathologic entities, extraction of computed features, and inferencing methods connecting imaging features to biological states.

  14. 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)

  15. Quantitative image quality evaluation for cardiac CT reconstructions

    NASA Astrophysics Data System (ADS)

    Tseng, Hsin-Wu; Fan, Jiahua; Kupinski, Matthew A.; Balhorn, William; Okerlund, Darin R.

    2016-03-01

    Maintaining image quality in the presence of motion is always desirable and challenging in clinical Cardiac CT imaging. Different image-reconstruction algorithms are available on current commercial CT systems that attempt to achieve this goal. It is widely accepted that image-quality assessment should be task-based and involve specific tasks, observers, and associated figures of merits. In this work, we developed an observer model that performed the task of estimating the percentage of plaque in a vessel from CT images. We compared task performance of Cardiac CT image data reconstructed using a conventional FBP reconstruction algorithm and the SnapShot Freeze (SSF) algorithm, each at default and optimal reconstruction cardiac phases. The purpose of this work is to design an approach for quantitative image-quality evaluation of temporal resolution for Cardiac CT systems. To simulate heart motion, a moving coronary type phantom synchronized with an ECG signal was used. Three different percentage plaques embedded in a 3 mm vessel phantom were imaged multiple times under motion free, 60 bpm, and 80 bpm heart rates. Static (motion free) images of this phantom were taken as reference images for image template generation. Independent ROIs from the 60 bpm and 80 bpm images were generated by vessel tracking. The observer performed estimation tasks using these ROIs. Ensemble mean square error (EMSE) was used as the figure of merit. Results suggest that the quality of SSF images is superior to the quality of FBP images in higher heart-rate scans.

  16. Medical gamma ray imaging

    DOEpatents

    Osborne, Louis S.; Lanza, Richard C.

    1984-01-01

    A method and apparatus for determining the distribution of a position-emitting radioisotope into an object, the apparatus consisting of a wire mesh radiation converter, an ionizable gas for propagating ionization events caused by electrodes released by the converter, a drift field, a spatial position detector and signal processing circuitry for correlating near-simultaneous ionization events and determining their time differences, whereby the position sources of back-to-back collinear radiation can be located and a distribution image constructed.

  17. 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.

  18. Preliminary experience on the implementation of computed tomography (CT)-based image guided brachytherapy (IGBT) of cervical cancer using high-dose-rate (HDR) Cobalt-60 source in University of Malaya Medical Centre (UMMC)

    NASA Astrophysics Data System (ADS)

    Jamalludin, Z.; Min, U. N.; Ishak, W. Z. Wan; Malik, R. Abdul

    2016-03-01

    This study presents our preliminary work of the computed tomography (CT) image guided brachytherapy (IGBT) implementation on cervical cancer patients. We developed a protocol in which patients undergo two Magnetic Resonance Imaging (MRI) examinations; a) prior to external beam radiotherapy (EBRT) and b) prior to intra-cavitary brachytherapy for tumour identification and delineation during IGBT planning and dosimetry. For each fraction, patients were simulated using CT simulator and images were transferred to the treatment planning system. The HR-CTV, IR-CTV, bladder and rectum were delineated on CT-based contouring for cervical cancer. Plans were optimised to achieve HR-CTV and IR-CTV dose (D90) of total EQD2 80Gy and 60Gy respectively, while limiting the minimum dose to the most irradiated 2cm3 volume (D2cc) of bladder and rectum to total EQD2 90Gy and 75Gy respectively. Data from seven insertions were analysed by comparing the volume-based with traditional point- based doses. Based on our data, there were differences between volume and point doses of HR- CTV, bladder and rectum organs. As the number of patients having the CT-based IGBT increases from day to day in our centre, it is expected that the treatment and dosimetry accuracy will be improved with the implementation.

  19. 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

  20. Principles of CT: radiation dose and image quality.

    PubMed

    Goldman, Lee W

    2007-12-01

    This article discusses CT radiation dose, the measurement of CT dose, and CT image quality. The most commonly used dose descriptor is CT dose index, which represents the dose to a location (e.g., depth) in a scanned volume from a complete series of slices. A weighted average of the CT dose index measured at the center and periphery of dose phantoms provides a convenient single-number estimate of patient dose for a procedure, and this value (or a related indicator that includes the scanned length) is often displayed on the operator's console. CT image quality, as in most imaging, is described in terms of contrast, spatial resolution, image noise, and artifacts. A strength of CT is its ability to visualize structures of low contrast in a subject, a task that is limited primarily by noise and is therefore closely associated with radiation dose: The higher the dose contributing to the image, the less apparent is image noise and the easier it is to perceive low-contrast structures. Spatial resolution is ultimately limited by sampling, but both image noise and resolution are strongly affected by the reconstruction filter. As a result, diagnostically acceptable image quality at acceptable doses of radiation requires appropriately designed clinical protocols, including appropriate kilovolt peaks, amperages, slice thicknesses, and reconstruction filters.

  1. Ring artifacts removal from synchrotron CT image slices

    NASA Astrophysics Data System (ADS)

    Wei, Zhouping; Wiebe, Sheldon; Chapman, Dean

    2013-06-01

    Ring artifacts can occur in reconstructed images from x-ray Computerized Tomography (CT) as full or partial concentric rings superimposed on the scanned structures. Due to the data corruption by those ring artifacts in CT images, qualitative and quantitative analysis of these images are compromised. In this paper, we propose to correct the ring artifacts on the reconstructed synchrotron radiation (SR) CT image slices. The proposed correction procedure includes the following steps: (1). transform the reconstructed CT images into polar coordinates; (2) apply discrete two-dimensional (2D) wavelet transform to the polar image to decompose it into four image components: low pass band image component, as well as the components from horizontal, vertical and diagonal details bands; (3). apply 2D Fourier transform to the vertical details band image component only, since the ring artifacts become vertical lines in the polar coordinates; (4). apply Gaussian filtering in Fourier domain along the abscissa direction to suppress the vertical lines, since the information of the vertical lines in Fourier domain is completely condensed to that direction; (5). perform inverse Fourier transform to get the corrected vertical details band image component; (6). perform inverse wavelet transform to get the corrected polar image; (7). transform the corrected polar image back to Cartesian coordinates to get the CT image slice with reduced ring artifacts. This approach has been successfully used on CT data acquired from the Biomedical Imaging and Therapy (BMIT) beamline in Canadian Light Source (CLS), and the results show that the ring artifacts in original SR CT images have been effectively suppressed with all the structure information in the image preserved.

  2. 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

  3. SU-C-9A-06: The Impact of CT Image Used for Attenuation Correction in 4D-PET

    SciTech Connect

    Cui, Y; Bowsher, J; Yan, S; Cai, J; Das, S; Yin, F

    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 Medical Systems, Palo Alto, CA) was used for respiratory gating. Both phase-gating and amplitude-gating methods were tested. The clinical imaging protocol was modified to use three different CT images for AC in 4D-PET reconstruction: first is to use a single-phase CT image to mimic actual clinical protocol (single-CT-PET); second is to use the average intensity projection CT (AveIP-CT) derived from 4D-CT scanning (AveIP-CT-PET); third is to use 4D-CT image to do the phase-matched AC (phase-matching- PET). Maximum SUV (SUVmax) and volume of the moving target (glass sphere) with threshold of 40% SUVmax were calculated for comparison between 4D-PET images derived with different AC methods. Results: The SUVmax varied 7.3%±6.9% over the breathing cycle in single-CT-PET, compared to 2.5%±2.8% in AveIP-CT-PET and 1.3%±1.2% in phasematching PET. The SUVmax in single-CT-PET differed by up to 15% from those in phase-matching-PET. The target volumes measured from single- CT-PET images also presented variations up to 10% among different phases of 4D PET in both phase-gating and amplitude-gating experiments. Conclusion: Attenuation correction using non-gated CT in 4D-PET imaging is not optimal process for quantitative analysis. Clinical 4D-PET imaging protocols should consider phase-matched 4D-CT image if available to achieve better accuracy.

  4. Multimodal CT in stroke imaging: new concepts.

    PubMed

    Ledezma, Carlos J; Wintermark, Max

    2009-01-01

    A multimodal CT protocol provides a comprehensive noninvasive survey of acute stroke patients with accurate demonstration of the site of arterial occlusion and its hemodynamic tissue status. It combines widespread availability with the ability to provide functional characterization of cerebral ischemia, and could potentially allow more accurate selection of candidates for acute stroke reperfusion therapy. This article discusses the individual components of multimodal CT and addresses the potential role of a combined multimodal CT stroke protocol in acute stroke therapy.

  5. Wavelet Packets-Based Blind Watermarking for Medical Image Management

    PubMed Central

    Mostafa, Salwa A.K.; El-sheimy, Naser; Tolba, A.S.; Abdelkader, F.M.; Elhindy, Hisham M.

    2010-01-01

    The last decade has witnessed an explosive use of medical images and Electronics Patient Record (EPR) in the healthcare sector for facilitating the sharing of patient information and exchange between networked hospitals and healthcare centers. To guarantee the security, authenticity and management of medical images and information through storage and distribution, the watermarking techniques are growing to protect the medical healthcare information. This paper presents a technique for embedding the EPR information in the medical image to save storage space and transmission overheads and to guarantee security of the shared data. In this paper a new method for protecting the patient information in which the information is embedded as a watermark in the discrete wavelet packet transform (DWPT) of the medical image using the hospital logo as a reference image. The patient information is coded by an error correcting code (ECC), BCH code, to enhance the robustness of the proposed method. The scheme is blind so that the EPR can be extracted from the medical image without the need of the original image. Therefore, this proposed technique is useful in telemedicine applications. Performance of the proposed method was tested using four modalities of medical images; MRA, MRI, Radiological, and CT. Experimental results showed no visible difference between the watermarked and the original image. Moreover, the proposed watermarking method is robust against a wide range of attacks such as JPEG coding, Gaussian noise addition, histogram equalization, gamma correction, contrast adjustment, and sharpen filter and rotation. PMID:20700520

  6. 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

  7. Semiautomatic brain morphometry from CT images

    NASA Astrophysics Data System (ADS)

    Soltanian-Zadeh, Hamid; Windham, Joe P.; Peck, Donald J.

    1994-05-01

    Fast, accurate, and reproducible volume estimation is vital to the diagnosis, treatment, and evaluation of many medical situations. We present the development and application of a semi-automatic method for estimating volumes of normal and abnormal brain tissues from computed tomography images. This method does not require manual drawing of the tissue boundaries. It is therefore expected to be faster and more reproducible than conventional methods. The steps of the new method are as follows. (1) The intracranial brain volume is segmented from the skull and background using thresholding and morphological operations. (2) The additive noise is suppressed (the image is restored) using a non-linear edge-preserving filter which preserves partial volume information on average. (3) The histogram of the resulting low-noise image is generated and the dominant peak is removed from it using a Gaussian model. (4) Minima and maxima of the resulting histogram are identified and using a minimum error criterion, the brain is segmented into the normal tissues (white matter and gray matter), cerebrospinal fluid, and lesions, if present. (5) Previous steps are repeated for each slice through the brain and the volume of each tissue type is estimated from the results. Details and significance of each step are explained. Experimental results using a simulation, a phantom, and selected clinical cases are presented.

  8. 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.

  9. 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

  10. Automatic nonrigid registration of whole body CT mice images.

    PubMed

    Li, Xia; Yankeelov, Thomas E; Peterson, Todd E; Gore, John C; Dawant, Benoit M

    2008-04-01

    Three-dimensional intra- and intersubject registration of image volumes is important for tasks that include quantification of temporal/longitudinal changes, atlas-based segmentation, computing population averages, or voxel and tensor-based morphometry. While a number of methods have been proposed to address this problem, few have focused on the problem of registering whole body image volumes acquired either from humans or small animals. These image volumes typically contain a large number of articulated structures, which makes registration more difficult than the registration of head images, to which the majority of registration algorithms have been applied. This article presents a new method for the automatic registration of whole body computed tomography (CT) volumes, which consists of two main steps. Skeletons are first brought into approximate correspondence with a robust point-based method. Transformations so obtained are refined with an intensity-based nonrigid registration algorithm that includes spatial adaptation of the transformation's stiffness. The approach has been applied to whole body CT images of mice, to CT images of the human upper torso, and to human head and neck CT images. To validate the authors method on soft tissue structures, which are difficult to see in CT images, the authors use coregistered magnetic resonance images. They demonstrate that the approach they propose can successfully register image volumes even when these volumes are very different in size and shape or if they have been acquired with the subjects in different positions.

  11. [Tattoos and medical imaging: issues and myths].

    PubMed

    Kluger, Nicolas

    2014-05-01

    Tattooing is characterized by the introduction in the dermis of exogenous pigments to obtain a permanent design. Whether it is a traditional tattoo applied on the skin or a cosmetic one (permanent make-up), its prevalence has boomed for the past 20 years. The increased prevalence of tattooed patients along with medical progresses, in the field of therapeutics or diagnostic means have lead to the discovery of "new" complications and unexpected issues. Medical imaging world has also been affected by the tattoo craze. It has been approximately 20 years when the first issues related to tattooing and permanent make-up aroused. However, cautions and questions as well as anecdotal severe case reports have sometimes led to an over-exaggerated response by some physicians such as the systematic avoidance of RMN imaging for tattooed individuals. This review is intended to summarize the risks but also the "myths" associated with tattoo in the daily practice of the radiologist for RMN, CT scan, mammography, Pet-scan and ultrasound imaging.

  12. Imaging of inflammatory bowel disease: CT and MR.

    PubMed

    Zalis, Michael; Singh, Ajay K

    2004-01-01

    Cross-sectional imaging has come to play a central role in the imaging of the abdomen. Concurrent to this, the role of CT and MRI in the imaging of inflammatory bowel disease has also increased in importance. These modalities offer numerous advantages over more traditional methods of radiologic diagnosis, and provide essential information not only for initial diagnosis, but for management, follow-up and detection of potential complications. On the horizon are several derivative techniques involving CT and MRI, potentially in combination with PET imaging; these may further improve the specificity and sensitivity of imaging modalities for diagnosis of inflammatory bowel disease.

  13. Tele-medical imaging conference system based on the Web.

    PubMed

    Choi, Heung-Kook; Park, Se-Myung; Kang, Jae-Hyo; Kim, Sang-Kyoon; Choi, Hang-Mook

    2002-06-01

    In this paper, a medical imaging conference system is presented, which is carried out in the Web environment using the distributed object technique, CORBA. Independent of platforms and different developing languages, the CORBA-based medical imaging conference system is very powerful for system development, extension and maintenance. With this Web client/server, one could easily execute a medical imaging conference using Applets on the Web. The Java language, which is object-oriented and independent of platforms, has the advantage of free usage wherever the Web browser is. By using the proposed system, we envisage being able to open a tele-conference using medical images, e.g. CT, MRI, X-ray etc., easily and effectively among remote hospitals.

  14. CT image quality over time: comparison of image quality for six different CT scanners over a six-year period.

    PubMed

    Roa, Ana Maria A; Andersen, Hilde K; Martinsen, Anne Catrine T

    2015-03-08

    UNSCEAR concluded that increased use of CT scanning caused dramatic changes in population dose. Therefore, international radiation protection authorities demand: 1) periodical quality assurance tests with respect to image quality and radiation dose, and 2) optimization of all examination protocols with respect to image quality and radiation dose. This study aimed to evaluate and analyze multiple image quality parameters and variability measured throughout time for six different CT scanners from four different vendors, in order to evaluate the current methodology for QA controls of CT systems. The results from this study indicate that there is minor drifting in the image noise and uniformity and in the spatial resolution over time for CT scanners, independent of vendors. The HU for different object densities vary between different CT scanner models from different vendors, and over time for one specific CT scanner. Future tests of interphantom and intraphantom variations, along with inclusion of more CT scanners, are necessary to establish robust baselines and recommendations of methodology for QA controls of CT systems, independent of model and vendor.

  15. Characterization of a prototype tabletop x-ray CT breast imaging system

    NASA Astrophysics Data System (ADS)

    O'Connor, J. Michael; Glick, Stephen J.; Gong, Xing; Didier, Clay; Mah'd, Mufeed

    2007-03-01

    Planar X-ray mammography is the standard medical imaging modality for the early detection of breast cancer. Based on advancements in digital flat-panel detector technology, dedicated x-ray computed tomography (CT) mammography is a modality under investigation that offers the potential for improved breast tumor imaging. We have implemented a prototype half cone-beam CT breast imaging system that utilizes an indirect flat-panel detector. This prototype can be used to explore and evaluate the effect of varying acquisition and reconstruction parameters on image quality. This report describes our system and characterizes the performance of the system through the analysis of Modulation Transfer Function (MTF) and Noise Power Spectrum (NPS). All CT reconstructions were made using Feldkamp's filtered backprojection algorithm. The 3D MTF was determined by the analysis of the plane spread function (PlSF) derived from the surface spread function (SSF) of reconstructed 6.3mm spheres. 3D NPS characterization was performed through the analysis of a 3D volume extracted from zero-mean CT noise of air reconstructions. The effect of varying locations on MTF and the effect of different Butterworth filter cutoff frequencies on NPS are reported. Finally, we present CT images of mastectomy excised breast tissue. Breast specimen images were acquired on our CTMS using an x-ray technique similar to the one used during performance characterization. Specimen images demonstrate the inherent CT capability to reduce the masking effect of anatomical noise. Both the quantitative system characterization and the breast specimen images continue to reinforce the hope that dedicated flat-panel detector, x-ray cone-beam CT will eventually provide enhanced breast cancer detection capability.

  16. Contextual medical-image viewer

    NASA Astrophysics Data System (ADS)

    Moreno, Ramon A.; Furuie, Sergio S.

    2004-04-01

    One of the greatest difficulties of dealing with medical images is their distinct characteristics, in terms of generation process and noise that requires different forms of treatment for visualization and processing. Besides that, medical images are only a compounding part of the patient"s history, which should be accessible for the user in an understandable way. Other factors that can be used to enhance the user capability and experience are: the computational power of the client machine; available knowledge about the case; if the access is local or remote and what kind of user is accessing the system (physician, nurse, administrator, etc...). These information compose the context of an application and should define its behavior during execution time. In this article, we present the architecture of a viewer that takes into account the contextual information that is present at the moment of execution. We also present a viewer of X-Ray Angiographic images that uses contextual information about the client's hardware and the kind of user to, if necessary, reduce the image size and hide demographic information of the patient. The proposed architecture is extensible, allowing the inclusion of new tools and viewers, being adaptive along time to the evolution of the medical systems.

  17. A feature-based learning framework for accurate prostate localization in CT images.

    PubMed

    Liao, Shu; Shen, Dinggang

    2012-08-01

    Automatic segmentation of prostate in CT images plays an important role in medical image analysis and image guided radiation therapy. It remains as a challenging problem mainly due to three issues: First, the image contrast between the prostate and its surrounding tissues is low in prostate CT images and no obvious boundaries can be observed. Second, the unpredictable prostate motion causes large position variations of the prostate in the treatment images scanned at different treatment days. Third, the uncertainty of the existence of bowel gas in treatment images significantly changes the image appearance even for images taken from the same patient. To address these issues, in this paper we are motivated to propose a feature based learning framework for accurate prostate localization in CT images. The main contributions of the proposed method lie in the following aspects: (1) Anatomical features are extracted from input images and adopted as signatures for each voxel. The most robust and informative features are identified by the feature selection process to help localize the prostate. (2) Regions with salient features but irrelevant to the localization of prostate, such as regions filled with bowel gas are automatically filtered out by the proposed method. (3) An online update mechanism is adopted in this paper to adaptively combine both population information and patient-specific information to localize the prostate. The proposed method is evaluated on a CT prostate dataset of 24 patients to localize the prostate, where each patient has more than 10 longitudinal images scanned at different treatment times. It is also compared with several state-of- the-art prostate localization algorithms in CT images, and the experimental results demonstrate that the proposed method achieves the highest localization accuracy among all the methods under comparison.

  18. Similarity searching for chest CT images based on object features and spatial relation maps.

    PubMed

    Yu, Sung-Nien; Chiang, Chih-Tsung

    2004-01-01

    In this paper, an object-based image retrieval system for chest CT image databases is proposed. Based on the scheme of the content-based image retrieval method, we proposed an image segmentation method which combines the anatomical knowledge of the chest and the well-known watershed segmentation algorithm. The purpose of segmentation is to identify the mediastinum and the two lung lobes in a chest CT image. The ARGs (attributed relational graphs) are chosen to describe the features of segmented objects. Then, image database is constructed by the feature vectors of images. In database searching, two searching modes are provided that are "query by example" and "query by object". Our system uses Euclidean distance to measure the similarity between the image in query and the image in database. The system output the 30 most similar images in the chest CT image database as query results. The experimental results show that the average precision of our system is about 80% which is impressive in a totally automatic medical image retrieval system. Moreover, query concentrated in certain objects features usually show better result than the regular query by example. The possible reasons are discussed.

  19. Digital diagnosis of medical images

    NASA Astrophysics Data System (ADS)

    Heinonen, Tomi; Kuismin, Raimo; Jormalainen, Raimo; Dastidar, Prasun; Frey, Harry; Eskola, Hannu

    2001-08-01

    The popularity of digital imaging devices and PACS installations has increased during the last years. Still, images are analyzed and diagnosed using conventional techniques. Our research group begun to study the requirements for digital image diagnostic methods to be applied together with PACS systems. The research was focused on various image analysis procedures (e.g., segmentation, volumetry, 3D visualization, image fusion, anatomic atlas, etc.) that could be useful in medical diagnosis. We have developed Image Analysis software (www.medimag.net) to enable several image-processing applications in medical diagnosis, such as volumetry, multimodal visualization, and 3D visualizations. We have also developed a commercial scalable image archive system (ActaServer, supports DICOM) based on component technology (www.acta.fi), and several telemedicine applications. All the software and systems operate in NT environment and are in clinical use in several hospitals. The analysis software have been applied in clinical work and utilized in numerous patient cases (500 patients). This method has been used in the diagnosis, therapy and follow-up in various diseases of the central nervous system (CNS), respiratory system (RS) and human reproductive system (HRS). In many of these diseases e.g. Systemic Lupus Erythematosus (CNS), nasal airways diseases (RS) and ovarian tumors (HRS), these methods have been used for the first time in clinical work. According to our results, digital diagnosis improves diagnostic capabilities, and together with PACS installations it will become standard tool during the next decade by enabling more accurate diagnosis and patient follow-up.

  20. [Realization of DICOM medical image compression technology].

    PubMed

    Wang, Chenxi; Wang, Quan; Ren, Haiping

    2013-05-01

    This paper introduces the implement method of DICOM medical image compression technology, The image part of DICOM files are extracted and converted to BMP format. The non-image information in DICOM file are stored into the text. When the final image of JPEG standard and non-image information are encapsulated to DICOM format images, it realizes the compression of medical image, which is beneficial to the image storage and transmission.

  1. Comparison of CT scanning and radionuclide imaging in liver disease

    SciTech Connect

    Friedman, M.L.; Esposito, F.S.

    1980-01-01

    Early experience with body CT suggested its usefulness in many diagnostic problems; jaundice, renal and pancreatic masses, and in the evaluation of relatively inaccessible parts of the body, such as the retroperitineum, mediastinum, and pelvis. Investigation of hepatic disease by CT was not unexpectedly compared to radionuclide liver scanning, the major preexisting modality for imaging the liver. In the evaluation of the jaundiced patient, CT rapidly assumed a major role, providing more specific information about the liver than the RN liver scan, as well as demonstrating adjacent organs. CT differentiate obstructive from non-obstructive jaundice. With respect to mass lesions of the liver, the RN liver scan is more sensitive than CT but less specific. The abnormalities on an isotope image of the liver consist of normal variants in configuration, extrinsic compression by adjacent structures, cysts, hemangiomata, abscesses, and neoplasms. These suspected lesions may then be better delineated by the CT image, and a more precise diagnosis made. The physiologic information provided by the RN liver scan is an added facet which is helpful in the patient with diffuse hepatic disease. The CT image will be normal in many of these patients, however, hemochromatosis and fatty infiltration lend themselves especially to density evaluation by CT. The evaluation of lymphoma is more thorough with CT. Structures other than the liver, such as lymph nodes, are visualized. Gallium, however, provides additional isotopic information in patients with lymphoma, and in addition, is known to be useful in the investigation of a febrile patient with an abscess. Newer isotopic agents expand hepatic imaging in other directions, visualizing the biliary tree and evaluating the jaundiced patient.

  2. 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.

  3. 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.

  4. Non-Rigid Registration of Liver CT Images for CT-Guided Ablation of Liver Tumors.

    PubMed

    Luu, Ha Manh; Klink, Camiel; Niessen, Wiro; Moelker, Adriaan; Walsum, Theo van

    2016-01-01

    CT-guided percutaneous ablation for liver cancer treatment is a relevant technique for patients not eligible for surgery and with tumors that are inconspicuous on US imaging. The lack of real-time imaging and the use of a limited amount of CT contrast agent make targeting the tumor with the needle challenging. In this study, we evaluate a registration framework that allows the integration of diagnostic pre-operative contrast enhanced CT images and intra-operative non-contrast enhanced CT images to improve image guidance in the intervention. The liver and tumor are segmented in the pre-operative contrast enhanced CT images. Next, the contrast enhanced image is registered to the intra-operative CT images in a two-stage approach. First, the contrast-enhanced diagnostic image is non-rigidly registered to a non-contrast enhanced image that is conventionally acquired at the start of the intervention. In case the initial registration is not sufficiently accurate, a refinement step is applied using non-rigid registration method with a local rigidity term. In the second stage, the intra-operative CT-images that are used to check the needle position, which often consist of only a few slices, are registered rigidly to the intra-operative image that was acquired at the start of the intervention. Subsequently, the diagnostic image is registered to the current intra-operative image, using both transformations, this allows the visualization of the tumor region extracted from pre-operative data in the intra-operative CT images containing needle. The method is evaluated on imaging data of 19 patients at the Erasmus MC. Quantitative evaluation is performed using the Dice metric, mean surface distance of the liver border and corresponding landmarks in the diagnostic and the intra-operative images. The registration of the diagnostic CT image to the initial intra-operative CT image did not require a refinement step in 13 cases. For those cases, the resulting registration had a Dice

  5. Non-Rigid Registration of Liver CT Images for CT-Guided Ablation of Liver Tumors

    PubMed Central

    Luu, Ha Manh; Klink, Camiel; Niessen, Wiro; Moelker, Adriaan; van Walsum, Theo

    2016-01-01

    CT-guided percutaneous ablation for liver cancer treatment is a relevant technique for patients not eligible for surgery and with tumors that are inconspicuous on US imaging. The lack of real-time imaging and the use of a limited amount of CT contrast agent make targeting the tumor with the needle challenging. In this study, we evaluate a registration framework that allows the integration of diagnostic pre-operative contrast enhanced CT images and intra-operative non-contrast enhanced CT images to improve image guidance in the intervention. The liver and tumor are segmented in the pre-operative contrast enhanced CT images. Next, the contrast enhanced image is registered to the intra-operative CT images in a two-stage approach. First, the contrast-enhanced diagnostic image is non-rigidly registered to a non-contrast enhanced image that is conventionally acquired at the start of the intervention. In case the initial registration is not sufficiently accurate, a refinement step is applied using non-rigid registration method with a local rigidity term. In the second stage, the intra-operative CT-images that are used to check the needle position, which often consist of only a few slices, are registered rigidly to the intra-operative image that was acquired at the start of the intervention. Subsequently, the diagnostic image is registered to the current intra-operative image, using both transformations, this allows the visualization of the tumor region extracted from pre-operative data in the intra-operative CT images containing needle. The method is evaluated on imaging data of 19 patients at the Erasmus MC. Quantitative evaluation is performed using the Dice metric, mean surface distance of the liver border and corresponding landmarks in the diagnostic and the intra-operative images. The registration of the diagnostic CT image to the initial intra-operative CT image did not require a refinement step in 13 cases. For those cases, the resulting registration had a Dice

  6. The value of diagnostic medical imaging.

    PubMed

    Bradley, Don; Bradley, Kendall E

    2014-01-01

    Diagnostic medical imaging has clear clinical utility, but it also imposes significant costs on the health care system. This commentary reviews the factors that drive the cost of medical imaging, discusses current interventions, and suggests possible future courses of action.

  7. Thoracic cancer imaging with PET/CT in radiation oncology

    NASA Astrophysics Data System (ADS)

    Chi, Pai-Chun Melinda

    Significance. Respiratory motion has been shown to cause artifacts in PET/CT imaging. This breathing artifact can have a significant impact on PET quantification and it can lead to large uncertainties when using PET for radiation therapy planning. We have demonstrated a promising solution to resolve the breathing artifact by acquiring respiration-averaged CT (ACT) for PET/CT. The purpose of this work was to optimize the ACT acquisition for clinical implementation and to evaluate the impact of ACT on PET/CT quantification. The hypothesis was that ACT is an effective method in removing the breathing artifact when compared to our current clinical protocol. Methods. Phase and cine approaches for acquiring ACT were investigated and the results of these two approaches were compared to the ACT generated from clinical 4DCT data sets (abbreviated as ACT10phs ). In the phase approach, ACT was generated based on combinations of selected respiratory phases; in the cine approach, ACT was generated based on cine images acquired over a fixed cine duration. The phase combination and cine duration that best approximated the ACT10phs were determined to be the optimized scanning parameters. 216 thoracic PET/CT patients were scanned with both current clinical and the ACT protocols. The effects of ACT on PET/CT quantification were assessed by comparing clinical PET/CT and ACT PET/CT using 3 metrics: PET/CT image alignment, maximum standardized uptake value (SUVmax), and threshold segmented gross tumor volume (GTV). Results. ACT10phs can be best approximated to within 2% of SUV variation by phase averaging based on 4 representative phases, and to within 3% by cine image averaging based on >3s of cine duration. We implemented the cine approach on the PET/CT scanners and acquired 216 patient data sets. 68% of patients had breathing artifacts in their clinical PET/CT and the artifacts were removed/reduced in all corresponding ACT PET/CT. PET/CT quantification for lesions <50 cm3 and

  8. Medical imaging, PACS, and imaging informatics: retrospective.

    PubMed

    Huang, H K

    2014-01-01

    Historical reviews of PACS (picture archiving and communication system) and imaging informatics development from different points of view have been published in the past (Huang in Euro J Radiol 78:163-176, 2011; Lemke in Euro J Radiol 78:177-183, 2011; Inamura and Jong in Euro J Radiol 78:184-189, 2011). This retrospective attempts to look at the topic from a different angle by identifying certain basic medical imaging inventions in the 1960s and 1970s which had conceptually defined basic components of PACS guiding its course of development in the 1980s and 1990s, as well as subsequent imaging informatics research in the 2000s. In medical imaging, the emphasis was on the innovations at Georgetown University in Washington, DC, in the 1960s and 1970s. During the 1980s and 1990s, research and training support from US government agencies and public and private medical imaging manufacturers became available for training of young talents in biomedical physics and for developing the key components required for PACS development. In the 2000s, computer hardware and software as well as communication networks advanced by leaps and bounds, opening the door for medical imaging informatics to flourish. Because many key components required for the PACS operation were developed by the UCLA PACS Team and its collaborative partners in the 1980s, this presentation is centered on that aspect. During this period, substantial collaborative research efforts by many individual teams in the US and in Japan were highlighted. Credits are due particularly to the Pattern Recognition Laboratory at Georgetown University, and the computed radiography (CR) development at the Fuji Electric Corp. in collaboration with Stanford University in the 1970s; the Image Processing Laboratory at UCLA in the 1980s-1990s; as well as the early PACS development at the Hokkaido University, Sapporo, Japan, in the late 1970s, and film scanner and digital radiography developed by Konishiroku Photo Ind. Co. Ltd

  9. TLD assessment of mouse dosimetry during microCT imaging

    SciTech Connect

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

    2008-09-15

    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 cm{sup 3} 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.

  10. Validation of 3D ultrasound: CT registration of prostate images

    NASA Astrophysics Data System (ADS)

    Firle, Evelyn A.; Wesarg, Stefan; Karangelis, Grigoris; Dold, Christian

    2003-05-01

    All over the world 20% of men are expected to develop prostate cancer sometime in his life. In addition to surgery - being the traditional treatment for cancer - the radiation treatment is getting more popular. The most interesting radiation treatment regarding prostate cancer is Brachytherapy radiation procedure. For the safe delivery of that therapy imaging is critically important. In several cases where a CT device is available a combination of the information provided by CT and 3D Ultrasound (U/S) images offers advantages in recognizing the borders of the lesion and delineating the region of treatment. For these applications the CT and U/S scans should be registered and fused in a multi-modal dataset. Purpose of the present development is a registration tool (registration, fusion and validation) for available CT volumes with 3D U/S images of the same anatomical region, i.e. the prostate. The combination of these two imaging modalities interlinks the advantages of the high-resolution CT imaging and low cost real-time U/S imaging and offers a multi-modality imaging environment for further target and anatomy delineation. This tool has been integrated into the visualization software "InViVo" which has been developed over several years in Fraunhofer IGD in Darmstadt.

  11. 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.

  12. Archimedes, an archive of medical images.

    PubMed

    Tahmoush, Dave; Samet, Hanan

    2006-01-01

    We present a medical image and medical record database for the storage, research, transmission, and evaluation of medical images. Medical images from any source that supports the DICOM standard can be stored and accessed, as well as associated analysis and annotations. Retrieval is based on patient info, date, doctor's annotations, features in the images, or a spatial combination. This database supports the secure transmission of sensitive data for tele-medicine and follows all HIPPA regulations.

  13. Joint detection and segmentation of vertebral bodies in CT images by sparse representation error minimization

    NASA Astrophysics Data System (ADS)

    Korez, Robert; Likar, Boštjan; Pernuš, Franjo; Vrtovec, Tomaž

    2016-03-01

    Automated detection and segmentation of vertebral bodies from spinal computed tomography (CT) images is usually a prerequisite step for numerous spine-related medical applications, such as diagnosis, surgical planning and follow-up assessment of spinal pathologies. However, automated detection and segmentation are challenging tasks due to a relatively high degree of anatomical complexity, presence of unclear boundaries and articulation of vertebrae with each other. In this paper, we describe a sparse representation error minimization (SEM) framework for joint detection and segmentation of vertebral bodies in CT images. By minimizing the sparse representation error of sampled intensity values, we are able to recover the oriented bounding box (OBB) and segmentation binary mask for each vertebral body in the CT image. The performance of the proposed SEM framework was evaluated on five CT images of the thoracolumbar spine. The resulting Euclidean distance of 1:75+/-1:02 mm, computed between the center points of recovered and corresponding reference OBBs, and Dice coefficient of 92:3+/-2:7%, computed between the resulting and corresponding reference segmentation binary masks, indicate that the proposed framework can successfully detect and segment vertebral bodies in CT images of the thoracolumbar spine.

  14. 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.

  15. MR and CT image fusion of the cervical spine: a noninvasive alternative to CT-myelography

    NASA Astrophysics Data System (ADS)

    Hu, Yangqiu; Mirza, Sohail K.; Jarvik, Jeffrey G.; Heagerty, Patrick J.; Haynor, David R.

    2005-04-01

    CT-Myelography (CTM) is routinely used for planning surgery for degenerative disease of the spine, but its invasive nature, significant potential morbidity, and high costs make a noninvasive substitute desirable. We report our work on evaluating CT and MR image fusion as an alternative to CTM. Because the spine is only piecewise rigid, a multi-rigid approach to the registration of spinal CT and MR images was developed (SPIE 2004), in which the spine on CT images is first segmented into separate vertebrae, each of which is then rigidly registered with the corresponding vertebra on MR images. The results are then blended to obtain fusion images. Since they contain information from both modalities, we hypothesized that fusion images would be equivalent to CTM. To test this we selected 34 patients who had undergone MRI and CTM for degenerative disease of the cervical spine, and used the multi-rigid approach to produce fused images. A clinical vignette for each patient was created and presented along with either CT/MR fusion images or CTM images. A group of spine surgeons are asked to formulate detailed surgical plans based on each set of images, and the surgical plans are compared. A similar study assessing diagnostic agreement is being performed with neuroradiologists, who also assess the accuracy of registration. Our work to date has demonstrated the feasibility of segmentation and multi-rigid fusion in clinical cases and the acceptability of the questionnaire to physicians. Preliminary analysis of one surgeon's and one neuroradiologist"s evaluation has been performed.

  16. 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.

  17. Implications of CT noise and artifacts for quantitative {sup 99m}Tc SPECT/CT imaging

    SciTech Connect

    Hulme, K. W.; Kappadath, S. C.

    2014-04-15

    Purpose: This paper evaluates the effects of computed tomography (CT) image noise and artifacts on quantitative single-photon emission computed-tomography (SPECT) imaging, with the aim of establishing an appropriate range of CT acquisition parameters for low-dose protocols with respect to accurate SPECT attenuation correction (AC). Methods: SPECT images of two geometric and one anthropomorphic phantom were reconstructed iteratively using CT scans acquired at a range of dose levels (CTDI{sub vol} = 0.4 to 46 mGy). Resultant SPECT image quality was evaluated by comparing mean signal, background noise, and artifacts to SPECT images reconstructed using the highest dose CT for AC. Noise injection was performed on linear-attenuation (μ) maps to determine the CT noise threshold for accurate AC. Results: High levels of CT noise (σ ∼ 200–400 HU) resulted in low μ-maps noise (σ ∼ 1%–3%). Noise levels greater than ∼10% in 140 keV μ-maps were required to produce visibly perceptible increases of ∼15% in {sup 99m}Tc SPECT images. These noise levels would be achieved at low CT dose levels (CTDI{sub vol} = 4 μGy) that are over 2 orders of magnitude lower than the minimum dose for diagnostic CT scanners. CT noise could also lower (bias) the expected μ values. The relative error in reconstructed SPECT signal trended linearly with the relative shift in μ. SPECT signal was, on average, underestimated in regions corresponding with beam-hardening artifacts in CT images. Any process that has the potential to change the CT number of a region by ∼100 HU (e.g., misregistration between CT images and SPECT images due to motion, the presence of contrast in CT images) could introduce errors in μ{sub 140} {sub keV} on the order of 10%, that in turn, could introduce errors on the order of ∼10% into the reconstructed {sup 99m}Tc SPECT image. Conclusions: The impact of CT noise on SPECT noise was demonstrated to be negligible for clinically achievable CT parameters. Because

  18. Development of contrast-enhanced rodent imaging using functional CT

    NASA Astrophysics Data System (ADS)

    Liang, Yun; Stantz, Keith M.; Krishnamurthi, Ganapathy; Steinmetz, Rosemary; Hutchins, Gary D.

    2003-05-01

    Micro-computed tomography (microCT) is capable of obtaining high-resolution images of skeletal tissues. However its image contrast among soft tissues remains inadequate for tumor detection. High speed functional computed tomography will be needed to image tumors by employing x-ray contrast medium. The functional microCT development will not only facilitate the image contrast enhancement among different tissues but also provide information of tumor physiology. To demonstrate the feasibility of functional CT in mouse imaging, sequential computed tomography is performed in mice after contrast material administration using a high-speed clinical CT scanner. Although the resolution of the clinical scanner is not sufficient to dissolve the anatomic details of rodents, bulky physiological parameters in major organs such as liver, kidney, pancreas, and ovaries (testicular) can be examined. For data analysis, a two-compartmental model is employed and implemented to characterize the tissue physiological parameters (regional blood flow, capillary permeability, and relative compartment volumes.) The measured contrast dynamics in kidneys are fitted with the compartmental model to derive the kidney tissue physiology. The study result suggests that it is feasible to extract mouse tissue physiology using functional CT imaging technology.

  19. [CT imaging--towards patient- and indication-specific optimization].

    PubMed

    Kortesniemi, Mika; Lantto, Eila

    2015-01-01

    The same CT imaging program should not be applied to all patients, because the required image quality and dose of radiation vary according to the indications and regions. The programs should be optimized on the basis of indication, size of the patient and usage of intravenously administered iodine contrast agent. New technical options are available for reducing the radiation exposure. Additional means of optimization include proper definition of the region being imaged, avoidance of redundant series of images, selection of correct image quality, tube current and voltage, and new methods of calculating images. Patients' radiation exposure and clinical image quality should also be monitored.

  20. Acute small bowel ischemia: CT imaging findings.

    PubMed

    Segatto, Enrica; Mortelé, Koenraad J; Ji, Hoon; Wiesner, Walter; Ros, Pablo R

    2003-10-01

    Small bowel ischemia is a disorder related to a variety of conditions resulting in interruption or reduction of the blood supply of the small intestine. It may present with various clinical and radiologic manifestations, and ranges pathologically from localized transient ischemia to catastrophic necrosis of the intestinal tract. The primary causes of insufficient blood flow to the small intestine are various and include thromboembolism (50% of cases), nonocclusive causes, bowel obstruction, neoplasms, vasculitis, abdominal inflammatory conditions, trauma, chemotherapy, radiation, and corrosive injury. Computed tomography (CT) can demonstrate changes because of ischemic bowel accurately, may be helpful in determining the primary cause of ischemia, and can demonstrate important coexistent findings or complications. However, common CT findings in acute small bowel ischemia are not specific and, therefore, it is often a combination of clinical, laboratory and radiologic signs that may lead to a correct diagnosis. Understanding the pathogenesis of various conditions leading to mesenteric ischemia and being familiar with the spectrum of diagnostic CT signs may help the radiologist recognize ischemic small bowel disease and avoid delayed diagnosis. The aim of this article is to provide a review of the pathogenesis and various causes of acute small bowel ischemia and to demonstrate the contribution of CT in the diagnosis of this complex disease.

  1. Pulmonary nodule, solitary - CT scan (image)

    MedlinePlus

    ... a single lesion (pulmonary nodule) in the right lung. This nodule is seen as the light circle in the upper portion of the dark area on the left side of the picture. A normal lung would look completely black in a CT scan.

  2. Adjunct processors in embedded medical imaging systems

    NASA Astrophysics Data System (ADS)

    Trepanier, Marc; Goddard, Iain

    2002-05-01

    Adjunct processors have traditionally been used for certain tasks in medical imaging systems. Often based on application-specific integrated circuits (ASICs), these processors formed X-ray image-processing pipelines or constituted the backprojectors in computed tomography (CT) systems. We examine appropriate functions to perform with adjunct processing and draw some conclusions about system design trade-offs. These trade-offs have traditionally focused on the required performance and flexibility of individual system components, with increasing emphasis on time-to-market impact. Typically, front-end processing close to the sensor has the most intensive processing requirements. However, the performance capabilities of each level are dynamic and the system architect must keep abreast of the current capabilities of all options to remain competitive. Designers are searching for the most efficient implementation of their particular system requirements. We cite algorithm characteristics that point to effective solutions by adjunct processors. We have developed a field- programmable gate array (FPGA) adjunct-processor solution for a Cone-Beam Reconstruction (CBR) algorithm that offers significant performance improvements over a general-purpose processor implementation. The same hardware could efficiently perform other image processing functions such as two-dimensional (2D) convolution. The potential performance, price, operating power, and flexibility advantages of an FPGA adjunct processor over an ASIC, DSP or general-purpose processing solutions are compelling.

  3. Joint Lung CT Image Segmentation: A Hierarchical Bayesian Approach

    PubMed Central

    Cheng, Wenjun; Ma, Luyao; Yang, Tiejun; Liang, Jiali

    2016-01-01

    Accurate lung CT image segmentation is of great clinical value, especially when it comes to delineate pathological regions including lung tumor. In this paper, we present a novel framework that jointly segments multiple lung computed tomography (CT) images via hierarchical Dirichlet process (HDP). In specifics, based on the assumption that lung CT images from different patients share similar image structure (organ sets and relative positioning), we derive a mathematical model to segment them simultaneously so that shared information across patients could be utilized to regularize each individual segmentation. Moreover, compared to many conventional models, the algorithm requires little manual involvement due to the nonparametric nature of Dirichlet process (DP). We validated proposed model upon clinical data consisting of healthy and abnormal (lung cancer) patients. We demonstrate that, because of the joint segmentation fashion, more accurate and consistent segmentations could be obtained. PMID:27611188

  4. Processing of medical images using Maple

    NASA Astrophysics Data System (ADS)

    Toro Betancur, V.

    2013-05-01

    Maple's Image Tools package was used to process medical images. The results showed clearer images and records of its intensities and entropy. The medical images of a rhinocerebral mucormycosis patient, who was not early diagnosed, were processed and analyzed using Maple's tools, which showed, in a clearer way, the affected parts in the perinasal cavities.

  5. A simple method for labeling CT images with respiratory states

    SciTech Connect

    Berlinger, Kajetan; Sauer, Otto; Vences, Lucia; Roth, Michael

    2006-09-15

    A method is described for labeling CT images with their respiratory state by a needle, connected to the patient's chest/abdomen. By means of a leverage the needle follows the abdominal respiratory motion. The needle is visible as a blurred spot in every CT slice. The method was tested with nine patients. A series of volume scans during free breathing was performed. The detected positions of the moving needle in every single slice were compared to each other thus enabling respiratory state assignment. The tool is an inexpensive alternative to complex respiratory measuring tools for four dimensional (4D) CT and was greatly accepted in the clinic due to its simplicity.

  6. Cloud computing in medical imaging.

    PubMed

    Kagadis, George C; Kloukinas, Christos; Moore, Kevin; Philbin, Jim; Papadimitroulas, Panagiotis; Alexakos, Christos; Nagy, Paul G; Visvikis, Dimitris; Hendee, William R

    2013-07-01

    Over the past century technology has played a decisive role in defining, driving, and reinventing procedures, devices, and pharmaceuticals in healthcare. Cloud computing has been introduced only recently but is already one of the major topics of discussion in research and clinical settings. The provision of extensive, easily accessible, and reconfigurable resources such as virtual systems, platforms, and applications with low service cost has caught the attention of many researchers and clinicians. Healthcare researchers are moving their efforts to the cloud, because they need adequate resources to process, store, exchange, and use large quantities of medical data. This Vision 20/20 paper addresses major questions related to the applicability of advanced cloud computing in medical imaging. The paper also considers security and ethical issues that accompany cloud computing.

  7. 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

  8. Adaptively Tuned Iterative Low Dose CT Image Denoising.

    PubMed

    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.

  9. 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.

  10. 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

  11. PET/CT for radiotherapy: image acquisition and data processing.

    PubMed

    Bettinardi, V; Picchio, M; Di Muzio, N; Gianolli, L; Messa, C; Gilardi, M C

    2010-10-01

    This paper focuses on acquisition and processing methods in positron emission tomography/computed tomography (PET/CT) for radiotherapy (RT) applications. The recent technological evolutions of PET/CT systems are described. Particular emphasis is dedicated to the tools needed for the patient positioning and immobilization, to be used in PET/CT studies as well as during RT treatment sessions. The effect of organ and lesion motion due to patient's respiration on PET/CT imaging is discussed. Breathing protocols proposed to minimize PET/CT spatial mismatches in relation to respiratory movements are illustrated. The respiratory gated (RG) 4D-PET/CT techniques, developed to measure and compensate for organ and lesion motion, are then introduced. Finally a description is provided of different acquisition and data processing techniques, implemented with the aim at improving: i) image quality and quantitative accuracy of PET images, and ii) target volume definition and treatment planning in RT, by using specific and personalised motion information.

  12. Multiscale registration of planning CT and daily cone beam CT images for adaptive radiation therapy

    SciTech Connect

    Paquin, Dana; Levy, Doron; Xing Lei

    2009-01-15

    Adaptive radiation therapy (ART) is the incorporation of daily images in the radiotherapy treatment process so that the treatment plan can be evaluated and modified to maximize the amount of radiation dose to the tumor while minimizing the amount of radiation delivered to healthy tissue. Registration of planning images with daily images is thus an important component of ART. In this article, the authors report their research on multiscale registration of planning computed tomography (CT) images with daily cone beam CT (CBCT) images. The multiscale algorithm is based on the hierarchical multiscale image decomposition of E. Tadmor, S. Nezzar, and L. Vese [Multiscale Model. Simul. 2(4), pp. 554-579 (2004)]. Registration is achieved by decomposing the images to be registered into a series of scales using the (BV, L{sup 2}) decomposition and initially registering the coarsest scales of the image using a landmark-based registration algorithm. The resulting transformation is then used as a starting point to deformably register the next coarse scales with one another. This procedure is iterated at each stage using the transformation computed by the previous scale registration as the starting point for the current registration. The authors present the results of studies of rectum, head-neck, and prostate CT-CBCT registration, and validate their registration method quantitatively using synthetic results in which the exact transformations our known, and qualitatively using clinical deformations in which the exact results are not known.

  13. 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.

  14. 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.

  15. 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.

  16. A curvelet transform approach for the fusion of MR and CT images

    NASA Astrophysics Data System (ADS)

    Ali, F. E.; El-Dokany, I. M.; Saad, A. A.; Abd El-Samie, F. E.

    2010-02-01

    There are several medical imaging techniques such as the magnetic resonance (MR) and the computed tomography (CT) techniques. Both techniques give sophisticated characteristics of the region to be imaged. This paper proposes a curvelet based approach for fusing MR and CT images to obtain images with as much detail as possible, for the sake of medical diagnosis. This approach is based on the application of the additive wavelet transform (AWT) on both images and the segmentation of their detail planes into small overlapping tiles. The ridgelet transform is then applied on each of these tiles, and the fusion process is performed on the ridgelet transforms of the tiles. Simulation results show the superiority of the proposed curvelet fusion approach to the traditional fusion techniques like the multiresolution discrete wavelet transform (DWT) technique and the principal component analysis (PCA) technique. The fusion of MR and CT images in the presence of noise is also studied and the results reveal that unlike the DWT fusion technique, the proposed curvelet fusion approach doesn't require denoising.

  17. 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.

  18. 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

  19. Objective index of image fidelity for JPEG2000 compressed body CT images

    SciTech Connect

    Kim, Kil Joong; Lee, Kyoung Ho; Kang, Heung-Sik; Kim, So Yeon; Kim, Young Hoon; Kim, Bohyoung; Seo, Jinwook; Mantiuk, Rafal

    2009-07-15

    Compression ratio (CR) has been the de facto standard index of compression level for medical images. The aim of the study is to evaluate the CR, peak signal-to-noise ratio (PSNR), and a perceptual quality metric (high-dynamic range visual difference predictor HDR-VDP) as objective indices of image fidelity for Joint Photographic Experts Group (JPEG) 2000 compressed body computed tomography (CT) images, from the viewpoint of visually lossless compression approach. A total of 250 body CT images obtained with five different scan protocols (5-mm-thick abdomen, 0.67-mm-thick abdomen, 5-mm-thick lung, 0.67-mm-thick lung, and 5-mm-thick low-dose lung) were compressed to one of five CRs (reversible, 6:1, 8:1, 10:1, and 15:1). The PSNR and HDR-VDP values were calculated for the 250 pairs of the original and compressed images. By alternately displaying an original and its compressed image on the same monitor, five radiologists independently determined if the pair was distinguishable or indistinguishable. The kappa statistic for the interobserver agreement among the five radiologists' responses was 0.70. According to the radiologists' responses, the number of distinguishable image pairs tended to significantly differ among the five scan protocols at 6:1-10:1 compressions (Fisher-Freeman-Halton exact tests). Spearman's correlation coefficients between each of the CR, PSNR, and HDR-VDP and the number of radiologists who responded as distinguishable were 0.72, -0.77, and 0.85, respectively. Using the radiologists' pooled responses as the reference standards, the areas under the receiver-operating-characteristic curves for the CR, PSNR, and HDR-VDP were 0.87, 0.93, and 0.97, respectively, showing significant differences between the CR and PSNR (p=0.04), or HDR-VDP (p<0.001), and between the PSNR and HDR-VDP (p<0.001). In conclusion, the CR is less suitable than the PSNR or HDR-VDP as an objective index of image fidelity for JPEG2000 compressed body CT images. The HDR-VDP is more

  20. Window classification of brain CT images in biomedical articles.

    PubMed

    Xue, Zhiyun; Antani, Sameer; Long, L Rodney; Demner-Fushman, Dina; Thoma, George R

    2012-01-01

    Effective capability to search biomedical articles based on visual properties of article images may significantly augment information retrieval in the future. In this paper, we present a new method to classify the window setting types of brain CT images. Windowing is a technique frequently used in the evaluation of CT scans, and is used to enhance contrast for the particular tissue or abnormality type being evaluated. In particular, it provides radiologists with an enhanced view of certain types of cranial abnormalities, such as the skull lesions and bone dysplasia which are usually examined using the " bone window" setting and illustrated in biomedical articles using "bone window images". Due to the inherent large variations of images among articles, it is important that the proposed method is robust. Our algorithm attained 90% accuracy in classifying images as bone window or non-bone window in a 210 image data set.

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

    SciTech Connect

    Kipritidis, J; Woodruff, H; Counter, W; Keall, P; Hofman, M; Siva, S; Callahan, J; Le Roux, P; Hardcastle, N

    2015-06-15

    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. 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

  2. Liver recognition based on statistical shape model in CT images

    NASA Astrophysics Data System (ADS)

    Xiang, Dehui; Jiang, Xueqing; Shi, Fei; Zhu, Weifang; Chen, Xinjian

    2016-03-01

    In this paper, an automatic method is proposed to recognize the liver on clinical 3D CT images. The proposed method effectively use statistical shape model of the liver. Our approach consist of three main parts: (1) model training, in which shape variability is detected using principal component analysis from the manual annotation; (2) model localization, in which a fast Euclidean distance transformation based method is able to localize the liver in CT images; (3) liver recognition, the initial mesh is locally and iteratively adapted to the liver boundary, which is constrained with the trained shape model. We validate our algorithm on a dataset which consists of 20 3D CT images obtained from different patients. The average ARVD was 8.99%, the average ASSD was 2.69mm, the average RMSD was 4.92mm, the average MSD was 28.841mm, and the average MSD was 13.31%.

  3. Medical Image Retrieval: A Multimodal Approach

    PubMed Central

    Cao, Yu; Steffey, Shawn; He, Jianbiao; Xiao, Degui; Tao, Cui; Chen, Ping; Müller, Henning

    2014-01-01

    Medical imaging is becoming a vital component of war on cancer. Tremendous amounts of medical image data are captured and recorded in a digital format during cancer care and cancer research. Facing such an unprecedented volume of image data with heterogeneous image modalities, it is necessary to develop effective and efficient content-based medical image retrieval systems for cancer clinical practice and research. While substantial progress has been made in different areas of content-based image retrieval (CBIR) research, direct applications of existing CBIR techniques to the medical images produced unsatisfactory results, because of the unique characteristics of medical images. In this paper, we develop a new multimodal medical image retrieval approach based on the recent advances in the statistical graphic model and deep learning. Specifically, we first investigate a new extended probabilistic Latent Semantic Analysis model to integrate the visual and textual information from medical images to bridge the semantic gap. We then develop a new deep Boltzmann machine-based multimodal learning model to learn the joint density model from multimodal information in order to derive the missing modality. Experimental results with large volume of real-world medical images have shown that our new approach is a promising solution for the next-generation medical imaging indexing and retrieval system. PMID:26309389

  4. 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.

  5. A biological phantom for evaluation of CT image reconstruction algorithms

    NASA Astrophysics Data System (ADS)

    Cammin, J.; Fung, G. S. K.; Fishman, E. K.; Siewerdsen, J. H.; Stayman, J. W.; Taguchi, K.

    2014-03-01

    In recent years, iterative algorithms have become popular in diagnostic CT imaging to reduce noise or radiation dose to the patient. The non-linear nature of these algorithms leads to non-linearities in the imaging chain. However, the methods to assess the performance of CT imaging systems were developed assuming the linear process of filtered backprojection (FBP). Those methods may not be suitable any longer when applied to non-linear systems. In order to evaluate the imaging performance, a phantom is typically scanned and the image quality is measured using various indices. For reasons of practicality, cost, and durability, those phantoms often consist of simple water containers with uniform cylinder inserts. However, these phantoms do not represent the rich structure and patterns of real tissue accurately. As a result, the measured image quality or detectability performance for lesions may not reflect the performance on clinical images. The discrepancy between estimated and real performance may be even larger for iterative methods which sometimes produce "plastic-like", patchy images with homogeneous patterns. Consequently, more realistic phantoms should be used to assess the performance of iterative algorithms. We designed and constructed a biological phantom consisting of porcine organs and tissue that models a human abdomen, including liver lesions. We scanned the phantom on a clinical CT scanner and compared basic image quality indices between filtered backprojection and an iterative reconstruction algorithm.

  6. Pixel-feature hybrid fusion for PET/CT images.

    PubMed

    Zhu, Yang-Ming; Nortmann, Charles A

    2011-02-01

    Color blending is a popular display method for functional and anatomic image fusion. The underlay image is typically displayed in grayscale, and the overlay image is displayed in pseudo colors. This pixel-level fusion provides too much information for reviewers to analyze quickly and effectively and clutters the display. To improve the fusion image reviewing speed and reduce the information clutter, a pixel-feature hybrid fusion method is proposed and tested for PET/CT images. Segments of the colormap are selectively masked to have a few discrete colors, and pixels displayed in the masked colors are made transparent. The colormap thus creates a false contouring effect on overlay images and allows the underlay to show through to give contours an anatomic context. The PET standardized uptake value (SUV) is used to control where colormap segments are masked. Examples show that SUV features can be extracted and blended with CT image instantaneously for viewing and diagnosis, and the non-feature part of the PET image is transparent. The proposed pixel-feature hybrid fusion highlights PET SUV features on CT images and reduces display clutters. It is easy to implement and can be used as complementarily to existing pixel-level fusion methods.

  7. Improved elastic medical image registration using mutual information

    NASA Astrophysics Data System (ADS)

    Ens, Konstantin; Schumacher, Hanno; Franz, Astrid; Fischer, Bernd

    2007-03-01

    One of the future-oriented areas of medical image processing is to develop fast and exact algorithms for image registration. By joining multi-modal images we are able to compensate the disadvantages of one imaging modality with the advantages of another modality. For instance, a Computed Tomography (CT) image containing the anatomy can be combined with metabolic information of a Positron Emission Tomography (PET) image. It is quite conceivable that a patient will not have the same position in both imaging systems. Furthermore some regions for instance in the abdomen can vary in shape and position due to different filling of the rectum. So a multi-modal image registration is needed to calculate a deformation field for one image in order to maximize the similarity between the two images, described by a so-called distance measure. In this work, we present a method to adapt a multi-modal distance measure, here mutual information (MI), with weighting masks. These masks are used to enhance relevant image structures and suppress image regions which otherwise would disturb the registration process. The performance of our method is tested on phantom data and real medical images.

  8. 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

  9. PET/CT imaging in lung cancer: indications and findings*

    PubMed Central

    Hochhegger, Bruno; Alves, Giordano Rafael Tronco; Irion, Klaus Loureiro; Fritscher, Carlos Cezar; Fritscher, Leandro Genehr; Concatto, Natália Henz; Marchiori, Edson

    2015-01-01

    The use of PET/CT imaging in the work-up and management of patients with lung cancer has greatly increased in recent decades. The ability to combine functional and anatomical information has equipped PET/CT to look into various aspects of lung cancer, allowing more precise disease staging and providing useful data during the characterization of indeterminate pulmonary nodules. In addition, the accuracy of PET/CT has been shown to be greater than is that of conventional modalities in some scenarios, making PET/CT a valuable noninvasive method for the investigation of lung cancer. However, the interpretation of PET/CT findings presents numerous pitfalls and potential confounders. Therefore, it is imperative for pulmonologists and radiologists to familiarize themselves with the most relevant indications for and limitations of PET/CT, seeking to protect their patients from unnecessary radiation exposure and inappropriate treatment. This review article aimed to summarize the basic principles, indications, cancer staging considerations, and future applications related to the use of PET/CT in lung cancer. PMID:26176525

  10. Potential Lung Nodules Identification for Characterization by Variable Multistep Threshold and Shape Indices from CT Images

    PubMed Central

    Iqbal, Saleem; Iqbal, Khalid; Shaukat, Arslan; Khanum, Aasia

    2014-01-01

    Computed tomography (CT) is an important imaging modality. Physicians, surgeons, and oncologists prefer CT scan for diagnosis of lung cancer. However, some nodules are missed in CT scan. Computer aided diagnosis methods are useful for radiologists for detection of these nodules and early diagnosis of lung cancer. Early detection of malignant nodule is helpful for treatment. Computer aided diagnosis of lung cancer involves lung segmentation, potential nodules identification, features extraction from the potential nodules, and classification of the nodules. In this paper, we are presenting an automatic method for detection and segmentation of lung nodules from CT scan for subsequent features extraction and classification. Contribution of the work is the detection and segmentation of small sized nodules, low and high contrast nodules, nodules attached with vasculature, nodules attached to pleura membrane, and nodules in close vicinity of the diaphragm and lung wall in one-go. The particular techniques of the method are multistep threshold for the nodule detection and shape index threshold for false positive reduction. We used 60 CT scans of “Lung Image Database Consortium-Image Database Resource Initiative” taken by GE medical systems LightSpeed16 scanner as dataset and correctly detected 92% nodules. The results are reproducible. PMID:25506388

  11. Potential lung nodules identification for characterization by variable multistep threshold and shape indices from CT images.

    PubMed

    Iqbal, Saleem; Iqbal, Khalid; Arif, Fahim; Shaukat, Arslan; Khanum, Aasia

    2014-01-01

    Computed tomography (CT) is an important imaging modality. Physicians, surgeons, and oncologists prefer CT scan for diagnosis of lung cancer. However, some nodules are missed in CT scan. Computer aided diagnosis methods are useful for radiologists for detection of these nodules and early diagnosis of lung cancer. Early detection of malignant nodule is helpful for treatment. Computer aided diagnosis of lung cancer involves lung segmentation, potential nodules identification, features extraction from the potential nodules, and classification of the nodules. In this paper, we are presenting an automatic method for detection and segmentation of lung nodules from CT scan for subsequent features extraction and classification. Contribution of the work is the detection and segmentation of small sized nodules, low and high contrast nodules, nodules attached with vasculature, nodules attached to pleura membrane, and nodules in close vicinity of the diaphragm and lung wall in one-go. The particular techniques of the method are multistep threshold for the nodule detection and shape index threshold for false positive reduction. We used 60 CT scans of "Lung Image Database Consortium-Image Database Resource Initiative" taken by GE medical systems LightSpeed16 scanner as dataset and correctly detected 92% nodules. The results are reproducible.

  12. Microcomputer-based image processing system for CT/MRI scans: II. Expert system

    NASA Astrophysics Data System (ADS)

    Kwok, John C. K.; Yu, Peter K. N.; Cheng, Andrew Y. S.; Ho, Wai-Chin

    1991-06-01

    A microcomputer-based image processing system is used to digitize and process serial sections of CT/MRI scan and reconstruct three-dimensional images of brain structures and brain lesions. The images grabbed also serve as templates and different vital regions with different risk values are also traced out for 3D reconstruction. A knowledge-based system employing rule-based programming has been built to help identifying brain lesions and to help planning trajectory for operations. The volumes of the lesions are also automatically determined. Such system is very useful for medical skills archival, tumor size monitoring, survival and outcome forecasting, and consistent neurosurgical planning.

  13. 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.

  14. Evaluation of segmentation using lung nodule phantom CT images

    NASA Astrophysics Data System (ADS)

    Judy, Philip F.; Jacobson, Francine L.

    2001-07-01

    Segmentation of chest CT images has several purposes. In lung-cancer screening programs, for nodules below 5mm, growth measured from sequential CT scans is the primary indication of malignancy. Automatic segmentation procedures have been used as a means to insure a reliable measurement of lung nodule size. A lung nodule phantom was developed to evaluate the validity and reliability of size measurements using CT images. Thirty acrylic spheres and cubes (2-8 mm) were placed in a 15cm diameter disk of uniform-material that simulated the lung. To demonstrate the use of the phantom, it was scanned using out hospital's lung-cancer screening protocol. A simple, yet objective threshold technique was used to segment all of the images in which the objects were visible. All the pixels above a common threshold (the mean of the lung material and the acrylic CT numbers) were considered within the nodule. The relative bias did not depend on the shape of the objects and ranged from -18% for the 2 mm objects to -2.5% for 8-mm objects. DICOM image files of the phantom are available for investigators with an interest in using the images to evaluate and compare segmentation procedures.

  15. Knowledge-Based Analysis And Understanding Of 3D Medical Images

    NASA Astrophysics Data System (ADS)

    Dhawan, Atam P.; Juvvadi, Sridhar

    1988-06-01

    The anatomical three-dimensional (3D) medical imaging modalities, such as X-ray CT and MRI, have been well recognized in the diagnostic radiology for several years while the nuclear medicine modalities, such as PET, have just started making a strong impact through functional imaging. Though PET images provide the functional information about the human organs, they are hard to interpret because of the lack of anatomical information. Our objective is to develop a knowledge-based biomedical image analysis system which can interpret the anatomical images (such as CT). The anatomical information thus obtained can then be used in analyzing PET images of the same patient. This will not only help in interpreting PET images but it will also provide a means of studying the correlation between the anatomical and functional imaging. This paper presents the preliminary results of the knowledge based biomedical image analysis system for interpreting CT images of the chest.

  16. Automated planning of breast radiotherapy using cone beam CT imaging

    SciTech Connect

    Amit, Guy; Purdie, Thomas G.

    2015-02-15

    Purpose: Develop and clinically validate a methodology for using cone beam computed tomography (CBCT) imaging in an automated treatment planning framework for breast IMRT. Methods: A technique for intensity correction of CBCT images was developed and evaluated. The technique is based on histogram matching of CBCT image sets, using information from “similar” planning CT image sets from a database of paired CBCT and CT image sets (n = 38). Automated treatment plans were generated for a testing subset (n = 15) on the planning CT and the corrected CBCT. The plans generated on the corrected CBCT were compared to the CT-based plans in terms of beam parameters, dosimetric indices, and dose distributions. Results: The corrected CBCT images showed considerable similarity to their corresponding planning CTs (average mutual information 1.0±0.1, average sum of absolute differences 185 ± 38). The automated CBCT-based plans were clinically acceptable, as well as equivalent to the CT-based plans with average gantry angle difference of 0.99°±1.1°, target volume overlap index (Dice) of 0.89±0.04 although with slightly higher maximum target doses (4482±90 vs 4560±84, P < 0.05). Gamma index analysis (3%, 3 mm) showed that the CBCT-based plans had the same dose distribution as plans calculated with the same beams on the registered planning CTs (average gamma index 0.12±0.04, gamma <1 in 99.4%±0.3%). Conclusions: The proposed method demonstrates the potential for a clinically feasible and efficient online adaptive breast IMRT planning method based on CBCT imaging, integrating automation.

  17. CT scan of the brain (image)

    MedlinePlus

    ... CAT scan (computed tomography) is a much more sensitive imaging technique than x-ray, allowing high definition not only of the bony structures, but of the soft tissues. Clear images of organs such as the brain, muscles, joint structures, veins ...

  18. "Conventional" CT images from spectral measurements

    NASA Astrophysics Data System (ADS)

    Rajbhandary, Paurakh L.; Pelc, Norbert J.

    2016-03-01

    Spectral imaging systems need to be able to produce "conventional" images, and it's been shown that systems with energy discriminating detectors can achieve higher CNR than conventional systems by optimal weighting. Combining measured data in energy bins (EBs) and also combining basis material images have previously been proposed, but there are no studies systematically comparing the two methods. In this paper, we analytically evaluate the two methods for systems with ideal photon counting detectors using CNR and beam hardening (BH) artifact as metrics. For a 120-kVp polychromatic simulations of a water phantom with low contrast inserts, the difference of the optimal CNR between the two methods for the studied phantom is within 2%. For a polychromatic spectrum, beam-hardening artifacts are noticeable in EB weighted images (BH artifact of 3.8% for 8 EB and 6.9% for 2 EB), while weighted basis material images are free of such artifacts.

  19. NASA Technology Finds Uses in Medical Imaging

    NASA Video Gallery

    NASA software has been incorporated into a new medical imaging device that could one day aid in the interpretation of mammograms, ultrasounds, and other medical imagery. The new MED-SEG system, dev...

  20. CT Angiography (CTA)

    MedlinePlus

    ... CT Angiography? Angiography is a minimally invasive medical test that helps physicians diagnose and treat medical conditions. Angiography uses one of three imaging technologies and, in most cases, a contrast material injection ...

  1. 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.

  2. Computer-aided diagnosis workstation for chest diagnosis based on multihelical CT images

    NASA Astrophysics Data System (ADS)

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

    2005-04-01

    Mass screening based on 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. This electronic medical recording system and prototype internet system were developed so as not to loosen the communication among staffs of hospital. 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.

  3. Annotation-free probabilistic atlas learning for robust anatomy detection in CT images

    NASA Astrophysics Data System (ADS)

    Franz, Astrid; Schadewaldt, Nicole; Schulz, Heinrich; Vik, Torbjørn; Kausch, Lisa; Modersitzki, Jan; Wiemker, Rafael; Bystrov, Daniel

    2015-03-01

    A fully automatic method generating a whole body atlas from CT images is presented. The atlas serves as a reference space for annotations. It is based on a large collection of partially overlapping medical images and a registration scheme. The atlas itself consists of probabilistic tissue type maps and can represent anatomical variations. The registration scheme is based on an entropy-like measure of these maps and is robust with respect to field-of-view variations. In contrast to other atlas generation methods, which typically rely on a sufficiently large set of annotations on training cases, the presented method requires only the images. An iterative refinement strategy is used to automatically stitch the images to build the atlas. Affine registration of unseen CT images to the probabilistic atlas can be used to transfer reference annotations, e.g. organ models for segmentation initialization or reference bounding boxes for field-of-view selection. The robustness and generality of the method is shown using a three-fold cross-validation of the registration on a set of 316 CT images of unknown content and large anatomical variability. As an example, 17 organs are annotated in the atlas reference space and their localization in the test images is evaluated. The method yields a recall (sensitivity), specificity and precision of at least 96% and thus performs excellent in comparison to competitors.

  4. Aliphatic polyesters for medical imaging and theranostic applications.

    PubMed

    Nottelet, Benjamin; Darcos, Vincent; Coudane, Jean

    2015-11-01

    Medical imaging is a cornerstone of modern medicine. In that context the development of innovative imaging systems combining biomaterials and contrast agents (CAs)/imaging probes (IPs) for improved diagnostic and theranostic applications focuses intense research efforts. In particular, the classical aliphatic (co)polyesters poly(lactide) (PLA), poly(lactide-co-glycolide) (PLGA) and poly(ɛ-caprolactone) (PCL), attract much attention due to their long track record in the medical field. This review aims therefore at providing a state-of-the-art of polyester-based imaging systems. In a first section a rapid description of the various imaging modalities, including magnetic resonance imaging (MRI), optical imaging, computed tomography (CT), ultrasound (US) and radionuclide imaging (SPECT, PET) will be given. Then, the two main strategies used to combine the CAs/IPs and the polyesters will be discussed. In more detail we will first present the strategies relying on CAs/IPs encapsulation in nanoparticles, micelles, dendrimers or capsules. We will then present chemical modifications of polyesters backbones and/or polyester surfaces to yield macromolecular imaging agents. Finally, opportunities offered by these innovative systems will be illustrated with some recent examples in the fields of cell labeling, diagnostic or theranostic applications and medical devices.

  5. Dental imaging using laminar optical tomography and micro CT

    NASA Astrophysics Data System (ADS)

    Long, Feixiao; Ozturk, Mehmet S.; Intes, Xavier; Kotha, Shiva

    2014-02-01

    Dental lesions located in the pulp are quite difficult to identify based on anatomical contrast, and, hence, to diagnose using traditional imaging methods such as dental CT. However, such lesions could lead to functional and/or molecular optical contrast. Herein, we report on the preliminary investigation of using Laminar Optical Tomography (LOT) to image the pulp and root canals in teeth. LOT is a non-contact, high resolution, molecular and functional mesoscopic optical imaging modality. To investigate the potential of LOT for dental imaging, we injected an optical dye into ex vivo teeth samples and imaged them using LOT and micro-CT simultaneously. A rigid image registration between the LOT and micro-CT reconstruction was obtained, validating the potential of LOT to image molecular optical contrast deep in the teeth with accuracy, non-invasively. We demonstrate that LOT can retrieve the 3D bio-distribution of molecular probes at depths up to 2mm with a resolution of several hundred microns in teeth.

  6. Influence of segmentation on micro-CT images of trabecular bone.

    PubMed

    Tassani, S; Korfiatis, V; Matsopoulos, G K

    2014-11-01

    Segmentation of biomedical images is of great importance in various studies aiming to both the identification of regions of interests within the image and the performance of quantified measurements. Nevertheless, the segmentation of the biomedical images represents a wide range of medical cases and there is not a unique technique applicable to all kinds of medical images. In this study, three popular techniques for segmenting micro-CT images of bone microstructures are evaluated. Fixed threshold, Otsu's algorithm and a modified version of the Chan-Vese segmentation technique have been applied on micro-CT images and have been compared to higher resolution golden standard, that is histological images. The modification of the Chan-Vese technique is based on the novel implementation of a new initialization process called the Branch Point Initialization. Stereological measurements were performed on all the segmented images and statistically compared to the golden standard. Fixed threshold and the modified Chan-Vese technique have shown comparable results, with a maximum significant error of about 10%. However, Chan-Vese showed an easier, faster and more reliable segmentation procedure for optimal settings identification. The Otsu's method showed a maximum error larger than 20%. Given the limits and advantages of the known segmentation techniques, the proposed modified Chan-Vese active contour technique shows high potential for use in the segmentation of micro-CT images as well as in other high-resolution X-ray images. This potential is augmented by the recent introduction of high-resolution clinical technologies for which standard techniques have already shown to be insufficient.

  7. 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

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

    PubMed

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

    2012-05-07

    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 (68)Ga/(68)Ge 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.

  9. Accuracy of CT-Based Attenuation Correction in PET/CT Bone Imaging

    PubMed Central

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

    2012-01-01

    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 range 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. PMID:22481547

  10. Computer aided detection of oral lesions on CT images

    NASA Astrophysics Data System (ADS)

    Galib, S.; Islam, F.; Abir, M.; Lee, H. K.

    2015-12-01

    Oral lesions are important findings on computed tomography (CT) images. In this study, a fully automatic method to detect oral lesions in mandibular region from dental CT images is proposed. Two methods were developed to recognize two types of lesions namely (1) Close border (CB) lesions and (2) Open border (OB) lesions, which cover most of the lesion types that can be found on CT images. For the detection of CB lesions, fifteen features were extracted from each initial lesion candidates and multi layer perceptron (MLP) neural network was used to classify suspicious regions. Moreover, OB lesions were detected using a rule based image processing method, where no feature extraction or classification algorithm were used. The results were validated using a CT dataset of 52 patients, where 22 patients had abnormalities and 30 patients were normal. Using non-training dataset, CB detection algorithm yielded 71% sensitivity with 0.31 false positives per patient. Furthermore, OB detection algorithm achieved 100% sensitivity with 0.13 false positives per patient. Results suggest that, the proposed framework, which consists of two methods, has the potential to be used in clinical context, and assist radiologists for better diagnosis.

  11. A dual micro-CT system for small animal imaging

    NASA Astrophysics Data System (ADS)

    Badea, C. T.; Johnston, S.; Johnson, B.; Lin, M.; Hedlund, L. W.; Johnson, G. Allan

    2008-03-01

    Micro-CT is a non-invasive imaging modality usually used to assess morphology in small animals. In our previous work, we have demonstrated that functional micro-CT imaging is also possible. This paper describes a dual micro-CT system with two fixed x-ray/detectors developed to address such challenging tasks as cardiac or perfusion studies in small animals. A two-tube/detector system ensures simultaneous acquisition of two projections, thus reducing scanning time and the number of contrast injections in perfusion studies by a factor of two. The system is integrated with software developed in-house for cardio-respiratory monitoring and gating. The sampling geometry was optimized for 88 microns in such a way that the geometric blur of the focal spot matches the Nyquist sample at the detector. A geometric calibration procedure allows one to combine projection data from the two chains into a single reconstructed volume. Image quality was measured in terms of spatial resolution, uniformity, noise, and linearity. The modulation transfer function (MTF) at 10% is 3.4 lp/mm for single detector reconstructions and 2.3 lp/mm for dual tube/detector reconstructions. We attribute this loss in spatial resolution to the compounding of slight errors in the separate single chain calibrations. The dual micro-CT system is currently used in studies for morphological and functional imaging of both rats and mice.

  12. Brain Imaging Using Mobile CT: Current Status and Future Prospects.

    PubMed

    John, Seby; Stock, Sarah; Cerejo, Russell; Uchino, Ken; Winners, Stacey; Russman, Andrew; Masaryk, Thomas; Rasmussen, Peter; Hussain, Muhammad S

    2016-01-01

    Computed tomography (CT) is an invaluable tool in the diagnosis of many clinical conditions. Several advancements in biomedical engineering have achieved increase in speed, improvements in low-contrast detectability and image quality, and lower radiation. Portable or mobile CT constituted one such important advancement. It is especially useful in evaluating critically ill, intensive care unit patients by scanning them at bedside. A paradigm shift in utilization of mobile CT was its installation in ambulances for the management of acute stroke. Given the time sensitive nature of acute ischemic stroke, Mobile stroke units (MSU) were developed in Germany consisting of an ambulance equipped with a CT scanner, point of care laboratory system, along with teleradiological support. In a radical reconfiguration of stroke care, the MSU would bring the CT scanner to the stroke patient, without waiting for the patient at the emergency room. Two separate MSU projects in Saarland and Berlin demonstrated the safety and feasibility of this concept for prehospital stroke care, showing increased rate of intravenous thrombolysis and significant reduction in time to treatment compared to conventional care. MSU also improved the triage of patients to appropriate and specialized hospitals. Although multiple issues remain yet unanswered with the MSU concept including clinical outcome and cost-effectiveness, the MSU venture is visionary and enables delivery of life-saving and enhancing treatment for ischemic and hemorrhagic stroke. In this review, we discuss the development of mobile CT and its applications, with specific focus on its use in MSUs along with our institution's MSU experience.

  13. 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.

  14. Prototype 1.75 MV X-band linear accelerator testing for medical CT and industrial nondestructive testing applications

    NASA Astrophysics Data System (ADS)

    Clayton, James; Shedlock, Daniel; Vanderet, Steven; Zentai, George; Star-Lack, Josh; LaFave, Richard; Virshup, Gary

    2015-03-01

    Flat panel imagers based on amorphous silicon technology (a-Si) for digital radiography are accepted by the medical and industrial community as having several advantages over radiographic film-based systems. Use of Mega-voltage x-rays with these flat panel systems is applicable to both portal imaging for radiotherapy and for nondestructive testing (NDT) and security applications. In the medical field, one potential application that has not been greatly explored is to radiotherapy treatment planning. Currently, such conventional computed tomographic (CT) data acquired at kV energies is used to help delineate tumor targets and normal structures that are to be spared during treatment. CT number accuracy is crucial for radiotherapy dose calculations. Conventional CT scanners operating at kV X-ray energies typically exhibit significant image reconstruction artifacts in the presence of metal implants in human body. Using the X-ray treatment beams, having energies typically >=6MV, to acquire the CT data may not be practical if it is desired to maintain contrast sensitivity at a sufficiently low dose. Nondestructive testing imaging systems can expand their application space with the development of the higher energy accelerator for use in pipeline, and casting inspection as well as certain cargo screening applications that require more penetration. A new prototype x-band BCL designed to operate up to 1.75 MV has been designed built and tested. The BCL was tested with a prototype portal imager and medical phantoms to determine artifact reductions and a PaxScan 2530HE industrial imager to demonstrate resolution is maintained and penetration is improved.

  15. Imaging lobular breast carcinoma: comparison of synchrotron radiation DEI-CT technique with clinical CT, mammography and histology

    NASA Astrophysics Data System (ADS)

    Fiedler, S.; Bravin, A.; Keyriläinen, J.; Fernández, M.; Suortti, P.; Thomlinson, W.; Tenhunen, M.; Virkkunen, P.; Karjalainen-Lindsberg, M.-L.

    2004-01-01

    Different modalities for imaging cancer-bearing breast tissue samples are described and compared. The images include clinical mammograms and computed tomography (CT) images, CT images with partly coherent synchrotron radiation (SR), and CT and radiography images taken with SR using the diffraction enhanced imaging (DEI) method. The images are evaluated by a radiologist and compared with histopathological examination of the samples. Two cases of lobular carcinoma are studied in detail. The indications of cancer are very weak or invisible in the conventional images, but the morphological changes due to invasion of cancer become pronounced in the images taken by the DEI method. The strands penetrating adipose tissue are seen clearly in the DEI-CT images, and the histopathology confirms that some strands contain the so-called 'Indian file' formations of cancer cells. The radiation dose is carefully measured for each of the imaging modalities. The mean glandular dose (MGD) for 50% glandular breast tissue is about 1 mGy in conventional mammography and less than 0.25 mGy in projection DEI, while in the clinical CT imaging the MGD is very high, about 45 mGy. The entrance dose of 95 mGy in DEI-CT imaging gives rise to an MGD of 40 mGy, but the dose may be reduced by an order of magnitude, because the contrast is very large in most images.

  16. Holography and the virtual patient: the holographic medical image

    NASA Astrophysics Data System (ADS)

    Ko, Kathryn; Erickson, Ronald R.; Webster, John M.

    1996-12-01

    Practical holographic systems utilizing the pulsed laser are finding potential applications in medicine. Exploiting both the hologram's true 3D image and holographic interferometry these techniques enhance the physician's vision beyond the 2D radiological imaging of even the best CT and MRI. The authors describe the use of pulsed laser holography as applied to the morphological specialties: anatomy, pathology, and surgery. The authors report on the Holographic Brain Anatomy Atlas for medical education; pathologic documentation with holography, and the use of holographic interferometry in surgical planning. The techniques are outlined and a discussion on the interpretation of holographic interferometry with living subjects is provided.

  17. Tooling Techniques Enhance Medical Imaging

    NASA Technical Reports Server (NTRS)

    2012-01-01

    mission. The manufacturing techniques developed to create the components have yielded innovations advancing medical imaging, transportation security, and even energy efficiency.

  18. Computer-aided kidney segmentation on abdominal CT images.

    PubMed

    Lin, Daw-Tung; Lei, Chung-Chih; Hung, Siu-Wan

    2006-01-01

    In this paper, an effective model-based approach for computer-aided kidney segmentation of abdominal CT images with anatomic structure consideration is presented. This automatic segmentation system is expected to assist physicians in both clinical diagnosis and educational training. The proposed method is a coarse to fine segmentation approach divided into two stages. First, the candidate kidney region is extracted according to the statistical geometric location of kidney within the abdomen. This approach is applicable to images of different sizes by using the relative distance of the kidney region to the spine. The second stage identifies the kidney by a series of image processing operations. The main elements of the proposed system are: 1) the location of the spine is used as the landmark for coordinate references; 2) elliptic candidate kidney region extraction with progressive positioning on the consecutive CT images; 3) novel directional model for a more reliable kidney region seed point identification; and 4) adaptive region growing controlled by the properties of image homogeneity. In addition, in order to provide different views for the physicians, we have implemented a visualization tool that will automatically show the renal contour through the method of second-order neighborhood edge detection. We considered segmentation of kidney regions from CT scans that contain pathologies in clinical practice. The results of a series of tests on 358 images from 30 patients indicate an average correlation coefficient of up to 88% between automatic and manual segmentation.

  19. An improved level set method for vertebra CT image segmentation

    PubMed Central

    2013-01-01

    Background Clinical diagnosis and therapy for the lumbar disc herniation requires accurate vertebra segmentation. The complex anatomical structure and the degenerative deformations of the vertebrae makes its segmentation challenging. Methods An improved level set method, namely edge- and region-based level set method (ERBLS), is proposed for vertebra CT images segmentation. By considering the gradient information and local region characteristics of images, the proposed model can efficiently segment images with intensity inhomogeneity and blurry or discontinuous boundaries. To reduce the dependency on manual initialization in many active contour models and for an automatic segmentation, a simple initialization method for the level set function is built, which utilizes the Otsu threshold. In addition, the need of the costly re-initialization procedure is completely eliminated. Results Experimental results on both synthetic and real images demonstrated that the proposed ERBLS model is very robust and efficient. Compared with the well-known local binary fitting (LBF) model, our method is much more computationally efficient and much less sensitive to the initial contour. The proposed method has also applied to 56 patient data sets and produced very promising results. Conclusions An improved level set method suitable for vertebra CT images segmentation is proposed. It has the flexibility of segmenting the vertebra CT images with blurry or discontinuous edges, internal inhomogeneity and no need of re-initialization. PMID:23714300

  20. 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

  1. 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

  2. Gamma Knife radiosurgery with CT image-based dose calculation.

    PubMed

    Xu, Andy Yuanguang; Bhatnagar, Jagdish; Bednarz, Greg; Niranjan, Ajay; Kondziolka, Douglas; Flickinger, John; Lunsford, L Dade; Huq, M Saiful

    2015-11-01

    The Leksell GammaPlan software version 10 introduces a CT image-based segmentation tool for automatic skull definition and a convolution dose calculation algorithm for tissue inhomogeneity correction. The purpose of this work was to evaluate the impact of these new approaches on routine clinical Gamma Knife treatment planning. Sixty-five patients who underwent CT image-guided Gamma Knife radiosurgeries at the University of Pittsburgh Medical Center in recent years were retrospectively investigated. The diagnoses for these cases include trigeminal neuralgia, meningioma, acoustic neuroma, AVM, glioma, and benign and metastatic brain tumors. Dose calculations were performed for each patient with the same dose prescriptions and the same shot arrangements using three different approaches: 1) TMR 10 dose calculation with imaging skull definition; 2) convolution dose calculation with imaging skull definition; 3) TMR 10 dose calculation with conventional measurement-based skull definition. For each treatment matrix, the total treatment time, the target coverage index, the selectivity index, the gradient index, and a set of dose statistics parameters were compared between the three calculations. The dose statistics parameters investigated include the prescription isodose volume, the 12 Gy isodose volume, the minimum, maximum and mean doses on the treatment targets, and the critical structures under consideration. The difference between the convolution and the TMR 10 dose calculations for the 104 treatment matrices were found to vary with the patient anatomy, location of the treatment shots, and the tissue inhomogeneities around the treatment target. An average difference of 8.4% was observed for the total treatment times between the convolution and the TMR algorithms. The maximum differences in the treatment times, the prescription isodose volumes, the 12 Gy isodose volumes, the target coverage indices, the selectivity indices, and the gradient indices from the convolution

  3. Gamma Knife radiosurgery with CT image-based dose calculation.

    PubMed

    Xu, Andy Yuanguang; Bhatnagar, Jagdish; Bednarz, Greg; Niranjan, Ajay; Kondziolka, Douglas; Flickinger, John; Lunsford, L Dade; Huq, M Saiful

    2015-11-08

    The Leksell GammaPlan software version 10 introduces a CT image-based segmentation tool for automatic skull definition and a convolution dose calculation algorithm for tissue inhomogeneity correction. The purpose of this work was to evaluate the impact of these new approaches on routine clinical Gamma Knife treatment planning. Sixty-five patients who underwent CT image-guided Gamma Knife radiosurgeries at the University of Pittsburgh Medical Center in recent years were retrospectively investigated. The diagnoses for these cases include trigeminal neuralgia, meningioma, acoustic neuroma, AVM, glioma, and benign and metastatic brain tumors. Dose calculations were performed for each patient with the same dose prescriptions and the same shot arrangements using three different approaches: 1) TMR 10 dose calculation with imaging skull definition; 2) convolution dose calculation with imaging skull definition; 3) TMR 10 dose calculation with conventional measurement-based skull definition. For each treatment matrix, the total treatment time, the target coverage index, the selectivity index, the gradient index, and a set of dose statistics parameters were compared between the three calculations. The dose statistics parameters investigated include the prescription isodose volume, the 12 Gy isodose volume, the minimum, maximum and mean doses on the treatment targets, and the critical structures under consideration. The difference between the convolution and the TMR 10 dose calculations for the 104 treatment matrices were found to vary with the patient anatomy, location of the treatment shots, and the tissue inhomogeneities around the treatment target. An average difference of 8.4% was observed for the total treatment times between the convolution and the TMR algorithms. The maximum differences in the treatment times, the prescription isodose volumes, the 12 Gy isodose volumes, the target coverage indices, the selectivity indices, and the gradient indices from the convolution

  4. Hybrid detection of lung nodules on CT scan images

    SciTech Connect

    Lu, Lin; Tan, Yongqiang; Schwartz, Lawrence H.; Zhao, Binsheng

    2015-09-15

    Purpose: The diversity of lung nodules poses difficulty for the current computer-aided diagnostic (CAD) schemes for lung nodule detection on computed tomography (CT) scan images, especially in large-scale CT screening studies. We proposed a novel CAD scheme based on a hybrid method to address the challenges of detection in diverse lung nodules. Methods: The hybrid method proposed in this paper integrates several existing and widely used algorithms in the field of nodule detection, including morphological operation, dot-enhancement based on Hessian matrix, fuzzy connectedness segmentation, local density maximum algorithm, geodesic distance map, and regression tree classification. All of the adopted algorithms were organized into tree structures with multi-nodes. Each node in the tree structure aimed to deal with one type of lung nodule. Results: The method has been evaluated on 294 CT scans from the Lung Image Database Consortium (LIDC) dataset. The CT scans were randomly divided into two independent subsets: a training set (196 scans) and a test set (98 scans). In total, the 294 CT scans contained 631 lung nodules, which were annotated by at least two radiologists participating in the LIDC project. The sensitivity and false positive per scan for the training set were 87% and 2.61%. The sensitivity and false positive per scan for the testing set were 85.2% and 3.13%. Conclusions: The proposed hybrid method yielded high performance on the evaluation dataset and exhibits advantages over existing CAD schemes. We believe that the present method would be useful for a wide variety of CT imaging protocols used in both routine diagnosis and screening studies.

  5. From analogue to apps--developing an app to prepare children for medical imaging procedures.

    PubMed

    Williams, Gigi; Greene, Siobhan

    2015-01-01

    The Royal Children's Hospital (RCH) in Melbourne has launched a world-first app for children that will help reduce anxiety and the need for anesthesia during medical imaging procedures. The free, game-based app, "Okee in Medical Imaging", helps children aged from four to eight years to prepare for all medical imaging procedures--X-ray, CT, MRI, ultrasound, nuclear medicine, and fluoroscopy. The app is designed to reduce anticipatory fear of imaging procedures, while helping to ensure that children attend imaging appointments equipped with the skills required for efficient and effective scans to be performed. This paper describes how the app was developed.

  6. Body CT (CAT Scan)

    MedlinePlus

    ... lives. CT has been shown to be a cost-effective imaging tool for a wide range of ... accredited facilities database . This website does not provide cost information. The costs for specific medical imaging tests, ...

  7. New insights on COPD imaging via CT and MRI

    PubMed Central

    Sverzellati, N; Molinari, F; Pirronti, T; Bonomo, L; Spagnolo, P; Zompatori, M

    2007-01-01

    Multidetector-row computed tomography (MDCT) can be used to quantify morphological features and investigate structure/function relationship in COPD. This approach allows a phenotypical definition of COPD patients, and might improve our understanding of disease pathogenesis and suggest new therapeutical options. In recent years, magnetic resonance imaging (MRI) has also become potentially suitable for the assessment of ventilation, perfusion and respiratory mechanics. This review focuses on the established clinical applications of CT, and novel CT and MRI techniques, which may prove valuable in evaluating the structural and functional damage in COPD. PMID:18229568

  8. Medical imaging V: Image capture, formatting, and display

    SciTech Connect

    Kim, Y.

    1991-01-01

    This book is covered under the following topics: Digital image display I-V; Quality assurance I-V; Clinical image presentation I-V; Imaging systems; Image compression; Workstations; and Medical diagnostic imaging support system for military medicine and other federal agencies.

  9. Automatic Annotation of Radiological Observations in Liver CT Images

    PubMed Central

    Gimenez, Francisco; Xu, Jiajing; Liu, Yi; Liu, Tiffany; Beaulieu, Christopher; Rubin, Daniel; Napel, Sandy

    2012-01-01

    We aim to predict radiological observations using computationally-derived imaging features extracted from computed tomography (CT) images. We created a dataset of 79 CT images containing liver lesions identified and annotated by a radiologist using a controlled vocabulary of 76 semantic terms. Computationally-derived features were extracted describing intensity, texture, shape, and edge sharpness. Traditional logistic regression was compared to L1-regularized logistic regression (LASSO) in order to predict the radiological observations using computational features. The approach was evaluated by leave one out cross-validation. Informative radiological observations such as lesion enhancement, hypervascular attenuation, and homogeneous retention were predicted well by computational features. By exploiting relationships between computational and semantic features, this approach could lead to more accurate and efficient radiology reporting. PMID:23304295

  10. A study on the effect of CT imaging acquisition parameters on lung nodule image interpretation

    NASA Astrophysics Data System (ADS)

    Yu, Shirley J.; Wantroba, Joseph S.; Raicu, Daniela S.; Furst, Jacob D.; Channin, David S.; Armato, Samuel G., III

    2009-02-01

    Most Computer-Aided Diagnosis (CAD) research studies are performed using a single type of Computer Tomography (CT) scanner and therefore, do not take into account the effect of differences in the imaging acquisition scanner parameters. In this paper, we present a study on the effect of the CT parameters on the low-level image features automatically extracted from CT images for lung nodule interpretation. The study is an extension of our previous study where we showed that image features can be used to predict semantic characteristics of lung nodules such as margin, lobulation, spiculation, and texture. Using the Lung Image Data Consortium (LIDC) dataset, we propose to integrate the imaging acquisition parameters with the low-level image features to generate classification models for the nodules' semantic characteristics. Our preliminary results identify seven CT parameters (convolution kernel, reconstruction diameter, exposure, nodule location along the z-axis, distance source to patient, slice thickness, and kVp) as influential in producing classification rules for the LIDC semantic characteristics. Further post-processing analysis, which included running box plots and binning of values, identified four CT parameters: distance source to patient, kVp, nodule location, and rescale intercept. The identification of these parameters will create the premises to normalize the image features across different scanners and, in the long run, generate automatic rules for lung nodules interpretation independently of the CT scanner types.

  11. Fast and automatic ultrasound simulation from CT images.

    PubMed

    Cong, Weijian; Yang, Jian; Liu, Yue; Wang, Yongtian

    2013-01-01

    Ultrasound is currently widely used in clinical diagnosis because of its fast and safe imaging principles. As the anatomical structures present in an ultrasound image are not as clear as CT or MRI. Physicians usually need advance clinical knowledge and experience to distinguish diseased tissues. Fast simulation of ultrasound provides a cost-effective way for the training and correlation of ultrasound and the anatomic structures. In this paper, a novel method is proposed for fast simulation of ultrasound from a CT image. A multiscale method is developed to enhance tubular structures so as to simulate the blood flow. The acoustic response of common tissues is generated by weighted integration of adjacent regions on the ultrasound propagation path in the CT image, from which parameters, including attenuation, reflection, scattering, and noise, are estimated simultaneously. The thin-plate spline interpolation method is employed to transform the simulation image between polar and rectangular coordinate systems. The Kaiser window function is utilized to produce integration and radial blurring effects of multiple transducer elements. Experimental results show that the developed method is very fast and effective, allowing realistic ultrasound to be fast generated. Given that the developed method is fully automatic, it can be utilized for ultrasound guided navigation in clinical practice and for training purpose.

  12. Automatic labeling and segmentation of vertebrae in CT images

    NASA Astrophysics Data System (ADS)

    Rasoulian, Abtin; Rohling, Robert N.; Abolmaesumi, Purang

    2014-03-01

    Labeling and segmentation of the spinal column from CT images is a pre-processing step for a range of image- guided interventions. State-of-the art techniques have focused either on image feature extraction or template matching for labeling of the vertebrae followed by segmentation of each vertebra. Recently, statistical multi- object models have been introduced to extract common statistical characteristics among several anatomies. In particular, we have created models for segmentation of the lumbar spine which are robust, accurate, and computationally tractable. In this paper, we reconstruct a statistical multi-vertebrae pose+shape model and utilize it in a novel framework for labeling and segmentation of the vertebra in a CT image. We validate our technique in terms of accuracy of the labeling and segmentation of CT images acquired from 56 subjects. The method correctly labels all vertebrae in 70% of patients and is only one level off for the remaining 30%. The mean distance error achieved for the segmentation is 2.1 +/- 0.7 mm.

  13. 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

  14. 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

  15. Medical staff extremity dosimetry in CT fluoroscopy: an anthropomorphic hand voxel phantom study

    NASA Astrophysics Data System (ADS)

    Figueira, C.; Becker, F.; Blunck, C.; DiMaria, S.; Baptista, M.; Esteves, B.; Paulo, G.; Santos, J.; Teles, P.; Vaz, P.

    2013-08-01

    This work aims to contribute to the study of the radiation dose distribution delivered to the hands of medical staff members during a general computed tomographic (CT) fluoroscopic guided procedure. In this study, both Monte Carlo simulations and measurements were performed. For free-in-air and computed tomography dose index (CTDI) body phantom measurements, a standard pencil ionization chamber (IC) 100 mm long was used. The CT scanner model was implemented using MCNPX (Monte Carlo N-Particle eXtended) and was successfully validated by comparing the simulated results with measurements. Subsequently, CT images of a hand, together with an anthropomorphic phantom, were voxelized and used with the MCNPX code for dose calculations. The hand dose distribution study was performed both by using thermo-luminescent detector measurements and Monte Carlo simulations. The validated simulation tool provides a new perspective for detailed investigations of CT-irradiation scenarios. Simulations show that there is a strong dose gradient, namely the even zones of the hand that are in precise vicinity to the x-ray beam only receive about 4% of the maximum dose delivered to adjacent areas which are directly exposed to the primary x-ray beam. Finally, the scatter contribution of the patient was also studied through MC simulations. The results show that for directly exposed parts of the hand surface, the dose is reduced by the body of the patient (due to the shielding), whereas the dose is increased by scattered radiation from the patient for parts of the skin that receive scattered radiation only.

  16. Theoretical analysis of x-ray CT phase-contrast imaging

    NASA Astrophysics Data System (ADS)

    Feng, Sheng; Liu, Song; Zhang, Xuelong

    2008-12-01

    Recently phase contrast imaging has attracted much attention. An obvious advantage of using X-rays for imaging the internal structure of relatively thick samples lies in its high degree of penetration of solid objects. However, often leads to poor image contrast for soft tissue. Phase contrast imaging can be very useful in such situation, as the phase of the transmitted beam may often be more sensitive indicator of density of sample than convention contrast. On the other hand, Computed Tomography is the best technology in the aspect of X-rays detection. Using the technology, the detected object can be imaged to three-dimensional image, so as to observe the inner structure of object, and be convenient to the disease examination. If the phase contrast imaging can be used to the technology of Computed Tomography, the high resolution image can be gained. The technology will become the development orientation of medical image. The aim of this article was to apply the theory of X-rays phase contrast imaging to the traditional X-CT technique. For this purpose, the formula deduced from the imaging theory with parallel monochromatic X-rays illuminating the object based on the Fresnel-Kircohhof theory had been completed and a formula similar to that of the traditional X-CT reconstruction had been gained, which was Radon transform formula. At last, X-rays reconstruction simulation had been carried out according to the formula, and proved that the method could be used in clinical medical imaging. The method discussed in this paper had a very bright prospect for application.

  17. Preliminary Study on Appearance-Based Detection of Anatomical Point Landmarks in Body Trunk CT Images

    NASA Astrophysics Data System (ADS)

    Nemoto, Mitsutaka; Nomura, Yukihiro; Hanaoka, Shohei; Masutani, Yoshitaka; Yoshikawa, Takeharu; Hayashi, Naoto; Yoshioka, Naoki; Ohtomo, Kuni

    Anatomical point landmarks as most primitive anatomical knowledge are useful for medical image understanding. In this study, we propose a detection method for anatomical point landmark based on appearance models, which include gray-level statistical variations at point landmarks and their surrounding area. The models are built based on results of Principal Component Analysis (PCA) of sample data sets. In addition, we employed generative learning method by transforming ROI of sample data. In this study, we evaluated our method with 24 data sets of body trunk CT images and obtained 95.8 ± 7.3 % of the average sensitivity in 28 landmarks.

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

    PubMed

    Taguchi, Katsuyuki; Iwanczyk, Jan S

    2013-10-01

    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.

  19. 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

  20. A hybrid method for pancreas extraction from CT image based on level set methods.

    PubMed

    Jiang, Huiyan; 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.

  1. CT Imaging of Coronary Stents: Past, Present, and Future

    PubMed Central

    Mahnken, Andreas H.

    2012-01-01

    Coronary stenting became a mainstay in coronary revascularization therapy. Despite tremendous advances in therapy, in-stent restenosis (ISR) remains a key problem after coronary stenting. Coronary CT angiography evolved as a valuable tool in the diagnostic workup of patients after coronary revascularization therapy. It has a negative predictive value in the range of 98% for ruling out significant ISR. As CT imaging of coronary stents depends on patient and stent characteristics, patient selection is crucial for success. Ideal candidates have stents with a diameter of 3 mm and more. Nevertheless, even with most recent CT scanners, about 8% of stents are not accessible mostly due to blooming or motion artifacts. While the diagnosis of ISR is currently based on the visual assessment of the stent lumen, functional information on the hemodynamic significance of in-stent stenosis became available with the most recent generation of dual source CT scanners. This paper provides a comprehensive overview on previous developments, current techniques, and clinical evidence for cardiac CT in patients with coronary artery stents. PMID:22997590

  2. The algorithm stitching for medical imaging

    NASA Astrophysics Data System (ADS)

    Semenishchev, E.; Marchuk, V.; Voronin, V.; Pismenskova, M.; Tolstova, I.; Svirin, I.

    2016-05-01

    In this paper we propose a stitching algorithm of medical images into one. The algorithm is designed to stitching the medical x-ray imaging, biological particles in microscopic images, medical microscopic images and other. Such image can improve the diagnosis accuracy and quality for minimally invasive studies (e.g., laparoscopy, ophthalmology and other). The proposed algorithm is based on the following steps: the searching and selection areas with overlap boundaries; the keypoint and feature detection; the preliminary stitching images and transformation to reduce the visible distortion; the search a single unified borders in overlap area; brightness, contrast and white balance converting; the superimposition into a one image. Experimental results demonstrate the effectiveness of the proposed method in the task of image stitching.

  3. Content standards for medical image metadata

    NASA Astrophysics Data System (ADS)

    d'Ornellas, Marcos C.; da Rocha, Rafael P.

    2003-12-01

    Medical images are at the heart of the healthcare diagnostic procedures. They have provided not only a noninvasive mean to view anatomical cross-sections of internal organs but also a mean for physicians to evaluate the patient"s diagnosis and monitor the effects of the treatment. For a Medical Center, the emphasis may shift from the generation of image to post processing and data management since the medical staff may generate even more processed images and other data from the original image after various analyses and post processing. A medical image data repository for health care information system is becoming a critical need. This data repository would contain comprehensive patient records, including information such as clinical data and related diagnostic images, and post-processed images. Due to the large volume and complexity of the data as well as the diversified user access requirements, the implementation of the medical image archive system will be a complex and challenging task. This paper discusses content standards for medical image metadata. In addition it also focuses on the image metadata content evaluation and metadata quality management.

  4. Gallium-68 EDTA PET/CT for Renal Imaging.

    PubMed

    Hofman, Michael S; Hicks, Rodney J

    2016-09-01

    Nuclear medicine renal imaging provides important functional data to assist in the diagnosis and management of patients with a variety of renal disorders. Physiologically stable metal chelates like ethylenediaminetetraacetic acid (EDTA) and diethylenetriamine penta-acetate (DTPA) are excreted by glomerular filtration and have been radiolabelled with a variety of isotopes for imaging glomerular filtration and quantitative assessment of glomerular filtration rate. Gallium-68 ((68)Ga) EDTA PET usage predates Technetium-99m ((99m)Tc) renal imaging, but virtually disappeared with the widespread adoption of gamma camera technology that was not optimal for imaging positron decay. There is now a reemergence of interest in (68)Ga owing to the greater availability of PET technology and use of (68)Ga to label other radiotracers. (68)Ga EDTA can be used a substitute for (99m)Tc DTPA for wide variety of clinical indications. A key advantage of PET for renal imaging over conventional scintigraphy is 3-dimensional dynamic imaging, which is particularly helpful in patients with complex anatomy in whom planar imaging may be nondiagnostic or difficult to interpret owing to overlying structures containing radioactive urine that cannot be differentiated. Other advantages include accurate and absolute (rather than relative) camera-based quantification, superior spatial and temporal resolution and integrated multislice CT providing anatomical correlation. Furthermore, the (68)Ga generator enables on-demand production at low cost, with no additional patient radiation exposure compared with conventional scintigraphy. Over the past decade, we have employed (68)Ga EDTA PET/CT primarily to answer difficult clinical questions in patients in whom other modalities have failed, particularly when it was envisaged that dynamic 3D imaging would be of assistance. We have also used it as a substitute for (99m)Tc DTPA if unavailable owing to supply issues, and have additionally examined the role of

  5. Imaging requirements for medical applications of additive manufacturing.

    PubMed

    Huotilainen, Eero; Paloheimo, Markku; Salmi, Mika; Paloheimo, Kaija-Stiina; Björkstrand, Roy; Tuomi, Jukka; Markkola, Antti; Mäkitie, Antti

    2014-02-01

    Additive manufacturing (AM), formerly known as rapid prototyping, is steadily shifting its focus from industrial prototyping to medical applications as AM processes, bioadaptive materials, and medical imaging technologies develop, and the benefits of the techniques gain wider knowledge among clinicians. This article gives an overview of the main requirements for medical imaging affected by needs of AM, as well as provides a brief literature review from existing clinical cases concentrating especially on the kind of radiology they required. As an example application, a pair of CT images of the facial skull base was turned into 3D models in order to illustrate the significance of suitable imaging parameters. Additionally, the model was printed into a preoperative medical model with a popular AM device. Successful clinical cases of AM are recognized to rely heavily on efficient collaboration between various disciplines - notably operating surgeons, radiologists, and engineers. The single main requirement separating tangible model creation from traditional imaging objectives such as diagnostics and preoperative planning is the increased need for anatomical accuracy in all three spatial dimensions, but depending on the application, other specific requirements may be present as well. This article essentially intends to narrow the potential communication gap between radiologists and engineers who work with projects involving AM by showcasing the overlap between the two disciplines.

  6. A survey of medical diagnostic imaging technologies

    SciTech Connect

    Heese, V.; Gmuer, N.; Thomlinson, W.

    1991-10-01

    The fields of medical imaging and medical imaging instrumentation are increasingly important. The state-of-the-art continues to advance at a very rapid pace. In fact, various medical imaging modalities are under development at the National Synchrotron Light Source (such as MECT and Transvenous Angiography.) It is important to understand how these techniques compare with today`s more conventional imaging modalities. The purpose of this report is to provide some basic information about the various medical imaging technologies currently in use and their potential developments as a basis for this comparison. This report is by no means an in-depth study of the physics and instrumentation of the various imaging modalities; instead, it is an attempt to provide an explanation of the physical bases of these techniques and their principal clinical and research capabilities.

  7. A survey of medical diagnostic imaging technologies

    SciTech Connect

    Heese, V.; Gmuer, N.; Thomlinson, W.

    1991-10-01

    The fields of medical imaging and medical imaging instrumentation are increasingly important. The state-of-the-art continues to advance at a very rapid pace. In fact, various medical imaging modalities are under development at the National Synchrotron Light Source (such as MECT and Transvenous Angiography.) It is important to understand how these techniques compare with today's more conventional imaging modalities. The purpose of this report is to provide some basic information about the various medical imaging technologies currently in use and their potential developments as a basis for this comparison. This report is by no means an in-depth study of the physics and instrumentation of the various imaging modalities; instead, it is an attempt to provide an explanation of the physical bases of these techniques and their principal clinical and research capabilities.

  8. Cochlear anatomy using micro computed tomography (μCT) imaging

    NASA Astrophysics Data System (ADS)

    Kim, Namkeun; Yoon, Yongjin; Steele, Charles; Puria, Sunil

    2008-02-01

    A novel micro computed tomography (μCT) image processing method was implemented to measure anatomical features of the gerbil and chinchilla cochleas, taking into account the bent modailosis axis. Measurements were made of the scala vestibule (SV) area, the scala tympani (SV) area, and the basilar membrane (BM) width using prepared cadaveric temporal bones. 3-D cochlear structures were obtained from the scanned images using a process described in this study. It was necessary to consider the sharp curvature of mododailosis axis near the basal region. The SV and ST areas were calculated from the μCT reconstructions and compared with existing data obtained by Magnetic Resonance Microscopy (MRM), showing both qualitative and quantitative agreement. In addition to this, the width of the BM, which is the distance between the primary and secondary osseous spiral laminae, is calculated for the two animals and compared with previous data from the MRM method. For the gerbil cochlea, which does not have much cartilage in the osseous spiral lamina, the μCT-based BM width measurements show good agreement with previous data. The chinchilla BM, which contains more cartilage in the osseous spiral lamina than the gerbil, shows a large difference in the BM widths between the μCT and MRM methods. The SV area, ST area, and BM width measurements from this study can be used in building an anatomically based mathematical cochlear model.

  9. The influence of respiratory motion on CT image volume definition

    SciTech Connect

    Rodríguez-Romero, Ruth Castro-Tejero, Pablo

    2014-04-15

    Purpose: Radiotherapy treatments are based on geometric and density information acquired from patient CT scans. It is well established that breathing motion during scan acquisition induces motion artifacts in CT images, which can alter the size, shape, and density of a patient's anatomy. The aim of this work is to examine and evaluate the impact of breathing motion on multislice CT imaging with respiratory synchronization (4DCT) and without it (3DCT). Methods: A specific phantom with a movable insert was used. Static and dynamic phantom acquisitions were obtained with a multislice CT. Four sinusoidal breath patterns were simulated to move known geometric structures longitudinally. Respiratory synchronized acquisitions (4DCT) were performed to generate images during inhale, intermediate, and exhale phases using prospective and retrospective techniques. Static phantom data were acquired in helical and sequential mode to define a baseline for each type of respiratory 4DCT technique. Taking into account the fact that respiratory 4DCT is not always available, 3DCT helical image studies were also acquired for several CT rotation periods. To study breath and acquisition coupling when respiratory 4DCT was not performed, the beginning of the CT image acquisition was matched with inhale, intermediate, or exhale respiratory phases, for each breath pattern. Other coupling scenarios were evaluated by simulating different phantom and CT acquisition parameters. Motion induced variations in shape and density were quantified by automatic threshold volume generation and Dice similarity coefficient calculation. The structure mass center positions were also determined to make a comparison with their theoretical expected position. Results: 4DCT acquisitions provided volume and position accuracies within ±3% and ±2 mm for structure dimensions >2 cm, breath amplitude ≤15 mm, and breath period ≥3 s. The smallest object (1 cm diameter) exceeded 5% volume variation for the breath

  10. Image analysis in medical imaging: recent advances in selected examples.

    PubMed

    Dougherty, G

    2010-01-01

    Medical imaging has developed into one of the most important fields within scientific imaging due to the rapid and continuing progress in computerised medical image visualisation and advances in analysis methods and computer-aided diagnosis. Several research applications are selected to illustrate the advances in image analysis algorithms and visualisation. Recent results, including previously unpublished data, are presented to illustrate the challenges and ongoing developments.

  11. 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.

  12. Cone-beam CT with a flat-panel detector: From image science to image-guided surgery

    NASA Astrophysics Data System (ADS)

    Siewerdsen, Jeffrey H.

    2011-08-01

    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 the 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

  13. Automatic lung nodule matching on sequential CT images.

    PubMed

    Hong, Helen; Lee, Jeongjin; Yim, Yeny

    2008-05-01

    We propose an automatic segmentation and registration method that provides more efficient and robust matching of lung nodules in sequential chest computed tomography (CT) images. Our method consists of four steps. First, the lungs are extracted from chest CT images by the automatic segmentation method. Second, gross translational mismatch is corrected by optimal cube registration. This initial alignment does not require extracting any anatomical landmarks. Third, the initial alignment is step-by-step refined by hierarchical surface registration. To evaluate the distance measures between lung boundary points, a three-dimensional distance map is generated by narrow-band distance propagation, which drives fast and robust convergence to the optimal value. Finally, correspondences of manually detected nodules are established from the pairs with the smallest Euclidean distances. Experimental results show that our segmentation method accurately extracts lung boundaries and the registration method effectively finds the nodule correspondences.

  14. Medical imaging in new drug clinical development.

    PubMed

    Wang, Yi-Xiang; Deng, Min

    2010-12-01

    Medical imaging can help answer key questions that arise during the drug development process. The role of medical imaging in new drug clinical trials includes identification of likely responders; detection and diagnosis of lesions and evaluation of their severity; and therapy monitoring and follow-up. Nuclear imaging techniques such as PET can be used to monitor drug pharmacokinetics and distribution and study specific molecular endpoints. In assessing drug efficacy, imaging biomarkers and imaging surrogate endpoints can be more objective and faster to measure than clinical outcomes, and allow small group sizes, quick results and good statistical power. Imaging also has important role in drug safety monitoring, particularly when there is no other suitable biomarkers available. Despite the long history of radiological sciences, its application to the drug development process is relatively recent. This review highlights the processes, opportunities, and challenges of medical imaging in new drug development.

  15. Denoising Medical Images using Calculus of Variations.

    PubMed

    Kohan, Mahdi Nakhaie; Behnam, Hamid

    2011-07-01

    We propose a method for medical image denoising using calculus of variations and local variance estimation by shaped windows. This method reduces any additive noise and preserves small patterns and edges of images. A pyramid structure-texture decomposition of images is used to separate noise and texture components based on local variance measures. The experimental results show that the proposed method has visual improvement as well as a better SNR, RMSE and PSNR than common medical image denoising methods. Experimental results in denoising a sample Magnetic Resonance image show that SNR, PSNR and RMSE have been improved by 19, 9 and 21 percents respectively.

  16. Content-Based Medical Image Retrieval

    NASA Astrophysics Data System (ADS)

    Müller, Henning; Deserno, Thomas M.

    This chapter details the necessity for alternative access concepts to the currently mainly text-based methods in medical information retrieval. This need is partly due to the large amount of visual data produced, the increasing variety of medical imaging data and changing user patterns. The stored visual data contain large amounts of unused information that, if well exploited, can help diagnosis, teaching and research. The chapter briefly reviews the history of image retrieval and its general methods before technologies that have been developed in the medical domain are focussed. We also discuss evaluation of medical content-based image retrieval (CBIR) systems and conclude with pointing out their strengths, gaps, and further developments. As examples, the MedGIFT project and the Image Retrieval in Medical Applications (IRMA) framework are presented.

  17. Simulation of mammograms and tomosynthesis imaging with cone beam breast CT images

    NASA Astrophysics Data System (ADS)

    Han, Tao; Shaw, Chris C.; Chen, Lingyun; Lai, Chao-jen; Liu, Xinming; Wang, Tianpeng

    2008-03-01

    The use of mammography techniques for the screening and diagnosis of breast cancers has been limited by the overlapping of cancer symptoms with normal tissue structures. To overcome this problem, two methods have been developed and actively investigated recently: digital tomosynthesis mammography and cone beam breast CT. Comparison study with these three techniques will be helpful to understand their difference and further might be supervise the direction of breast imaging. This paper describes and discusses about a technique using a general-purpose PC cluster to develop a parallel computer simulation model to simulate mammograms and tomosynthesis imaging with cone beam CT images of a mastectomy breast specimen. The breast model used in simulating mammography and tomosynthesis was developed by re-scaling the CT numbers of cone beam CT images from 80kVp to 20 kev. The compression of breast was simulated by deformation of the breast model. Re-projection software with parallel computation was developed and used to compute projection images of this simulated compressed breast for a stationary detector and a linearly shifted x-ray source. The resulting images were then used to reconstruct tomosynthesis mammograms using shift-and-add algorithms. It was found that MCs in cone beam CT images were not visible in regular mammograms but faintly visible in tomosynthesis images. The scatter signal and noise property needs to be simulated and incorporated in the future.

  18. Nonrigid Image Registration for Head and Neck Cancer Radiotherapy Treatment Planning With PET/CT

    SciTech Connect

    Ireland, Rob H. . E-mail: r.ireland@sheffield.ac.uk; Dyker, Karen E.; Barber, David C.; Wood, Steven M.; Hanney, Michael B.; Tindale, Wendy B.; Woodhouse, Neil; Hoggard, Nigel; Conway, John; Robinson, Martin H.

    2007-07-01

    Purpose: Head and neck radiotherapy planning with positron emission tomography/computed tomography (PET/CT) requires the images to be reliably registered with treatment planning CT. Acquiring PET/CT in treatment position is problematic, and in practice for some patients it may be beneficial to use diagnostic PET/CT for radiotherapy planning. Therefore, the aim of this study was first to quantify the image registration accuracy of PET/CT to radiotherapy CT and, second, to assess whether PET/CT acquired in diagnostic position can be registered to planning CT. Methods and Materials: Positron emission tomography/CT acquired in diagnostic and treatment position for five patients with head and neck cancer was registered to radiotherapy planning CT using both rigid and nonrigid image registration. The root mean squared error for each method was calculated from a set of anatomic landmarks marked by four independent observers. Results: Nonrigid and rigid registration errors for treatment position PET/CT to planning CT were 2.77 {+-} 0.80 mm and 4.96 {+-} 2.38 mm, respectively, p = 0.001. Applying the nonrigid registration to diagnostic position PET/CT produced a more accurate match to the planning CT than rigid registration of treatment position PET/CT (3.20 {+-} 1.22 mm and 4.96 {+-} 2.38 mm, respectively, p = 0.012). Conclusions: Nonrigid registration provides a more accurate registration of head and neck PET/CT to treatment planning CT than rigid registration. In addition, nonrigid registration of PET/CT acquired with patients in a standardized, diagnostic position can provide images registered to planning CT with greater accuracy than a rigid registration of PET/CT images acquired in treatment position. This may allow greater flexibility in the timing of PET/CT for head and neck cancer patients due to undergo radiotherapy.

  19. A Novel Assessment of Various Bio-Imaging Methods for Lung Tumor Detection and Treatment by using 4-D and 2-D CT Images

    PubMed Central

    Judice A., Antony; Geetha, Dr. K. Parimala

    2013-01-01

    Lung Cancer is known as one of the most difficult cancer to cure, and the number of deaths that it causes generally increasing. A detection of the Lung Cancer in its early stage can be helpful for Medical treatment to limit the danger, but it is a challenging problem due to Cancer cell structure. Interpretation of Medical image is often difficult and time consuming, even for the experienced Physicians. The aid of image analysis Based on machine learning can make this process easier. This paper describes fully Automatic Decision Support system for Lung Cancer diagnostic from CT Lung images. Most traditional medical diagnosis systems are founded on huge quantity of training data and takes long processing time. However, on the occasion that very little volume of data is available, the traditional diagnosis systems derive defects such as larger error, Time complexity. Focused on the solution to this problem, a Medical Diagnosis System based on Hidden Markov Model (HMM) is presented. In this paper we describe a pre-processing stage involving some Noise removal techniques help to solve this problem, we preprocess an images (by Mean Error Square Filtering and Histogram analysis)obtained after scanning the Lung CT images. Secondly separate the lung areas from an image by a segmentation process (by Thresholding and region growing techniques). Finally we developed HMM for the classification of Cancer Nodule. Results are checked for 2D and 4D CT images. This automation process reduces the time complexity and increases the diagnosis confidence. PMID:23847454

  20. Medical image analysis with artificial neural networks.

    PubMed

    Jiang, J; Trundle, P; Ren, J

    2010-12-01

    Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging.

  1. Lung fissure detection in CT images using global minimal paths

    NASA Astrophysics Data System (ADS)

    Appia, Vikram; Patil, Uday; Das, Bipul

    2010-03-01

    Pulmonary fissures separate human lungs into five distinct regions called lobes. Detection of fissure is essential for localization of the lobar distribution of lung diseases, surgical planning and follow-up. Treatment planning also requires calculation of the lobe volume. This volume estimation mandates accurate segmentation of the fissures. Presence of other structures (like vessels) near the fissure, along with its high variational probability in terms of position, shape etc. makes the lobe segmentation a challenging task. Also, false incomplete fissures and occurrence of diseases add to the complications of fissure detection. In this paper, we propose a semi-automated fissure segmentation algorithm using a minimal path approach on CT images. An energy function is defined such that the path integral over the fissure is the global minimum. Based on a few user defined points on a single slice of the CT image, the proposed algorithm minimizes a 2D energy function on the sagital slice computed using (a) intensity (b) distance of the vasculature, (c) curvature in 2D, (d) continuity in 3D. The fissure is the infimum energy path between a representative point on the fissure and nearest lung boundary point in this energy domain. The algorithm has been tested on 10 CT volume datasets acquired from GE scanners at multiple clinical sites. The datasets span through different pathological conditions and varying imaging artifacts.

  2. Evaluation of image quality and dose on a flat-panel CT-scanner

    NASA Astrophysics Data System (ADS)

    Grasruck, M.; Suess, Ch.; Stierstorfer, K.; Popescu, S.; Flohr, T.

    2005-04-01

    We developed and evaluated a prototype flat-panel detector based Volume CT (VCT) scanner. We focused on improving the image quality using different detector settings and reducing x-ray scatter intensities. For the presented results we used a Varian 4030CB flat-panel detector mounted in a multislice CT-gantry (Siemens Medical Systems). The scatter intensities may severely impair image quality in flat-panel detector CT systems. To reduce the impact of scatter we tested bowtie shaped filters, anti-scatter grids and post-processing correction algorithms. We evaluated the improvement of image quality by each method and also by a combination of the several methods. To achieve an extended dynamic range in the projection data, we implemented a novel dynamic gain-switching mode. The read out charge amplifier feedback capacitance is changing dynamically in this mode, depending on the signal level. For this scan mode dedicated corrections in the offset and gain calibration are required. We compared image quality in terms of low contrast for both, the dynamic mode and the standard fixed gain mode. VCT scanners require different types of dose parameters. We measured the dose in a 16 cm CTDI phantom and free air in the scanners iso-center and defined a new metric for a VCT dose index (VCTDI). The dose for a high quality VCT scan of this prototype scanner varied between 15 and 40 mGy.

  3. [Image fusion in medical radiology].

    PubMed

    Burger, C

    1996-07-20

    Image fusion supports the correlation between images of two or more studies of the same organ. First, the effect of differing geometries during image acquisitions, such as a head tilt, is compensated for. As a consequence, congruent images can easily be obtained. Instead of merely putting them side by side in a static manner and burdening the radiologist with the whole correlation task, image fusion supports him with interactive visualization techniques. This is especially worthwhile for small lesions as they can be more precisely located. Image fusion is feasible today. Easy and robust techniques are readily available, and furthermore DICOM, a rapidly evolving data exchange standard, diminishes the once severe compatibility problems for image data originating from systems of different manufacturers. However, the current solutions for image fusion are not yet established enough for a high throughput of fusion studies. Thus, for the time being image fusion is most appropriately confined to clinical research studies.

  4. [Accuracy analysis of computer tomography imaging for medical modeling purposes on the example of Siemens Sensation 10 scanner].

    PubMed

    Miechowicz, Sławomir; Urbanik, Andrzej; Chrzan, Robert; Grochowska, Anna

    2010-01-01

    Medical model is a material model of human body part, used for better visualization or surgery planning. It may be produced by Rapid Prototyping method, based on data obtained during medical imaging (computer tomography--CT, magnetic resonance--MR). Important problem is to provide proper spatial accuracy of the model, influenced by imaging accuracy of CT and MR scanners. The aim of the study is the accuracy analysis of CT imaging for medical modeling purposes on the example of Siemens Sensation 10 scanner. Using stereolithography technique a physical pattern--phantom in the form of grating was produced. The phantom was measured by a Coordinate Measuring Machine Leitz PMM 12106 to consider production process inaccuracy. Then the phantom was examined using CT scanner Siemens Sensation 10. Phantom measurement error distribution was determined, based on the data obtained. Maximal measurement error, considering both phantom production inaccuracy and CT imaging inaccuracy was +/- 0.87 mm, while considering only CT imaging inaccuracy was not exceeding 0.28 mm. CT acquisition process is by itself the source of measurement errors. So to provide high quality of medical models produced by Rapid Prototyping methods, it is necessary to perform accuracy measurements for every CT scanner used for obtaing data serving as the base for model production.

  5. Semiautomatic segmentation of liver metastases on volumetric CT images

    SciTech Connect

    Yan, Jiayong; Schwartz, Lawrence H.; Zhao, Binsheng

    2015-11-15

    Purpose: Accurate segmentation and quantification of liver metastases on CT images are critical to surgery/radiation treatment planning and therapy response assessment. To date, there are no reliable methods to perform such segmentation automatically. In this work, the authors present a method for semiautomatic delineation of liver metastases on contrast-enhanced volumetric CT images. Methods: The first step is to manually place a seed region-of-interest (ROI) in the lesion on an image. This ROI will (1) serve as an internal marker and (2) assist in automatically identifying an external marker. With these two markers, lesion contour on the image can be accurately delineated using traditional watershed transformation. Density information will then be extracted from the segmented 2D lesion and help determine the 3D connected object that is a candidate of the lesion volume. The authors have developed a robust strategy to automatically determine internal and external markers for marker-controlled watershed segmentation. By manually placing a seed region-of-interest in the lesion to be delineated on a reference image, the method can automatically determine dual threshold values to approximately separate the lesion from its surrounding structures and refine the thresholds from the segmented lesion for the accurate segmentation of the lesion volume. This method was applied to 69 liver metastases (1.1–10.3 cm in diameter) from a total of 15 patients. An independent radiologist manually delineated all lesions and the resultant lesion volumes served as the “gold standard” for validation of the method’s accuracy. Results: The algorithm received a median overlap, overestimation ratio, and underestimation ratio of 82.3%, 6.0%, and 11.5%, respectively, and a median average boundary distance of 1.2 mm. Conclusions: Preliminary results have shown that volumes of liver metastases on contrast-enhanced CT images can be accurately estimated by a semiautomatic segmentation

  6. CT and MR imaging of odontoid abnormalities: A pictorial review

    PubMed Central

    Jain, Nishchint; Verma, Ritu; Garga, Umesh C; Baruah, Barinder P; Jain, Sachin K; Bhaskar, Surya N

    2016-01-01

    Odontoid process is the central pillar of the craniovertebral junction. Imaging of this small structure continues to be a challenge for the radiologists due to complex bony and ligamentous anatomy. A wide range of developmental and acquired abnormalities of odontoid have been identified. Their accurate radiologic evaluation is important as different lesions have markedly different clinical course, patient management, and prognosis. This article seeks to provide knowledge for interpreting appearances of odontoid on computed tomography (CT) and magnetic resonance imaging (MRI) with respect to various disease processes, along with providing a quick review of the embryology and relevant anatomy. PMID:27081234

  7. Pancreas tumor model in rabbit imaged by perfusion CT scans

    NASA Astrophysics Data System (ADS)

    Gunn, Jason; Tichauer, Kenneth; Moodie, Karen; Kane, Susan; Hoopes, Jack; Stewart, Errol E.; Hadway, Jennifer; Lee, Ting-Yim; Pereira, Stephen P.; Pogue, Brian W.

    2013-03-01

    The goal of this work was to develop and validate a pancreas tumor animal model to investigate the relationship between photodynamic therapy (PDT) effectiveness and photosensitizer drug delivery. More specifically, this work lays the foundation for investigating the utility of dynamic contrast enhanced blood perfusion imaging to be used to inform subsequent PDT. A VX2 carcinoma rabbit cell line was grown in the tail of the pancreas of three New Zealand White rabbits and approximately 3-4 weeks after implantation the rabbits were imaged on a CT scanner using a contrast enhanced perfusion protocol, providing parametric maps of blood flow, blood volume, mean transit time, and vascular permeability surface area product.

  8. Image registration method for medical image sequences

    DOEpatents

    Gee, Timothy F.; Goddard, James S.

    2013-03-26

    Image registration of low contrast image sequences is provided. In one aspect, a desired region of an image is automatically segmented and only the desired region is registered. Active contours and adaptive thresholding of intensity or edge information may be used to segment the desired regions. A transform function is defined to register the segmented region, and sub-pixel information may be determined using one or more interpolation methods.

  9. Medical image libraries: ICoS project

    NASA Astrophysics Data System (ADS)

    Honniball, John; Thomas, Peter

    1999-08-01

    FOr use of digital techniques for the production, manipulation and storage of images has resulted in the creation of digital image libraries. These libraries often store many thousands of images. While provision of storage media for such large amounts of data has been straightforward, provision of effective searching and retrieval tools has not. Medicine relies heavily on images as a diagnostic tool. The most obvious example is the x-ray, but many other image forms are in everyday use. Advances in technology are affecting the ways medical images are generated, stored and retrieved. The paper describes the work of the Image COding and Segmentation to Support Variable Rate Transmission Channels and Variable Resolution Platforms (ICoS) research project currently under way in Bristol, UK. ICoS is a project of the Mobile of England and Hewlett-Packard Research Laboratories Europe. Funding is provided by the Engineering and PHysical Sciences Research Council. The aim of the ICoS project is to demonstrate the practical application of computer networking to medical image libraries. Work at the University of the West of England concentrates on user interface and indexing issues. Metadata is used to organize the images, coded using the WWW Consortium standard Resource Description Framework. We are investigating the application of such standards to medical images, one outcome being to implement a metadata-based image library. This paper describes the ICoS project in detail and discuses both metadata system and user interfaces in the context of medical applications.

  10. Contraindications and side effects of commonly used medications in coronary CT angiography.

    PubMed

    Khan, Mansoor; Cummings, Kristopher W; Gutierrez, Fernando R; Bhalla, Sanjeev; Woodard, Pamela K; Saeed, Ibrahim M

    2011-03-01

    For certain clinical applications, coronary CT angiography (CCTA) has become a useful tool for the noninvasive evaluation of coronary artery atherosclerosis. To optimize image quality in CCTA, medications are often given prior to scanning to slow the heart rate or distend the arteries. These medications have side effects and are contraindicated in certain patient populations. Metoprolol is the ß-blocker of choice in CCTA, and it has been shown to be effective in achieving the goal heart rate of less than 65 beats per minute for CCTA and in minimizing variability of heart rate. It is contraindicated in patients with hypotension or high degree AV block, and it must be used with caution in patients with asthma or obstructive pulmonary disease, patients with decompensated heart failure, and those with vasospastic or vasoocclusive disease. Diltiazem, the calcium channel blocker of choice in CCTA, is a reasonable alternative for heart control, particularly in patients with asthma or bronchospastic disease, and patients with orthotopic heart transplants that have been sympathetically denervated. Sublingual nitroglycerin is especially useful in order to dilate distal arteries to improve stenosis visibility. However, it is contraindicated in patients on erectile dysfunction medications and those with severe anemia. It must be used cautiously in patients with aortic stenosis or other preload-dependant cardiac pathologies.

  11. 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

  12. THz Medical Imaging: in vivo Hydration Sensing

    PubMed Central

    Taylor, Zachary D.; Singh, Rahul S.; Bennett, David B.; Tewari, Priyamvada; Kealey, Colin P.; Bajwa, Neha; Culjat, Martin O.; Stojadinovic, Alexander; Lee, Hua; Hubschman, Jean-Pierre; Brown, Elliott R.; Grundfest, Warren S.

    2015-01-01

    The application of THz to medical imaging is experiencing a surge in both interest and federal funding. A brief overview of the field is provided along with promising and emerging applications and ongoing research. THz imaging phenomenology is discussed and tradeoffs are identified. A THz medical imaging system, operating at ~525 GHz center frequency with ~125 GHz of response normalized bandwidth is introduced and details regarding principles of operation are provided. Two promising medical applications of THz imaging are presented: skin burns and cornea. For burns, images of second degree, partial thickness burns were obtained in rat models in vivo over an 8 hour period. These images clearly show the formation and progression of edema in and around the burn wound area. For cornea, experimental data measuring the hydration of ex vivo porcine cornea under drying is presented demonstrating utility in ophthalmologic applications. PMID:26085958

  13. Elastic registration of multiphase CT images of liver

    NASA Astrophysics Data System (ADS)

    Heldmann, Stefan; Zidowitz, Stephan

    2009-02-01

    In this work we present a novel approach for elastic image registration of multi-phase contrast enhanced CT images of liver. A problem in registration of multiphase CT is that the images contain similar but complementary structures. In our application each image shows a different part of the vessel system, e.g., portal/hepatic venous/arterial, or biliary vessels. Portal, arterial and biliary vessels run in parallel and abut on each other forming the so called portal triad, while hepatic veins run independent. Naive registration will tend to align complementary vessel. Our new approach is based on minimizing a cost function consisting of a distance measure and a regularizer. For the distance we use the recently proposed normalized gradient field measure that focuses on the alignment of edges. For the regularizer we use the linear elastic potential. The key feature of our approach is an additional penalty term using segmentations of the different vessel systems in the images to avoid overlaps of complementary structures. We successfully demonstrate our new method by real data examples.

  14. 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

  15. Classification of CT brain images based on deep learning networks.

    PubMed

    Gao, Xiaohong W; Hui, Rui; Tian, Zengmin

    2017-01-01

    While computerised tomography (CT) may have been the first imaging tool to study human brain, it has not yet been implemented into clinical decision making process for diagnosis of Alzheimer's disease (AD). On the other hand, with the nature of being prevalent, inexpensive and non-invasive, CT does present diagnostic features of AD to a great extent. This study explores the significance and impact on the application of the burgeoning deep learning techniques to the task of classification of CT brain images, in particular utilising convolutional neural network (CNN), aiming at providing supplementary information for the early diagnosis of Alzheimer's disease. Towards this end, three categories of CT images (N = 285) are clustered into three groups, which are AD, lesion (e.g. tumour) and normal ageing. In addition, considering the characteristics of this collection with larger thickness along the direction of depth (z) (~3-5 mm), an advanced CNN architecture is established integrating both 2D and 3D CNN networks. The fusion of the two CNN networks is subsequently coordinated based on the average of Softmax scores obtained from both networks consolidating 2D images along spatial axial directions and 3D segmented blocks respectively. As a result, the classification accuracy rates rendered by this elaborated CNN architecture are 85.2%, 80% and 95.3% for classes of AD, lesion and normal respectively with an average of 87.6%. Additionally, this improved CNN network appears to outperform the others when in comparison with 2D version only of CNN network as well as a number of state of the art hand-crafted approaches. As a result, these approaches deliver accuracy rates in percentage of 86.3, 85.6 ± 1.10, 86.3 ± 1.04, 85.2 ± 1.60, 83.1 ± 0.35 for 2D CNN, 2D SIFT, 2D KAZE, 3D SIFT and 3D KAZE respectively. The two major contributions of the paper constitute a new 3-D approach while applying deep learning technique to extract signature information

  16. Study warns of radiation risk in medical imaging

    NASA Astrophysics Data System (ADS)

    Gwynne, Peter

    2009-10-01

    A study of a million US patients suggests that some who undergo medical imaging could be exposed to more ionizing radiation than those who work with radioactive materials in nuclear power plants. The study, reported in The New England Journal of Medicine (361 849), implies that current exposure to radiation from conventional X-ray equipment as well as computed tomography (CT) and positron-emission tomography (PET) scanners could lead to tens of thousands of extra cases of cancer in the US alone.

  17. Infective endocarditis detection through SPECT/CT images digital processing

    NASA Astrophysics Data System (ADS)

    Moreno, Albino; Valdés, Raquel; Jiménez, Luis; Vallejo, Enrique; Hernández, Salvador; Soto, Gabriel

    2014-03-01

    Infective endocarditis (IE) is a difficult-to-diagnose pathology, since its manifestation in patients is highly variable. In this work, it was proposed a semiautomatic algorithm based on SPECT images digital processing for the detection of IE using a CT images volume as a spatial reference. The heart/lung rate was calculated using the SPECT images information. There were no statistically significant differences between the heart/lung rates values of a group of patients diagnosed with IE (2.62+/-0.47) and a group of healthy or control subjects (2.84+/-0.68). However, it is necessary to increase the study sample of both the individuals diagnosed with IE and the control group subjects, as well as to improve the images quality.

  18. Ground truth and CT image model simulation for pathophysiological human airway system

    NASA Astrophysics Data System (ADS)

    Ortner, Margarete; Fetita, Catalin; Brillet, Pierre-Yves; Pr"teux, Françoise; Grenier, Philippe

    2010-02-01

    Recurrent problem in medical image segmentation and analysis, establishing a ground truth for assessment purposes is often difficult. Facing this problem, the scientific community orients its efforts towards the development of objective methods for evaluation, namely by building up or simulating the missing ground truth for analysis. This paper focuses on the case of human pulmonary airways and develops a method 1) to simulate the ground truth for different pathophysiological configurations of the bronchial tree as a mesh model, and 2) to generate synthetic 3D CT images of airways associated with the simulated ground truth. The airway model is here built up based on the information provided by a medial axis (describing bronchus shape, subdivision geometry and local radii), which is computed from real CT data to ensure realism and matching with a patient-specific morphology. The model parameters can be further on adjusted to simulate various pathophysiological conditions of the same patient (longitudinal studies). Based on the airway mesh model, a 3D image model is synthesized by simulating the CT acquisition process. The image realism is achieved by including textural features of the surrounding pulmonary tissue which are obtained by segmentation from the same original CT data providing the airway axis. By varying the scanning simulation parameters, several 3D image models can be generated for the same airway mesh ground truth. Simulation results for physiological and pathological configurations are presented and discussed, illustrating the interest of such a modeling process for designing computer-aided diagnosis systems or for assessing their sensitivity, mainly for follow-up studies in asthma and COPD.

  19. CT imaging signs of surgically proven bowel trauma.

    PubMed

    LeBedis, Christina A; Anderson, Stephan W; Bates, David D B; Khalil, Ramy; Matherly, David; Wing, Heidi; Burke, Peter A; Soto, Jorge A

    2016-06-01

    The objective of this study was to determine the incidence and interobserver agreement of individual CT findings as well as the bowel injury prediction score (BIPS) in surgically proven bowel injury after blunt abdominal trauma. This HIPAA-compliant retrospective study was IRB approved and consent was waived. All patients 14 years or older who sustained surgically proven bowel injury after blunt abdominal trauma between 1/1/2004 and 6/30/2015 were included. Admission trauma MDCT scans were independently interpreted by two abdominal fellowship-trained radiologists who recorded the following CT findings: intraperitoneal fluid, mesenteric hematoma/fat stranding, bowel wall thickening/hematoma, active intravenous contrast extravasation, free intraperitoneal air, bowel wall discontinuity, and focal bowel hypoenhancement. Subsequently, the electronic medical records of the included patients, admission abdominal physical exam results, admission white blood cell count, and findings at exploratory laparotomy of the included patients were recorded. Thirty-three patients met the inclusion criteria. The incidence and interobserver agreement of the CT findings were as follows: intraperitoneal fluid 93.9 %, kappa = 0.784 (good); mesenteric hematoma/fat stranding 84.8 %, kappa = 0.718 (good); bowel wall thickening/hematoma 42.4 %, kappa = 0.491 (moderate); active IV contrast extravasation 36.3 %, kappa = 1.00 (perfect); free intraperitoneal air 21.2 %, kappa = 0.904 (very good), bowel wall discontinuity 6.1 %, kappa = 1.00 (perfect); and focal bowel hypoenhancement 6.1 %, kappa = 0.468 (moderate). An absence of the specified CT findings was encountered in 9.1 % with surgically proven bowel injuries (kappa = 1.00, perfect). In our study, 9/16 patients or 56.3 % had a bowel injury prediction score (BIPS) of 2 or more as defined by McNutt et al. (J Trauma Acute Care Surg 78(1):105-111, 2014). The presence of intraperitoneal fluid and

  20. Recent advances in medical imaging: anatomical and clinical applications.

    PubMed

    Grignon, Bruno; Mainard, Laurence; Delion, Matthieu; Hodez, Claude; Oldrini, Guillaume

    2012-10-01

    The aim of this paper was to present an overview of the most important recent advances in medical imaging and their potential clinical and anatomical applications. Dramatic changes have been particularly observed in the field of computed tomography (CT) and magnetic resonance imaging (MRI). Computed tomography (CT) has been completely overturned by the successive development of helical acquisition, multidetector and large area-detector acquisition. Visualising brain function has become a new challenge for MRI, which is called functional MRI, currently based principally on blood oxygenation level-dependent sequences, which could be completed or replaced by other techniques such as diffusion MRI (DWI). Based on molecular diffusion due to the thermal energy of free water, DWI offers a spectrum of anatomical and clinical applications, ranging from brain ischemia to visualisation of large fibrous structures of the human body such as the anatomical bundles of white matter with diffusion tensor imaging and tractography. In the field of X-ray projection imaging, a new low-dose device called EOS has been developed through new highly sensitive detectors of X-rays, allowing for acquiring frontal and lateral images simultaneously. Other improvements have been briefly mentioned. Technical principles have been considered in order to understand what is most useful in clinical practice as well as in the field of anatomical applications. Nuclear medicine has not been included.

  1. Advances in scintillators for medical imaging applications

    NASA Astrophysics Data System (ADS)

    van Loef, Edgar V.; Shah, Kanai S.

    2014-09-01

    A review is presented of some recent work in the field of inorganic scintillator research for medical imaging applications, in particular scintillation detectors for Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET).

  2. Web-based medical image archive system

    NASA Astrophysics Data System (ADS)

    Suh, Edward B.; Warach, Steven; Cheung, Huey; Wang, Shaohua A.; Tangiral, Phanidral; Luby, Marie; Martino, Robert L.

    2002-05-01

    This paper presents a Web-based medical image archive system in three-tier, client-server architecture for the storage and retrieval of medical image data, as well as patient information and clinical data. The Web-based medical image archive system was designed to meet the need of the National Institute of Neurological Disorders and Stroke for a central image repository to address questions of stroke pathophysiology and imaging biomarkers in stroke clinical trials by analyzing images obtained from a large number of clinical trials conducted by government, academic and pharmaceutical industry researchers. In the database management-tier, we designed the image storage hierarchy to accommodate large binary image data files that the database software can access in parallel. In the middle-tier, a commercial Enterprise Java Bean server and secure Web server manages user access to the image database system. User-friendly Web-interfaces and applet tools are provided in the client-tier for easy access to the image archive system over the Internet. Benchmark test results show that our three-tier image archive system yields fast system response time for uploading, downloading, and querying the image database.

  3. Imaging Properties of 3D Printed Materials: Multi-Energy CT of Filament Polymers.

    PubMed

    Shin, James; Sandhu, Ranjit S; Shih, George

    2017-02-06

    Clinical applications of 3D printing are increasingly commonplace, likewise the frequency of inclusion of 3D printed objects on imaging studies. Although there is a general familiarity with the imaging appearance of traditional materials comprising common surgical hardware and medical devices, comparatively less is known regarding the appearance of available 3D printing materials in the consumer market. This work detailing the CT appearance of a selected number of common filament polymer classes is an initial effort to catalog these data, to provide for accurate interpretation of imaging studies incidentally or intentionally including fabricated objects. Furthermore, this information can inform the design of image-realistic tissue-mimicking phantoms for a variety of applications, with clear candidate material analogs for bone, soft tissue, water, and fat attenuation.

  4. Ultrasmall dopamine-coated nanogolds: preparation, characteristics, and CT imaging

    PubMed Central

    Yu, Yao; Wu, Youshen; Liu, JiaJun; Zhan, Yonghua; Wu, Daocheng

    2016-01-01

    ABSTRACT Water-dispersible ultrasmall nanogolds (WDU AuNPs) and their dopamine-coated nanogolds (WDU AuNPs@DPAs) were prepared by a reduction method with sodium borohydride as a reducing agent and a stabilised agent of 2-mercaptosuccinic acid in aqueous solution. The effects of these nanoparticles on computed tomography (CT) imaging were evaluated. The size distributions and Zeta potential of the nanoparticles were measured with a Malvern size analyser, and nanoparticle morphology was observed by transmission electron microscopy. These characteristics were confirmed by Fourier transform spectroscopy and ultraviolet/visible spectra. It was found that WDU AuNPs@DPAs were 5.4 nm in size with clear core–shell structure. The 3-(4, 5-Dimethyl-2-thiazolyl)-2, 5-diphenyltetrazolium bromide assay results showed that the WDU AuNPs and WDU AuNPs@DPAs were hypotoxic to different cells. The WDU AuNPs@DPAs showed a much longer circulation time and a larger CT attenuation coefficient than iohexol and could be excreted by the kidney and bladder. These nanoparticles showed considerable potential for future application in CT imaging. PMID:27366201

  5. Improving image accuracy of region-of-interest in cone-beam CT using prior image.

    PubMed

    Lee, Jiseoc; Kim, Jin Sung; Cho, Seungryong

    2014-03-06

    In diagnostic follow-ups of diseases, such as calcium scoring in kidney or fat content assessment in liver using repeated CT scans, quantitatively accurate and consistent CT values are desirable at a low cost of radiation dose to the patient. Region of-interest (ROI) imaging technique is considered a reasonable dose reduction method in CT scans for its shielding geometry outside the ROI. However, image artifacts in the reconstructed images caused by missing data outside the ROI may degrade overall image quality and, more importantly, can decrease image accuracy of the ROI substantially. In this study, we propose a method to increase image accuracy of the ROI and to reduce imaging radiation dose via utilizing the outside ROI data from prior scans in the repeated CT applications. We performed both numerical and experimental studies to validate our proposed method. In a numerical study, we used an XCAT phantom with its liver and stomach changing their sizes from one scan to another. Image accuracy of the liver has been improved as the error decreased from 44.4 HU to -0.1 HU by the proposed method, compared to an existing method of data extrapolation to compensate for the missing data outside the ROI. Repeated cone-beam CT (CBCT) images of a patient who went through daily CBCT scans for radiation therapy were also used to demonstrate the performance of the proposed method experimentally. The results showed improved image accuracy inside the ROI. The magnitude of error decreased from -73.2 HU to 18 HU, and effectively reduced image artifacts throughout the entire image.

  6. Iterative image-domain decomposition for dual-energy CT

    SciTech Connect

    Niu, Tianye; Dong, Xue; Petrongolo, Michael; Zhu, Lei

    2014-04-15

    Purpose: Dual energy CT (DECT) imaging plays an important role in advanced imaging applications due to its capability of material decomposition. Direct decomposition via matrix inversion suffers from significant degradation of image signal-to-noise ratios, which reduces clinical values of DECT. Existing denoising algorithms achieve suboptimal performance since they suppress image noise either before or after the decomposition and do not fully explore the noise statistical properties of the decomposition process. In this work, the authors propose an iterative image-domain decomposition method for noise suppression in DECT, using the full variance-covariance matrix of the decomposed images. Methods: The proposed algorithm is formulated in the form of least-square estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, the authors include the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. The regularization term enforces the image smoothness by calculating the square sum of neighboring pixel value differences. To retain the boundary sharpness of the decomposed images, the authors detect the edges in the CT images before decomposition. These edge pixels have small weights in the calculation of the regularization term. Distinct from the existing denoising algorithms applied on the images before or after decomposition, the method has an iterative process for noise suppression, with decomposition performed in each iteration. The authors implement the proposed algorithm using a standard conjugate gradient algorithm. The method performance is evaluated using an evaluation phantom (Catphan©600) and an anthropomorphic head phantom. The results are compared with those generated using direct matrix inversion with no noise suppression, a denoising method applied on the decomposed images, and an existing algorithm with similar formulation as the

  7. Liver segmentation for CT images using GVF snake

    SciTech Connect

    Liu Fan; Zhao Binsheng; Kijewski, Peter K.; Wang Liang; Schwartz, Lawrence H.

    2005-12-15

    Accurate liver segmentation on computed tomography (CT) images is a challenging task especially at sites where surrounding tissues (e.g., stomach, kidney) have densities similar to that of the liver and lesions reside at the liver edges. We have developed a method for semiautomatic delineation of the liver contours on contrast-enhanced CT images. The method utilizes a snake algorithm with a gradient vector flow (GVF) field as its external force. To improve the performance of the GVF snake in the segmentation of the liver contour, an edge map was obtained with a Canny edge detector, followed by modifications using a liver template and a concavity removal algorithm. With the modified edge map, for which unwanted edges inside the liver were eliminated, the GVF field was computed and an initial liver contour was formed. The snake algorithm was then applied to obtain the actual liver contour. This algorithm was extended to segment the liver volume in a slice-by-slice fashion, where the result of the preceding slice constrained the segmentation of the adjacent slice. 551 two-dimensional liver images from 20 volumetric images with colorectal metastases spreading throughout the livers were delineated using this method, and also manually by a radiologist for evaluation. The difference ratio, which is defined as the percentage ratio of mismatching volume between the computer and the radiologist's results, ranged from 2.9% to 7.6% with a median value of 5.3%.

  8. Classification of lung area using multidetector-row CT images

    NASA Astrophysics Data System (ADS)

    Mukaibo, Tsutomu; Kawata, Yoshiki; Niki, Noboru; Ohmatsu, Hironobu; Kakinuma, Ryutaro; Eguchi, Kenji; Kaneko, Masahiro; Moriyama, Noriyuki

    2002-05-01

    Recently, we can get high quality images in the short time for the progress of X-ray CT scanner. And the three dimensional (3-D) analysis of pulmonary organs using multidetector-row CT (MDCT) images, is expected. This paper presents a method for classifying lung area into each lobe using pulmonary MDCT images of the whole lung area. It is possible to recognize the position of nodule by classifying lung area into these lobes. The structure of lungs differs on the right one and left one. The right lung is divided into three domains by major fissure and minor fissure. And, the left lung is divided into two domains by major fissure. Watching MDCT images carefully, we find that the surroundings of fissures have few blood vessels. Therefore, lung area is classified by extraction of the domain that the distance from pulmonary blood vessels is large and connective search of these extracted domains. These extraction and search are realized by 3-D weighted Hough transform.

  9. Accuracy of quantitative reconstructions in SPECT/CT imaging

    NASA Astrophysics Data System (ADS)

    Shcherbinin, S.; Celler, A.; Belhocine, T.; van der Werf, R.; Driedger, A.

    2008-09-01

    The goal of this study was to determine the quantitative accuracy of our OSEM-APDI reconstruction method based on SPECT/CT imaging for Tc-99m, In-111, I-123, and I-131 isotopes. Phantom studies were performed on a SPECT/low-dose multislice CT system (Infinia-Hawkeye-4 slice, GE Healthcare) using clinical acquisition protocols. Two radioactive sources were centrally and peripherally placed inside an anthropometric Thorax phantom filled with non-radioactive water. Corrections for attenuation, scatter, collimator blurring and collimator septal penetration were applied and their contribution to the overall accuracy of the reconstruction was evaluated. Reconstruction with the most comprehensive set of corrections resulted in activity estimation with error levels of 3-5% for all the isotopes.

  10. 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).

  11. Image processing for medical diagnosis using CNN

    NASA Astrophysics Data System (ADS)

    Arena, Paolo; Basile, Adriano; Bucolo, Maide; Fortuna, Luigi

    2003-01-01

    Medical diagnosis is one of the most important area in which image processing procedures are usefully applied. Image processing is an important phase in order to improve the accuracy both for diagnosis procedure and for surgical operation. One of these fields is tumor/cancer detection by using Microarray analysis. The research studies in the Cancer Genetics Branch are mainly involved in a range of experiments including the identification of inherited mutations predisposing family members to malignant melanoma, prostate and breast cancer. In bio-medical field the real-time processing is very important, but often image processing is a quite time-consuming phase. Therefore techniques able to speed up the elaboration play an important rule. From this point of view, in this work a novel approach to image processing has been developed. The new idea is to use the Cellular Neural Networks to investigate on diagnostic images, like: Magnetic Resonance Imaging, Computed Tomography, and fluorescent cDNA microarray images.

  12. Medical image segmentation by MDP model

    NASA Astrophysics Data System (ADS)

    Lu, Yisu; Chen, Wufan

    2011-11-01

    MDP (Dirichlet Process Mixtures) model is applied to segment medical images in this paper. Segmentation can been automatically done without initializing segmentation class numbers. The MDP model segmentation algorithm is used to segment natural images and MR (Magnetic Resonance) images in the paper. To demonstrate the accuracy of the MDP model segmentation algorithm, many compared experiments, such as EM (Expectation Maximization) image segmentation algorithm, K-means image segmentation algorithm and MRF (Markov Field) image segmentation algorithm, have been done to segment medical MR images. All the methods are also analyzed quantitatively by using DSC (Dice Similarity Coefficients). The experiments results show that DSC of MDP model segmentation algorithm of all slices exceed 90%, which show that the proposed method is robust and accurate.

  13. Current perspectives in medical image perception

    PubMed Central

    Krupinski, Elizabeth A.

    2013-01-01

    Medical images constitute a core portion of the information a physician utilizes to render diagnostic and treatment decisions. At a fundamental level, this diagnostic process involves two basic processes: visually inspecting the image (visual perception) and rendering an interpretation (cognition). The likelihood of error in the interpretation of medical images is, unfortunately, not negligible. Errors do occur, and patients’ lives are impacted, underscoring our need to understand how physicians interact with the information in an image during the interpretation process. With improved understanding, we can develop ways to further improve decision making and, thus, to improve patient care. The science of medical image perception is dedicated to understanding and improving the clinical interpretation process. PMID:20601701

  14. Lung imaging in rodents using dual energy micro-CT

    NASA Astrophysics Data System (ADS)

    Badea, C. T.; Guo, X.; Clark, D.; Johnston, S. M.; Marshall, C.; Piantadosi, C.

    2012-03-01

    Dual energy CT imaging is expected to play a major role in the diagnostic arena as it provides material decomposition on an elemental basis. The purpose of this work is to investigate the use of dual energy micro-CT for the estimation of vascular, tissue, and air fractions in rodent lungs using a post-reconstruction three-material decomposition method. We have tested our method using both simulations and experimental work. Using simulations, we have estimated the accuracy limits of the decomposition for realistic micro-CT noise levels. Next, we performed experiments involving ex vivo lung imaging in which intact lungs were carefully removed from the thorax, were injected with an iodine-based contrast agent and inflated with air at different volume levels. Finally, we performed in vivo imaging studies in (n=5) C57BL/6 mice using fast prospective respiratory gating in endinspiration and end-expiration for three different levels of positive end-expiratory pressure (PEEP). Prior to imaging, mice were injected with a liposomal blood pool contrast agent. The mean accuracy values were for Air (95.5%), Blood (96%), and Tissue (92.4%). The absolute accuracy in determining all fraction materials was 94.6%. The minimum difference that we could detect in material fractions was 15%. As expected, an increase in PEEP levels for the living mouse resulted in statistically significant increases in air fractions at end-expiration, but no significant changes in end-inspiration. Our method has applicability in preclinical pulmonary studies where various physiological changes can occur as a result of genetic changes, lung disease, or drug effects.

  15. 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.

  16. Lesion area detection using source image correlation coefficient for CT perfusion imaging.

    PubMed

    Fan Zhu; Rodriguez Gonzalez, David; Carpenter, Trevor; Atkinson, Malcolm; Wardlaw, Joanna

    2013-09-01

    Computer tomography (CT) perfusion imaging is widely used to calculate brain hemodynamic quantities such as cerebral blood flow, cerebral blood volume, and mean transit time that aid the diagnosis of acute stroke. Since perfusion source images contain more information than hemodynamic maps, good utilization of the source images can lead to better understanding than the hemodynamic maps alone. Correlation-coefficient tests are used in our approach to measure the similarity between healthy tissue time-concentration curves and unknown curves. This information is then used to differentiate penumbra and dead tissues from healthy tissues. The goal of the segmentation is to fully utilize information in the perfusion source images. Our method directly identifies suspected abnormal areas from perfusion source images and then delivers a suggested segmentation of healthy, penumbra, and dead tissue. This approach is designed to handle CT perfusion images, but it can also be used to detect lesion areas in magnetic resonance perfusion images.

  17. A web-based image viewer for multiple PET-CT follow-up studies.

    PubMed

    Haraguchi, Daiki; Kim, Jinman; Kumar, Ashnil; Constantinescu, Liviu; Wen, Lingfeng; Feng, David Dagan

    2011-01-01

    There exist many viewers for single-modal medical images that are efficient and are equipped with powerful analysis tools. However, there is a distinct lack of efficient image viewers for multi-modality images, particularly for displaying multiple follow-up studies that depict a patient's response to treatment over time. Such viewers would be required to display large amounts of image data. In this study, we present the TAGIGEN viewer--a web-based image viewer designed specifically for the visualisation of multi-modality follow-up studies. We innovate by defining a series of dynamically generated image grid layouts that display sets of related images together in order to improve the ability to compare and assimilate the myriad images. We adopted a web-based client-server image streaming technology, thus enabling interactive navigation of the images in a computationally efficient manner. Furthermore, our web-based approach is interoperable and requires no software installation. We evaluated the ability of our viewer in displaying and understanding a patient's follow-up images in a case study with combined positron emission tomography and computed tomography (PET-CT) follow-up scans. We conducted a usability survey on 10 participants to measure the usefulness of our viewer, used as an outpatient viewer e.g. viewer designed for use by the patients, in tracking a patient's disease state across four PET-CT studies. Our initial results suggest that our viewer was able to efficiently visualise the patient data over time, and that the web-based implementation was fast (loading on average within 5.6 seconds with real-time navigation) and easy to use (overall survey score higher than 4 / 5).

  18. Infrared thermographic imaging, magnetic resonance imaging, CT scan and myelography in low back pain.

    PubMed

    Thomas, D; Cullum, D; Siahamis, G; Langlois, S

    1990-08-01

    Sixty-five cases of chronic low back pain were studied. Infrared thermography (IRT) was abnormal in 92%, magnetic resonance imaging (MRI) in 89%, computerized tomography (CT) in 87% and myelography in 80%. IRT correlated with MRI in 94% of cases, and with CT in 87% of cases. Of 22 MRI positive disc and root cases, 21 (95%) had significant leg abnormalities on IRT. All 19 cases with radicular involvement on CT and all 18 with radicular involvement on myelography demonstrated significant leg changes on IRT.

  19. 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

    SciTech Connect

    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 optical 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 image

  20. Molecular Body Imaging: MR Imaging, CT, and US. Part I. Principles

    PubMed Central

    Kircher, Moritz F.

    2012-01-01

    Molecular imaging, generally defined as noninvasive imaging of cellular and subcellular events, has gained tremendous depth and breadth as a research and clinical discipline in recent years. The coalescence of major advances in engineering, molecular biology, chemistry, immunology, and genetics has fueled multi- and interdisciplinary innovations with the goal of driving clinical noninvasive imaging strategies that will ultimately allow disease identification, risk stratification, and monitoring of therapy effects with unparalleled sensitivity and specificity. Techniques that allow imaging of molecular and cellular events facilitate and go hand in hand with the development of molecular therapies, offering promise for successfully combining imaging with therapy. While traditionally nuclear medicine imaging techniques, in particular positron emission tomography (PET), PET combined with computed tomography (CT), and single photon emission computed tomography, have been the molecular imaging methods most familiar to clinicians, great advances have recently been made in developing imaging techniques that utilize magnetic resonance (MR), optical, CT, and ultrasonographic (US) imaging. In the first part of this review series, we present an overview of the principles of MR imaging-, CT-, and US-based molecular imaging strategies. © RSNA, 2012 PMID:22623690

  1. Improved image quality for x-ray CT imaging of gel dosimeters

    SciTech Connect

    Kakakhel, M. B.; Kairn, T.; Kenny, J.; Trapp, J. V.

    2011-09-15

    Purpose: This study provides a simple method for improving precision of x-ray computed tomography (CT) scans of irradiated polymer gel dosimetry. The noise affecting CT scans of irradiated gels has been an impediment to the use of clinical CT scanners for gel dosimetry studies. Methods: In this study, it is shown that multiple scans of a single PAGAT gel dosimeter can be used to extrapolate a ''zero-scan'' image which displays a similar level of precision to an image obtained by averaging multiple CT images, without the compromised dose measurement resulting from the exposure of the gel to radiation from the CT scanner. Results: When extrapolating the zero-scan image, it is shown that exponential and simple linear fits to the relationship between Hounsfield unit and scan number, for each pixel in the image, provide an accurate indication of gel density. Conclusions: It is expected that this work will be utilized in the analysis of three-dimensional gel volumes irradiated using complex radiotherapy treatments.

  2. Medical applications of microwave imaging.

    PubMed

    Wang, Zhao; Lim, Eng Gee; Tang, Yujun; Leach, Mark

    2014-01-01

    Ultrawide band (UWB) microwave imaging is a promising method for the detection of early stage breast cancer, based on the large contrast in electrical parameters between malignant tumour tissue and the surrounding normal breast-tissue. In this paper, the detection and imaging of a malignant tumour are performed through a tomographic based microwave system and signal processing. Simulations of the proposed system are performed and postimage processing is presented. Signal processing involves the extraction of tumour information from background information and then image reconstruction through the confocal method delay-and-sum algorithms. Ultimately, the revision of time-delay and the superposition of more tumour signals are applied to improve accuracy.

  3. Intuitionistic fuzzy segmentation of medical images.

    PubMed

    Chaira, Tamalika

    2010-06-01

    This paper proposes a novel and probably the first method, using Attanassov intuitionistic fuzzy set theory to segment blood vessels and also the blood cells in pathological images. This type of segmentation is very important in detecting different types of human diseases, e.g., an increase in the number of vessels may lead to cancer in prostates, mammary, etc. The medical images are not properly illuminated, and segmentation in that case becomes very difficult. A novel image segmentation approach using intuitionistic fuzzy set theory and a new membership function is proposed using restricted equivalence function from automorphisms, for finding the membership values of the pixels of the image. An intuitionistic fuzzy image is constructed using Sugeno type intuitionistic fuzzy generator. Local thresholding is applied to threshold medical images. The results showed a much better performance on poor contrast medical images, where almost all the blood vessels and blood cells are visible properly. There are several fuzzy and intuitionistic fuzzy thresholding methods, but these methods are not related to the medical images. To make a comparison with the proposed method with other thresholding methods, the method is compared with six nonfuzzy, fuzzy, and intuitionistic fuzzy methods.

  4. Automated medical image library creation for education.

    PubMed

    Smith, Mark; Feied, Craig; Gillam, Michael; Handler, Jonathan

    2006-01-01

    The authors describe a method to create a medical teaching library that is automatically maintained, contains tens of thousands of radiologic images and is built using existing, internal, hospital dictations, radiologic images, and an off-the-shelf commercial search engine product (Google Inc.).

  5. Acoustic waves in medical imaging and diagnostics.

    PubMed

    Sarvazyan, Armen P; Urban, Matthew W; Greenleaf, James F

    2013-07-01

    Up until about two decades ago acoustic imaging and ultrasound imaging were synonymous. The term ultrasonography, or its abbreviated version sonography, meant an imaging modality based on the use of ultrasonic compressional bulk waves. Beginning in the 1990s, there started to emerge numerous acoustic imaging modalities based on the use of a different mode of acoustic wave: shear waves. Imaging with these waves was shown to provide very useful and very different information about the biological tissue being examined. We discuss the physical basis for the differences between these two basic modes of acoustic waves used in medical imaging and analyze the advantages associated with shear acoustic imaging. A comprehensive analysis of the range of acoustic wavelengths, velocities and frequencies that have been used in different imaging applications is presented. We discuss the potential for future shear wave imaging applications.

  6. Multi-channel medical imaging system

    SciTech Connect

    Frangioni, John V

    2013-12-31

    A medical imaging system provides simultaneous rendering of visible light and fluorescent images. The system may employ dyes in a small-molecule form that remain in the subject's blood stream for several minutes, allowing real-time imaging of the subject's circulatory system superimposed upon a conventional, visible light image of the subject. The system may provide an excitation light source to excite the fluorescent substance and a visible light source for general illumination within the same optical guide used to capture images. The system may be configured for use in open surgical procedures by providing an operating area that is closed to ambient light. The systems described herein provide two or more diagnostic imaging channels for capture of multiple, concurrent diagnostic images and may be used where a visible light image may be usefully supplemented by two or more images that are independently marked for functional interest.

  7. Multi-channel medical imaging system

    SciTech Connect

    Frangioni, John V.

    2016-05-03

    A medical imaging system provides simultaneous rendering of visible light and fluorescent images. The system may employ dyes in a small-molecule form that remain in a subject's blood stream for several minutes, allowing real-time imaging of the subject's circulatory system superimposed upon a conventional, visible light image of the subject. The system may provide an excitation light source to excite the fluorescent substance and a visible light source for general illumination within the same optical guide used to capture images. The system may be configured for use in open surgical procedures by providing an operating area that is closed to ambient light. The systems described herein provide two or more diagnostic imaging channels for capture of multiple, concurrent diagnostic images and may be used where a visible light image may be usefully supplemented by two or more images that are independently marked for functional interest.

  8. Phantom based evaluation of CT to CBCT image registration for proton therapy dose recalculation

    NASA Astrophysics Data System (ADS)

    Landry, Guillaume; Dedes, George; Zöllner, Christoph; Handrack, Josefine; Janssens, Guillaume; Orban de Xivry, Jonathan; Reiner, Michael; Paganelli, Chiara; Riboldi, Marco; Kamp, Florian; Söhn, Matthias; Wilkens, Jan J.; Baroni, Guido; Belka, Claus; Parodi, Katia

    2015-01-01

    The ability to perform dose recalculation on the anatomy of the day is important in the context of adaptive proton therapy. The objective of this study was to investigate the use of deformable image registration (DIR) and cone beam CT (CBCT) imaging to generate the daily stopping power distribution of the patient. We investigated the deformation of the planning CT scan (pCT) onto daily CBCT images to generate a virtual CT (vCT) using a deformable phantom designed for the head and neck (H & N) region. The phantom was imaged at a planning CT scanner in planning configuration, yielding a pCT and in deformed, treatment day configuration, yielding a reference CT (refCT). The treatment day configuration was additionally scanned at a CBCT scanner. A Morphons DIR algorithm was used to generate a vCT. The accuracy of the vCT was evaluated by comparison to the refCT in terms of corresponding features as identified by an adaptive scale invariant feature transform (aSIFT) algorithm. Additionally, the vCT CT numbers were compared to those of the refCT using both profiles and regions of interest and the volumes and overlap (DICE coefficients) of various phantom structures were compared. The water equivalent thickness (WET) of the vCT, refCT and pCT were also compared to evaluate proton range differences. Proton dose distributions from the same initial fluence were calculated on the refCT, vCT and pCT and compared in terms of proton range. The method was tested on a clinical dataset using a replanning CT scan acquired close in time to a CBCT scan as reference using the WET evaluation. Results from the aSIFT investigation suggest a deformation accuracy of 2-3 mm. The use of the Morphon algorithm did not distort CT number intensity in uniform regions and WET differences between vCT and refCT were of the order of 2% of the proton range. This result was confirmed by proton dose calculations. The patient results were consistent with phantom observations. In conclusion, our phantom

  9. Multispectral imaging for medical diagnosis

    NASA Technical Reports Server (NTRS)

    Anselmo, V. J.

    1977-01-01

    Photography technique determines amount of morbidity present in tissue. Imaging apparatus incorporates numerical filtering. Overall system operates in near-real time. Information gained from this system enables physician to understand extent of injury and leads to accelerated treatment.

  10. Medical Image Fusion Based on Feature Extraction and Sparse Representation

    PubMed Central

    Wei, Gao; Zongxi, Song

    2017-01-01

    As a novel multiscale geometric analysis tool, sparse representation has shown many advantages over the conventional image representation methods. However, the standard sparse representation does not take intrinsic structure and its time complexity into consideration. In this paper, a new fusion mechanism for multimodal medical images based on sparse representation and decision map is proposed to deal with these problems simultaneously. Three decision maps are designed including structure information map (SM) and energy information map (EM) as well as structure and energy map (SEM) to make the results reserve more energy and edge information. SM contains the local structure feature captured by the Laplacian of a Gaussian (LOG) and EM contains the energy and energy distribution feature detected by the mean square deviation. The decision map is added to the normal sparse representation based method to improve the speed of the algorithm. Proposed approach also improves the quality of the fused results by enhancing the contrast and reserving more structure and energy information from the source images. The experiment results of 36 groups of CT/MR, MR-T1/MR-T2, and CT/PET images demonstrate that the method based on SR and SEM outperforms five state-of-the-art methods. PMID:28321246

  11. Proton-induced x-ray fluorescence CT imaging

    SciTech Connect

    Bazalova-Carter, Magdalena Xing, Lei; Ahmad, Moiz; Matsuura, Taeko; Takao, Seishin; Shirato, Hiroki; Umegaki, Kikuo; Matsuo, Yuto; Fahrig, Rebecca

    2015-02-15

    Purpose: To demonstrate the feasibility of proton-induced x-ray fluorescence CT (pXFCT) imaging of gold in a small animal sized object by means of experiments and Monte Carlo (MC) simulations. Methods: First, proton-induced gold x-ray fluorescence (pXRF) was measured as a function of gold concentration. Vials of 2.2 cm in diameter filled with 0%–5% Au solutions were irradiated with a 220 MeV proton beam and x-ray fluorescence induced by the interaction of protons, and Au was detected with a 3 × 3 mm{sup 2} CdTe detector placed at 90° with respect to the incident proton beam at a distance of 45 cm from the vials. Second, a 7-cm diameter water phantom containing three 2.2-diameter vials with 3%–5% Au solutions was imaged with a 7-mm FWHM 220 MeV proton beam in a first generation CT scanning geometry. X-rays scattered perpendicular to the incident proton beam were acquired with the CdTe detector placed at 45 cm from the phantom positioned on a translation/rotation stage. Twenty one translational steps spaced by 3 mm at each of 36 projection angles spaced by 10° were acquired, and pXFCT images of the phantom were reconstructed with filtered back projection. A simplified geometry of the experimental data acquisition setup was modeled with the MC TOPAS code, and simulation results were compared to the experimental data. Results: A linear relationship between gold pXRF and gold concentration was observed in both experimental and MC simulation data (R{sup 2} > 0.99). All Au vials were apparent in the experimental and simulated pXFCT images. Specifically, the 3% Au vial was detectable in the experimental [contrast-to-noise ratio (CNR) = 5.8] and simulated (CNR = 11.5) pXFCT image. Due to fluorescence x-ray attenuation in the higher concentration vials, the 4% and 5% Au contrast were underestimated by 10% and 15%, respectively, in both the experimental and simulated pXFCT images. Conclusions: Proton-induced x-ray fluorescence CT imaging of 3%–5% gold solutions in a

  12. Proton-induced x-ray fluorescence CT imaging

    PubMed Central

    Bazalova-Carter, Magdalena; Ahmad, Moiz; Matsuura, Taeko; Takao, Seishin; Matsuo, Yuto; Fahrig, Rebecca; Shirato, Hiroki; Umegaki, Kikuo; Xing, Lei

    2015-01-01

    Purpose: To demonstrate the feasibility of proton-induced x-ray fluorescence CT (pXFCT) imaging of gold in a small animal sized object by means of experiments and Monte Carlo (MC) simulations. Methods: First, proton-induced gold x-ray fluorescence (pXRF) was measured as a function of gold concentration. Vials of 2.2 cm in diameter filled with 0%–5% Au solutions were irradiated with a 220 MeV proton beam and x-ray fluorescence induced by the interaction of protons, and Au was detected with a 3 × 3 mm2 CdTe detector placed at 90° with respect to the incident proton beam at a distance of 45 cm from the vials. Second, a 7-cm diameter water phantom containing three 2.2-diameter vials with 3%–5% Au solutions was imaged with a 7-mm FWHM 220 MeV proton beam in a first generation CT scanning geometry. X-rays scattered perpendicular to the incident proton beam were acquired with the CdTe detector placed at 45 cm from the phantom positioned on a translation/rotation stage. Twenty one translational steps spaced by 3 mm at each of 36 projection angles spaced by 10° were acquired, and pXFCT images of the phantom were reconstructed with filtered back projection. A simplified geometry of the experimental data acquisition setup was modeled with the MC TOPAS code, and simulation results were compared to the experimental data. Results: A linear relationship between gold pXRF and gold concentration was observed in both experimental and MC simulation data (R2 > 0.99). All Au vials were apparent in the experimental and simulated pXFCT images. Specifically, the 3% Au vial was detectable in the experimental [contrast-to-noise ratio (CNR) = 5.8] and simulated (CNR = 11.5) pXFCT image. Due to fluorescence x-ray attenuation in the higher concentration vials, the 4% and 5% Au contrast were underestimated by 10% and 15%, respectively, in both the experimental and simulated pXFCT images. Conclusions: Proton-induced x-ray fluorescence CT imaging of 3%–5% gold solutions in a small animal

  13. Using the ACR CT accreditation phantom for routine image quality assurance on both CT and CBCT imaging systems in a radiotherapy environment.

    PubMed

    Hobson, Maritza A; Soisson, Emilie T; Davis, Stephen D; Parker, William

    2014-07-08

    Image-guided radiation therapy using cone-beam computed tomography (CBCT) is becoming routine practice in modern radiation therapy. The purpose of this work was to develop an imaging QA program for CT and CBCT units in our department, based on the American College of Radiology (ACR) CT accreditation phantom. The phantom has four testing modules, permitting one to test CT number accuracy, slice width, low contrast resolution, image uniformity, in-plane distance accuracy, and high-contrast resolution reproducibly with suggested window/levels for image analysis. Additional tests for contrast-to-noise ratio (CNR) and noise were added using the polyethylene and acrylic plugs. Baseline values were obtained from CT simulator images acquired on a Phillips Brilliance Big Bore CT simulator and CBCT images acquired on three Varian CBCTs for the imaging protocols most used clinically. Images were then acquired quarterly over a period of two years. Images were exported via DICOM and analyzed manually using OsiriX. Baseline values were used to ensure that image quality remained consistent quarterly, and baselines were reset at any major maintenance or recalibration. Analysis of CT simulator images showed that image quality was within ACR guidelines for all tested scanning protocols. All three CBCT systems were unable to distinguish the low-contrast resolution plugs and had the same high-contrast resolution over all imaging protocols. Analysis of CBCT results over time determined a range of values that could be used to establish quantitative tolerance levels for image quality deterioration. While appropriate for the helical CT, the ACR phantom and guidelines could be modified to be more useful in evaluating CBCT systems. In addition, the observed values for the CT simulator were well within ACR tolerances.

  14. Stump appendicitis: surgical background, CT appearance, and imaging mimics.

    PubMed

    Johnston, Jennifer; Myers, Daniel T; Williams, Todd R

    2015-02-01

    Stump appendicitis, also known as remnant appendicitis, is an uncommon entity with little radiologic literature. It is the result of unintentional incomplete appendectomy with subsequent inflammatory changes in the appendiceal remnant. A retrospective review of the radiology and pathology archives at our institution over an 8-year period yielded six surgically/pathologically confirmed cases. Imaging findings at presentation were evaluated, including appendiceal stump length, appendiceal stump diameter, presence or absence of surrounding stranding in the periappendiceal fat, and presence or absence of complication (perforation or abscess). The CT findings of the six cases had an average surgical specimen appendiceal stump length of 3.5 cm (range 2.0-5 cm) and an average appendiceal diameter of 12.3 mm (range 10-16 mm). All six cases demonstrated the presence of periappendiceal inflammatory fat stranding on the CT scan. Range of imaging presentation is reviewed with pictorial examples as well as examples of potential false-positive cases (mimics) including Crohn's disease, residual surgical drain tract, and epiploic appendagitis. Familiarity with stump appendicitis as well as its imaging mimics may lead to earlier diagnosis and treatment and prevent unnecessary complications.

  15. An Iterative CT Reconstruction Algorithm for Fast Fluid Flow Imaging.

    PubMed

    Van Eyndhoven, Geert; Batenburg, K Joost; Kazantsev, Daniil; Van Nieuwenhove, Vincent; Lee, Peter D; Dobson, Katherine J; Sijbers, Jan

    2015-11-01

    The study of fluid flow through solid matter by computed tomography (CT) imaging has many applications, ranging from petroleum and aquifer engineering to biomedical, manufacturing, and environmental research. To avoid motion artifacts, current experiments are often limited to slow fluid flow dynamics. This severely limits the applicability of the technique. In this paper, a new iterative CT reconstruction algorithm for improved a temporal/spatial resolution in the imaging of fluid flow through solid matter is introduced. The proposed algorithm exploits prior knowledge in two ways. First, the time-varying object is assumed to consist of stationary (the solid matter) and dynamic regions (the fluid flow). Second, the attenuation curve of a particular voxel in the dynamic region is modeled by a piecewise constant function over time, which is in accordance with the actual advancing fluid/air boundary. Quantitative and qualitative results on different simulation experiments and a real neutron tomography data set show that, in comparison with the state-of-the-art algorithms, the proposed algorithm allows reconstruction from substantially fewer projections per rotation without image quality loss. Therefore, the temporal resolution can be substantially increased, and thus fluid flow experiments with faster dynamics can be performed.

  16. Simulation of four-dimensional CT images from deformable registration between inhale and exhale breath-hold CT scans

    SciTech Connect

    Sarrut, David; Boldea, Vlad; Miguet, Serge; Ginestet, Chantal

    2006-03-15

    Purpose: We propose to simulate an artificial four-dimensional (4-D) CT image of the thorax during breathing. It is performed by deformable registration of two CT scans acquired at inhale and exhale breath-hold. Materials and methods: Breath-hold images were acquired with the ABC (Active Breathing Coordinator) system. Dense deformable registrations were performed. The method was a minimization of the sum of squared differences (SSD) using an approximated second-order gradient. Gaussian and linear-elastic vector field regularizations were compared. A new preprocessing step, called a priori lung density modification (APLDM), was proposed to take into account lung density changes due to inspiration. It consisted of modulating the lung densities in one image according to the densities in the other, in order to make them comparable. Simulated 4-D images were then built by vector field interpolation and image resampling of the two initial CT images. A variation in the lung density was taken into account to generate intermediate artificial CT images. The Jacobian of the deformation was used to compute voxel values in Hounsfield units. The accuracy of the deformable registration was assessed by the spatial correspondence of anatomic landmarks located by experts. Results: APLDM produced statistically significantly better results than the reference method (registration without APLDM preprocessing). The mean (and standard deviation) of distances between automatically found landmark positions and landmarks set by experts were 2.7(1.1) mm with APLDM, and 6.3(3.8) mm without. Interexpert variability was 2.3(1.2) mm. The differences between Gaussian and linear elastic regularizations were not statistically significant. In the second experiment using 4-D images, the mean difference between automatic and manual landmark positions for intermediate CT images was 2.6(2.0) mm. Conclusion: The generation of 4-D CT images by deformable registration of inhale and exhale CT images is

  17. Segmentation and separation of venous vasculatures in liver CT images

    NASA Astrophysics Data System (ADS)

    Wang, Lei; Hansen, Christian; Zidowitz, Stephan; Hahn, Horst K.

    2014-03-01

    Computer-aided analysis of venous vasculatures including hepatic veins and portal veins is important in liver surgery planning. The analysis normally consists of two important pre-processing tasks: segmenting both vasculatures and separating them from each other by assigning different labels. During the acquisition of multi-phase CT images, both of the venous vessels are enhanced by injected contrast agent and acquired either in a common phase or in two individual phases. The enhanced signals established by contrast agent are often not stably acquired due to non-optimal acquisition time. Inadequate contrast and the presence of large lesions in oncological patients, make the segmentation task quite challenging. To overcome these diffculties, we propose a framework with minimal user interactions to analyze venous vasculatures in multi-phase CT images. Firstly, presented vasculatures are automatically segmented adopting an efficient multi-scale Hessian-based vesselness filter. The initially segmented vessel trees are then converted to a graph representation, on which a series of graph filters are applied in post-processing steps to rule out irrelevant structures. Eventually, we develop a semi-automatic workow to refine the segmentation in the areas of inferior vena cava and entrance of portal veins, and to simultaneously separate hepatic veins from portal veins. Segmentation quality was evaluated with intensive tests enclosing 60 CT images from both healthy liver donors and oncological patients. To quantitatively measure the similarities between segmented and reference vessel trees, we propose three additional metrics: skeleton distance, branch coverage, and boundary surface distance, which are dedicated to quantifying the misalignment induced by both branching patterns and radii of two vessel trees.

  18. 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.

  19. Semantic Feature Extraction for Brain CT Image Clustering Using Nonnegative Matrix Factorization

    NASA Astrophysics Data System (ADS)

    Liu, Weixiang; Peng, Fei; Feng, Shu; You, Jiangsheng; Chen, Ziqiang; Wu, Jian; Yuan, Kehong; Ye, Datian

    Brain computed tomography (CT) image based computer-aided diagnosis (CAD) system is helpful for clinical diagnosis and treatment. However it is challenging to extract significant features for analysis because CT images come from different people and CT operator. In this study, we apply nonnegative matrix factorization to extract both appearance and histogram based semantic features of images for clustering analysis as test. Our experimental results on normal and tumor CT images demonstrate that NMF can discover local features for both visual content and histogram based semantics, and the clustering results show that the semantic image features are superior to low level visual features.

  20. Pushing CT and MR Imaging to the Molecular Level for Studying the “Omics”: Current Challenges and Advancements

    PubMed Central

    Huang, Hsuan-Ming; Shih, Yi-Yu

    2014-01-01

    During the past decade, medical imaging has made the transition from anatomical imaging to functional and even molecular imaging. Such transition provides a great opportunity to begin the integration of imaging data and various levels of biological data. In particular, the integration of imaging data and multiomics data such as genomics, metabolomics, proteomics, and pharmacogenomics may open new avenues for predictive, preventive, and personalized medicine. However, to promote imaging-omics integration, the practical challenge of imaging techniques should be addressed. In this paper, we describe key challenges in two imaging techniques: computed tomography (CT) and magnetic resonance imaging (MRI) and then review existing technological advancements. Despite the fact that CT and MRI have different principles of image formation, both imaging techniques can provide high-resolution anatomical images while playing a more and more important role in providing molecular information. Such imaging techniques that enable single modality to image both the detailed anatomy and function of tissues and organs of the body will be beneficial in the imaging-omics field. PMID:24738056

  1. Towards a comprehensive CT image segmentation for thoracic organ radiation dose estimation and reporting

    NASA Astrophysics Data System (ADS)

    Lorenz, Cristian; Ruppertshofen, Heike; Vik, Torbjörn; Prinsen, Peter; Wiegert, Jens

    2014-03-01

    Administered dose of ionizing radiation during medical imaging is an issue of increasing concern for the patient, for the clinical community, and for respective regulatory bodies. CT radiation dose is currently estimated based on a set of very simplifying assumptions which do not take the actual body geometry and organ specific doses into account. This makes it very difficult to accurately report imaging related administered dose and to track it for different organs over the life of the patient. In this paper this deficit is addressed in a two-fold way. In a first step, the absorbed radiation dose in each image voxel is estimated based on a Monte-Carlo simulation of X-ray absorption and scattering. In a second step, the image is segmented into tissue types with different radio sensitivity. In combination this allows to calculate the effective dose as a weighted sum of the individual organ doses. The main purpose of this paper is to assess the feasibility of automatic organ specific dose estimation. With respect to a commercially applicable solution and respective robustness and efficiency requirements, we investigated the effect of dose sampling rather than integration over the organ volume. We focused on the thoracic anatomy as the exemplary body region, imaged frequently by CT. For image segmentation we applied a set of available approaches which allowed us to cover the main thoracic radio-sensitive tissue types. We applied the dose estimation approach to 10 thoracic CT datasets and evaluated segmentation accuracy and administered dose and could show that organ specific dose estimation can be achieved.

  2. Medical imaging techniques: implications for nursing care.

    PubMed

    Malcolm, Alison

    The four basic techniques of medical imaging are X-ray, ultrasound, magnetic resonance and radionuclide. This article describes imaging techniques that display anatomical structure and those that are better at showing the physiological function of organs and tissues. Safety and preparation relating to nursing practice are discussed. Understanding the purpose and limitations of the different imaging techniques is important for providing best patient care.

  3. Superiorization-based multi-energy CT image reconstruction

    NASA Astrophysics Data System (ADS)

    Yang, Q.; Cong, W.; Wang, G.

    2017-04-01

    The recently-developed superiorization approach is efficient and robust for solving various constrained optimization problems. This methodology can be applied to multi-energy CT image reconstruction with the regularization in terms of the prior rank, intensity and sparsity model (PRISM). In this paper, we propose a superiorized version of the simultaneous algebraic reconstruction technique (SART) based on the PRISM model. Then, we compare the proposed superiorized algorithm with the Split-Bregman algorithm in numerical experiments. The results show that both the Superiorized-SART and the Split-Bregman algorithms generate good results with weak noise and reduced artefacts.

  4. Medical image segmentation using genetic algorithms.

    PubMed

    Maulik, Ujjwal

    2009-03-01

    Genetic algorithms (GAs) have been found to be effective in the domain of medical image segmentation, since the problem can often be mapped to one of search in a complex and multimodal landscape. The challenges in medical image segmentation arise due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. The resulting search space is therefore often noisy with a multitude of local optima. Not only does the genetic algorithmic framework prove to be effective in coming out of local optima, it also brings considerable flexibility into the segmentation procedure. In this paper, an attempt has been made to review the major applications of GAs to the domain of medical image segmentation.

  5. Deep Learning in Medical Image Analysis.

    PubMed

    Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

    2017-03-09

    This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the core of these advances is the ability to exploit hierarchical feature representations learned solely from data, instead of features designed by hand according to domain-specific knowledge. Deep learning is rapidly becoming the state of the art, leading to enhanced performance in various medical applications. We introduce the fundamentals of deep learning methods and review their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on. We conclude by discussing research issues and suggesting future directions for further improvement. Expected final online publication date for the Annual Review of Biomedical Engineering Volume 19 is June 4, 2017. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

  6. Image quality of flat-panel cone beam CT

    NASA Astrophysics Data System (ADS)

    Rose, Georg; Wiegert, Jens; Schaefer, Dirk; Fiedler, Klaus; Conrads, Norbert; Timmer, Jan; Rasche, Volker; Noordhoek, Niels; Klotz, Erhard; Koppe, Reiner

    2003-06-01

    We present results on 3D image quality in terms of spatial resolution (MTF) and low contrast detectability, obtained on a flat dynamic X-ray detector (FD) based cone-beam CT (CB-CT) setup. Experiments have been performed on a high precision bench-top system with rotating object table, fixed X-ray tube and 176 x 176 mm2 active detector area (Trixell Pixium 4800). Several objects, including CT performance-, MTF- and pelvis phantoms, have been scanned under various conditions, including a high dose setup in order to explore the 3D performance limits. Under these optimal conditions, the system is capable of resolving less than 1% (~10 HU) contrast in a water background. Within a pelvis phantom, even inserts of muscle and fat equivalent are clearly distinguishable. This also holds for fast acquisitions of up to 40 fps. Focusing on the spatial resolution, we obtain an almost isotropic three-dimensional resolution of up to 30 lp/cm at 10% modulation.

  7. Investigation of uncertainties in image registration of cone beam CT to CT on an image-guided radiotherapy system

    NASA Astrophysics Data System (ADS)

    Sykes, J. R.; Brettle, D. S.; Magee, D. R.; Thwaites, D. I.

    2009-12-01

    Methods of measuring uncertainties in rigid body image registration of fan beam computed tomography (FBCT) to cone beam CT (CBCT) have been developed for automatic image registration algorithms in a commercial image guidance system (Synergy, Elekta, UK). The relationships between image registration uncertainty and both imaging dose and image resolution have been investigated with an anthropomorphic skull phantom and further measurements performed with patient images of the head. A new metric of target registration error is proposed. The metric calculates the mean distance traversed by a set of equi-spaced points on the surface of a 5 cm sphere, centred at the isocentre when transformed by the residual error of registration. Studies aimed at giving practical guidance on the use of the Synergy automated image registration, including choice of algorithm and use of the Clipbox are reported. The chamfer-matching algorithm was found to be highly robust to the increased noise induced by low-dose acquisitions. This would allow the imaging dose to be reduced from the current clinical norm of 2 mGy to 0.2 mGy without a clinically significant loss of accuracy. A study of the effect of FBCT slice thickness/spacing and CBCT voxel size showed that 2.5 mm and 1 mm, respectively, gave acceptable image registration performance. Registration failures were highly infrequent if the misalignment was typical of normal clinical set-up errors and these were easily identified. The standard deviation of translational registration errors, measured with patient images, was 0.5 mm on the surface of a 5 cm sphere centred on the treatment centre. The chamfer algorithm is suitable for routine clinical use with minimal need for close inspection of image misalignment.

  8. Use of mobile devices for medical imaging.

    PubMed

    Hirschorn, David S; Choudhri, Asim F; Shih, George; Kim, Woojin

    2014-12-01

    Mobile devices have fundamentally changed personal computing, with many people forgoing the desktop and even laptop computer altogether in favor of a smaller, lighter, and cheaper device with a touch screen. Doctors and patients are beginning to expect medical images to be available on these devices for consultative viewing, if not actual diagnosis. However, this raises serious concerns with regard to the ability of existing mobile devices and networks to quickly and securely move these images. Medical images often come in large sets, which can bog down a network if not conveyed in an intelligent manner, and downloaded data on a mobile device are highly vulnerable to a breach of patient confidentiality should that device become lost or stolen. Some degree of regulation is needed to ensure that the software used to view these images allows all relevant medical information to be visible and manipulated in a clinically acceptable manner. There also needs to be a quality control mechanism to ensure that a device's display accurately conveys the image content without loss of contrast detail. Furthermore, not all mobile displays are appropriate for all types of images. The smaller displays of smart phones, for example, are not well suited for viewing entire chest radiographs, no matter how small and numerous the pixels of the display may be. All of these factors should be taken into account when deciding where, when, and how to use mobile devices for the display of medical images.

  9. Automatic landmark generation for deformable image registration evaluation for 4D CT images of lung

    NASA Astrophysics Data System (ADS)

    Vickress, J.; Battista, J.; Barnett, R.; Morgan, J.; Yartsev, S.

    2016-10-01

    Deformable image registration (DIR) has become a common tool in medical imaging across both diagnostic and treatment specialties, but the methods used offer varying levels of accuracy. Evaluation of DIR is commonly performed using manually selected landmarks, which is subjective, tedious and time consuming. We propose a semi-automated method that saves time and provides accuracy comparable to manual selection. Three landmarking methods including manual (with two independent observers), scale invariant feature transform (SIFT), and SIFT with manual editing (SIFT-M) were tested on 10 thoracic 4DCT image studies corresponding to the 0% and 50% phases of respiration. Results of each method were evaluated against a gold standard (GS) landmark set comparing both mean and proximal landmark displacements. The proximal method compares the local deformation magnitude between a test landmark pair and the closest GS pair. Statistical analysis was done using an intra class correlation (ICC) between test and GS displacement values. The creation time per landmark pair was 22, 34, 2.3, and 4.3 s for observers 1 and 2, SIFT, and SIFT-M methods respectively. Across 20 lungs from the 10 CT studies, the ICC values between the GS and observer 1 and 2, SIFT, and SIFT-M methods were 0.85, 0.85, 0.84, and 0.82 for mean lung deformation, and 0.97, 0.98, 0.91, and 0.96 for proximal landmark deformation, respectively. SIFT and SIFT-M methods have an accuracy that is comparable to manual methods when tested against a GS landmark set while saving 90% of the time. The number and distribution of landmarks significantly affected the analysis as manifested by the different results for mean deformation and proximal landmark deformation methods. Automatic landmark methods offer a promising alternative to manual landmarking, if the quantity, quality and distribution of landmarks can be optimized for the intended application.

  10. Deep convolutional networks for pancreas segmentation in CT imaging

    NASA Astrophysics Data System (ADS)

    Roth, Holger R.; Farag, Amal; Lu, Le; Turkbey, Evrim B.; Summers, Ronald M.

    2015-03-01

    Automatic organ segmentation is an important prerequisite for many computer-aided diagnosis systems. The high anatomical variability of organs in the abdomen, such as the pancreas, prevents many segmentation methods from achieving high accuracies when compared to state-of-the-art segmentation of organs like the liver, heart or kidneys. Recently, the availability of large annotated training sets and the accessibility of affordable parallel computing resources via GPUs have made it feasible for "deep learning" methods such as convolutional networks (ConvNets) to succeed in image classification tasks. These methods have the advantage that used classification features are trained directly from the imaging data. We present a fully-automated bottom-up method for pancreas segmentation in computed tomography (CT) images of the abdomen. The method is based on hierarchical coarse-to-fine classification of local image regions (superpixels). Superpixels are extracted from the abdominal region using Simple Linear Iterative Clustering (SLIC). An initial probability response map is generated, using patch-level confidences and a two-level cascade of random forest classifiers, from which superpixel regions with probabilities larger 0.5 are retained. These retained superpixels serve as a highly sensitive initial input of the pancreas and its surroundings to a ConvNet that samples a bounding box around each superpixel at different scales (and random non-rigid deformations at training time) in order to assign a more distinct probability of each superpixel region being pancreas or not. We evaluate our method on CT images of 82 patients (60 for training, 2 for validation, and 20 for testing). Using ConvNets we achieve maximum Dice scores of an average 68% +/- 10% (range, 43-80%) in testing. This shows promise for accurate pancreas segmentation, using a deep learning approach and compares favorably to state-of-the-art methods.

  11. An efficient neural network based method for medical image segmentation.

    PubMed

    Torbati, Nima; Ayatollahi, Ahmad; Kermani, Ali

    2014-01-01

    The aim of this research is to propose a new neural network based method for medical image segmentation. Firstly, a modified self-organizing map (SOM) network, named moving average SOM (MA-SOM), is utilized to segment medical images. After the initial segmentation stage, a merging process is designed to connect the objects of a joint cluster together. A two-dimensional (2D) discrete wavelet transform (DWT) is used to build the input feature space of the network. The experimental results show that MA-SOM is robust to noise and it determines the input image pattern properly. The segmentation results of breast ultrasound images (BUS) demonstrate that there is a significant correlation between the tumor region selected by a physician and the tumor region segmented by our proposed method. In addition, the proposed method segments X-ray computerized tomography (CT) and magnetic resonance (MR) head images much better than the incremental supervised neural network (ISNN) and SOM-based methods.

  12. Restricted surface matching: a new registration method for medical images

    NASA Astrophysics Data System (ADS)

    Gong, JianXing; Zamorano, Lucia J.; Jiang, Zhaowei; Nolte, Lutz P.; Diaz, Fernando

    1998-06-01

    Since its introduction to neurological surgery in the early 1980's, computer assisted surgery (CAS) with and without robotics navigation has been applied to several medical fields. The common issue all CAS systems is registration between two pre-operative 3D image modalities (for example, CT/MRI/PET et al) and the 3D image references of the patient in the operative room. In Wayne State University, a new way is introduced for medical image registration, which is different from traditional fiducial point registration and surface registration. We call it restricted surface matching (RSM). The method fast, convenient, accurate and robust. It combines the advantages from two registration methods mentioned before. Because of a penalty function introduced in its cost function, it is called `RSM'. The surface of a 3D image modality is pre-operatively extracted using segmentation techniques, and a distance map is created from such surface. The surface of another 3D reference is presented by a cloud of 3D points. At least three rough landmarks are used to restrict a registration not far away from global minimum. The local minimum issue is solved by use of a restriction for in the cost function and larger number of random starting points. The accuracy of matching is achieved by gradually releasing the restriction and limiting the influence of outliers. It only needs about half a minute to find the global minimum (for 256 X 256 X 56 images) in a SunSparc 10 station.

  13. Adapting content-based image retrieval techniques for the semantic annotation of medical images.

    PubMed

    Kumar, Ashnil; Dyer, Shane; Kim, Jinman; Li, Changyang; Leong, Philip H W; Fulham, Michael; Feng, Dagan

    2016-04-01

    The automatic annotation of medical images is a prerequisite for building comprehensive semantic archives that can be used to enhance evidence-based diagnosis, physician education, and biomedical research. Annotation also has important applications in the automatic generation of structured radiology reports. Much of the prior research work has focused on annotating images with properties such as the modality of the image, or the biological system or body region being imaged. However, many challenges remain for the annotation of high-level semantic content in medical images (e.g., presence of calcification, vessel obstruction, etc.) due to the difficulty in discovering relationships and associations between low-level image features and high-level semantic concepts. This difficulty is further compounded by the lack of labelled training data. In this paper, we present a method for the automatic semantic annotation of medical images that leverages techniques from content-based image retrieval (CBIR). CBIR is a well-established image search technology that uses quantifiable low-level image features to represent the high-level semantic content depicted in those images. Our method extends CBIR techniques to identify or retrieve a collection of labelled images that have similar low-level features and then uses this collection to determine the best high-level semantic annotations. We demonstrate our annotation method using retrieval via weighted nearest-neighbour retrieval and multi-class classification to show that our approach is viable regardless of the underlying retrieval strategy. We experimentally compared our method with several well-established baseline techniques (classification and regression) and showed that our method achieved the highest accuracy in the annotation of liver computed tomography (CT) images.

  14. High definition ultrasound imaging for battlefield medical applications

    SciTech Connect

    Kwok, K.S.; Morimoto, A.K.; Kozlowski, D.M.; Krumm, J.C.; Dickey, F.M.; Rogers, B; Walsh, N.

    1996-06-23

    A team has developed an improved resolution ultrasound system for low cost diagnostics. This paper describes the development of an ultrasound based imaging system capable of generating 3D images showing surface and subsurface tissue and bone structures. We include results of a comparative study between images obtained from X-Ray Computed Tomography (CT) and ultrasound. We found that the quality of ultrasound images compares favorably with those from CT. Volumetric and surface data extracted from these images were within 7% of the range between ultrasound and CT scans. We also include images of porcine abdominal scans from two different sets of animal trials.

  15. 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.

  16. A study on the change in image quality before and after an attenuation correction with the use of a CT image in a SPECT/CT scan

    NASA Astrophysics Data System (ADS)

    Park, Yong-Soon; Kim, Woo-Hyun; Shim, Dong-Oh; Kim, Ho-Sung; Chung, Woon-Kwan; Cho, Jae-Hwan

    2012-12-01

    This study compared the SPECT (single-photon emission computed tomography) images before and after applying an attenuation correction by using the CT (computed tomography) image in a SPECT/CT scan and examined depending of the change in image quality on the CT dose. A flangeless Esser PET (positron emission tomography) Phantom was used to evaluate the image quality for the Precedence 16 SPECT/CT system manufactured by Philips. The experimental method was to obtain a SPECT image and a CT image of a flangeless Esser PET Phantom to acquire an attenuation-corrected SPECT image. A ROI (region of interest) was then set up at a hot spot of the acquired image to measure the SNR (signal to noise ratio) and the FWHM (full width at half maximum) and to compare the image quality with that of an unattenuation-corrected SPECT image. To evaluate the quality of a SPECT image, we set the ROI as a cylinder diameter (25, 16, 12, and 8 mm) and the BKG (background) radioactivity of the phantom images was obtained when each CT condition was changed. Subsequently, the counts were compared to measure the SNR. The FWHM of the smallest cylinder (8 mm) was measured to compare the image quality. A comparison of the SPECT images with and without attenuation correction revealed 5.01-fold, 4.77 fold, 4.43-fold, 4.38-fold, and 5.13-fold differences in SNR for the 25-mm cylinder, 16-mm cylinder, 12-mm cylinder, 8-mm cylinder, and BKG, respectively. In the phantom image obtained when the CT dose was changed, the FWHM of the 8-mm cylinder showed almost no difference under each condition regardless of the changes in kVp and mAs.

  17. Perspectives of medical X-ray imaging

    NASA Astrophysics Data System (ADS)

    Freudenberger, J.; Hell, E.; Knüpfer, W.

    2001-06-01

    While X-ray image intensifiers (XII), storage phosphor screens and film-screen systems are still the work horses of medical imaging, large flat panel solid state detectors using either scintillators and amorphous silicon photo diode arrays (FD-Si), or direct X-ray conversion in amorphous selenium are reaching maturity. The main advantage with respect to image quality and low patient dose of the XII and FD-Si systems is caused by the rise of the Detector Quantum Efficiency originating from the application of thick needle-structured phosphor X-ray absorbers. With the detectors getting closer to an optimal state, further progress in medical X-ray imaging requires an improvement of the usable source characteristics. The development of clinical monochromatic X-ray sources of high power would not only allow an improved contrast-to-dose ratio by allowing smaller average photon energies in applications but would also lead to new imaging techniques.

  18. Deformable Medical Image Registration: A Survey

    PubMed Central

    Sotiras, Aristeidis; Davatzikos, Christos; Paragios, Nikos

    2013-01-01

    Deformable image registration is a fundamental task in medical image processing. Among its most important applications, one may cite: i) multi-modality fusion, where information acquired by different imaging devices or protocols is fused to facilitate diagnosis and treatment planning; ii) longitudinal studies, where temporal structural or anatomical changes are investigated; and iii) population modeling and statistical atlases used to study normal anatomical variability. In this paper, we attempt to give an overview of deformable registration methods, putting emphasis on the most recent advances in the domain. Additional emphasis has been given to techniques applied to medical images. In order to study image registration methods in depth, their main components are identified and studied independently. The most recent techniques are presented in a systematic fashion. The contribution of this paper is to provide an extensive account of registration techniques in a systematic manner. PMID:23739795

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

    SciTech Connect

    Wen, N; Glide-Hurst, C; Zhong, H; Chin, K; Kumarasiri, A; Liu, C; Liu, M; Siddiqui, S

    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, seminal 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.

  20. Smart spotting of pulmonary TB cavities using CT images.

    PubMed

    Swanly, V Ezhil; Selvam, L; Kumar, P Mohan; Renjith, J Arokia; Arunachalam, M; Shunmuganathan, K L

    2013-01-01

    One third of the world's population is thought to have been infected with mycobacterium tuberculosis (TB) with new infection occurring at a rate of about one per second. TB typically attacks the lungs. Indication of cavities in upper lobes of lungs shows the high infection. Traditionally, it has been detected manually by physicians. But the automatic technique proposed in this paper focuses on accurate detection of disease by computed tomography (CT) using computer-aided detection (CAD) system. The various steps of the detection process include the following: (i) image preprocessing, which is done by techniques such as resizing, masking, and Gaussian smoothening, (ii) image egmentation that is implemented by using mean-shift model and gradient vector flow (GVF) model, (iii) feature extraction that can be achieved by Gradient inverse coefficient of variation and circularity measure, and (iv) classification using Bayesian classifier. Experimental results show that its perfection of detecting cavities is very accurate in low false positive rate (FPR).

  1. Nanotechnology-supported THz medical imaging

    PubMed Central

    Stylianou, Andreas; Talias, Michael A

    2013-01-01

    Over the last few decades, the achievements and progress in the field of medical imaging have dramatically enhanced the early detection and treatment of many pathological conditions. The development of new imaging modalities, especially non-ionising ones, which will improve prognosis, is of crucial importance. A number of novel imaging modalities have been developed but they are still in the initial stages of development and serious drawbacks obstruct them from offering their benefits to the medical field. In the 21 st century, it is believed that nanotechnology will highly influence our everyday life and dramatically change the world of medicine, including medical imaging. Here we discuss how nanotechnology, which is still in its infancy, can improve Terahertz (THz) imaging, an emerging imaging modality, and how it may find its way into real clinical applications. THz imaging is characterised by the use of non-ionising radiation and although it has the potential to be used in many biomedical fields, it remains in the field of basic research. An extensive review of the recent available literature shows how the current state of this emerging imaging modality can be transformed by nanotechnology. Innovative scientific concepts that use nanotechnology-based techniques to overcome some of the limitations of the use of THz imaging are discussed. We review a number of drawbacks, such as a low contrast mechanism, poor source performance and bulky THz systems, which characterise present THz medical imaging and suggest how they can be overcome through nanotechnology. Better resolution and higher detection sensitivity can also be achieved using nanotechnology techniques. PMID:24555052

  2. Medical image segmentation on GPUs--a comprehensive review.

    PubMed

    Smistad, Erik; Falch, Thomas L; Bozorgi, Mohammadmehdi; Elster, Anne C; Lindseth, Frank

    2015-02-01

    Segmentation of anatomical structures, from modalities like computed tomography (CT), magnetic resonance imaging (MRI) and ultrasound, is a key enabling technology for medical applications such as diagnostics, planning and guidance. More efficient implementations are necessary, as most segmentation methods are computationally expensive, and the amount of medical imaging data is growing. The increased programmability of graphic processing units (GPUs) in recent years have enabled their use in several areas. GPUs can solve large data parallel problems at a higher speed than the traditional CPU, while being more affordable and energy efficient than distributed systems. Furthermore, using a GPU enables concurrent visualization and interactive segmentation, where the user can help the algorithm to achieve a satisfactory result. This review investigates the use of GPUs to accelerate medical image segmentation methods. A set of criteria for efficient use of GPUs are defined and each segmentation method is rated accordingly. In addition, references to relevant GPU implementations and insight into GPU optimization are provided and discussed. The review concludes that most segmentation methods may benefit from GPU processing due to the methods' data parallel structure and high thread count. However, factors such as synchronization, branch divergence and memory usage can limit the speedup.

  3. Multiscale Medical Image Fusion in Wavelet Domain

    PubMed Central

    Khare, Ashish

    2013-01-01

    Wavelet transforms have emerged as a powerful tool in image fusion. However, the study and analysis of medical image fusion is still a challenging area of research. Therefore, in this paper, we propose a multiscale fusion of multimodal medical images in wavelet domain. Fusion of medical images has been performed at multiple scales varying from minimum to maximum level using maximum selection rule which provides more flexibility and choice to select the relevant fused images. The experimental analysis of the proposed method has been performed with several sets of medical images. Fusion results have been evaluated subjectively and objectively with existing state-of-the-art fusion methods which include several pyramid- and wavelet-transform-based fusion methods and principal component analysis (PCA) fusion method. The comparative analysis of the fusion results has been performed with edge strength (Q), mutual information (MI), entropy (E), standard deviation (SD), blind structural similarity index metric (BSSIM), spatial frequency (SF), and average gradient (AG) metrics. The combined subjective and objective evaluations of the proposed fusion method at multiple scales showed the effectiveness and goodness of the proposed approach. PMID:24453868

  4. Diagnostic accuracy at several reduced radiation dose levels for CT imaging in the diagnosis of appendicitis

    NASA Astrophysics Data System (ADS)

    Zhang, Di; Khatonabadi, Maryam; Kim, Hyun; Jude, Matilda; Zaragoza, Edward; Lee, Margaret; Patel, Maitraya; Poon, Cheryce; Douek, Michael; Andrews-Tang, Denise; Doepke, Laura; McNitt-Gray, Shawn; Cagnon, Chris; DeMarco, John; McNitt-Gray, Michael

    2012-03-01

    Purpose: While several studies have investigated the tradeoffs between radiation dose and image quality (noise) in CT imaging, the purpose of this study was to take this analysis a step further by investigating the tradeoffs between patient radiation dose (including organ dose) and diagnostic accuracy in diagnosis of appendicitis using CT. Methods: This study was IRB approved and utilized data from 20 patients who underwent clinical CT exams for indications of appendicitis. Medical record review established true diagnosis of appendicitis, with 10 positives and 10 negatives. A validated software tool used raw projection data from each scan to create simulated images at lower dose levels (70%, 50%, 30%, 20% of original). An observer study was performed with 6 radiologists reviewing each case at each dose level in random order over several sessions. Readers assessed image quality and provided confidence in their diagnosis of appendicitis, each on a 5 point scale. Liver doses at each case and each dose level were estimated using Monte Carlo simulation based methods. Results: Overall diagnostic accuracy varies across dose levels: 92%, 93%, 91%, 90% and 90% across the 100%, 70%, 50%, 30% and 20% dose levels respectively. And it is 93%, 95%, 88%, 90% and 90% across the 13.5-22mGy, 9.6-13.5mGy, 6.4-9.6mGy, 4-6.4mGy, and 2-4mGy liver dose ranges respectively. Only 4 out of 600 observations were rated "unacceptable" for image quality. Conclusion: The results from this pilot study indicate that the diagnostic accuracy does not change dramatically even at significantly reduced radiation dose.

  5. Radiation-Based Medical Imaging Techniques: An Overview

    NASA Astrophysics Data System (ADS)

    Prior, John O.; Lecoq, Paul

    This chapter will present an overview of two radiation-based medical imaging techniques using radiopharmaceuticals used in nuclear medicine/molecular imaging, namely, single-photon emission computed tomography (SPECT) and positron emission tomography (PET). The relative merits in terms of radiation sensitivity and image resolution of SPECT and PET will be compared to the main conventional radiologic modalities that are computed tomography (CT) and magnetic resonance (MR) imaging. Differences in terms of temporal resolution will also be outlined, as well as the other similarities and dissimilarities of these two techniques, including their latest and upcoming multimodality combination. The main clinical applications are briefly described and examples of specific SPECT and PET radiopharmaceuticals are listed. SPECT and PET imaging will be then further detailed in the two subsequent chapters describing in greater depth the basics and future trends of each technique (see Chaps. 37, "SPECT Imaging: Basics and New Trends" 10.1007/978-3-642-13271-1_37 and 38, "PET Imaging: Basics and New Trends" 10.1007/978-3-642-13271-1_38.

  6. Radial intensity projection for lumen: application to CT angiographic imaging

    NASA Astrophysics Data System (ADS)

    Kokubun, Hiroto; Miyazaki, Osamu; Hayashi, Hiromitsu

    2006-03-01

    For the diagnosis of lumen, such as plaque in the coronary and polyp in the colon, it is important to create the cross sectional image of tubular organ on the basis of luminal centerline (i.e., Curved Planar Reformation: CPR). However, since each CPR image has the only limited angle information, it may overlook objects of diagnostic importance. To overcome this limitation and improve diagnostic accuracy we have developed a method called Radial Intensity Projection for lumen (RIP) to create an image based on luminal centerline that integrates all directional information. RIP is executed as follows. At first image processing is performed on array of pixel in the orthogonal direction to a luminal centerline. Secondly, this image processing is performed repeatedly in the angle direction along a luminal centerline. Finally, RIP image, which incorporates all directional information based on luminal centerline, is created. In addition to developing the RIP method for the diagnosis of soft plaque, which is considered as one of the main causes of myocardial infarction, we have also developed the profile step imaging method (PSI). This is an algorithm for visualizing a level gradient point in the radial direction, paying attention to the fact that the gradient approaches zero at the region of soft plaque. We applied RIP method to the clinical image data of a coronary angiography, which has been scanned with the multi slice CT scanner. Using RIP method, it is possible to check the existence of calcified plaque present in the surrounding of a vessel wall without changing the view angle. We have also applied PSI method to the clinical image of a coronary angiography with a soft plaque. The PSI image overlaid on RIP image enables us to verify the high possibility of existing soft plaque. Moreover, the perspectively mapped RIP image to a half pipe object allows us to grasp the orientation of plaque more easily. RIP method is also effective for extended organs, such as peripheral

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

    SciTech Connect

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

    2006-12-15

    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 CTDI{sub W} 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.

  8. Quantitative imaging features: extension of the oncology medical image database

    NASA Astrophysics Data System (ADS)

    Patel, M. N.; Looney, P. T.; Young, K. C.; Halling-Brown, M. D.

    2015-03-01

    Radiological imaging is fundamental within the healthcare industry and has become routinely adopted for diagnosis, disease monitoring and treatment planning. With the advent of digital imaging modalities and the rapid growth in both diagnostic and therapeutic imaging, the ability to be able to harness this large influx of data is of paramount importance. The Oncology Medical Image Database (OMI-DB) was created to provide a centralized, fully annotated dataset for research. The database contains both processed and unprocessed images, associated data, and annotations and where applicable expert determined ground truths describing features of interest. Medical imaging provides the ability to detect and localize many changes that are important to determine whether a disease is present or a therapy is effective by depicting alterations in anatomic, physiologic, biochemical or molecular processes. Quantitative imaging features are sensitive, specific, accurate and reproducible imaging measures of these changes. Here, we describe an extension to the OMI-DB whereby a range of imaging features and descriptors are pre-calculated using a high throughput approach. The ability to calculate multiple imaging features and data from the acquired images would be valuable and facilitate further research applications investigating detection, prognosis, and classification. The resultant data store contains more than 10 million quantitative features as well as features derived from CAD predictions. Theses data can be used to build predictive models to aid image classification, treatment response assessment as well as to identify prognostic imaging biomarkers.

  9. Application of the optically stimulated luminescence (OSL) technique for mouse dosimetry in micro-CT imaging

    SciTech Connect

    Vrigneaud, Jean-Marc; Courteau, Alan; Oudot, Alexandra; Collin, Bertrand; Ranouil, Julien; Morgand, Loïc; Raguin, Olivier; Walker, Paul; Brunotte, François

    2013-12-15

    Purpose: Micro-CT is considered to be a powerful tool to investigate various models of disease on anesthetized animals. In longitudinal studies, the radiation dose delivered by the micro-CT to the same animal is a major concern as it could potentially induce spurious effects in experimental results. Optically stimulated luminescence dosimeters (OSLDs) are a relatively new kind of detector used in radiation dosimetry for medical applications. The aim of this work was to assess the dose delivered by the CT component of a micro-SPECT (single-photon emission computed tomography)/CT camera during a typical whole-body mouse study, using commercially available OSLDs based on Al{sub 2}O{sub 3}:C crystals.Methods: CTDI (computed tomography dose index) was measured in micro-CT with a properly calibrated pencil ionization chamber using a rat-like phantom (60 mm in diameter) and a mouse-like phantom (30 mm in diameter). OSLDs were checked for reproducibility and linearity in the range of doses delivered by the micro-CT. Dose measurements obtained with OSLDs were compared to those of the ionization chamber to correct for the radiation quality dependence of OSLDs in the low-kV range. Doses to tissue were then investigated in phantoms and cadavers. A 30 mm diameter phantom, specifically designed to insert OSLDs, was used to assess radiation dose over a typical whole-body mouse imaging study. Eighteen healthy female BALB/c mice weighing 27.1 ± 0.8 g (1 SD) were euthanized for small animal measurements. OLSDs were placed externally or implanted internally in nine different locations by an experienced animal technician. Five commonly used micro-CT protocols were investigated.Results: CTDI measurements were between 78.0 ± 2.1 and 110.7 ± 3.0 mGy for the rat-like phantom and between 169.3 ± 4.6 and 203.6 ± 5.5 mGy for the mouse-like phantom. On average, the displayed CTDI at the operator console was underestimated by 1.19 for the rat-like phantom and 2.36 for the mouse

  10. Task-based optimization of image reconstruction in breast CT

    NASA Astrophysics Data System (ADS)

    Sanchez, Adrian A.; Sidky, Emil Y.; Pan, Xiaochuan

    2014-03-01

    We demonstrate a task-based assessment of image quality in dedicated breast CT in order to optimize the number of projection views acquired. The methodology we employ is based on the Hotelling Observer (HO) and its associated metrics. We consider two tasks: the Rayleigh task of discerning between two resolvable objects and a single larger object, and the signal detection task of classifying an image as belonging to either a signalpresent or signal-absent hypothesis. HO SNR values are computed for 50, 100, 200, 500, and 1000 projection view images, with the total imaging radiation dose held constant. We use the conventional fan-beam FBP algorithm and investigate the effect of varying the width of a Hanning window used in the reconstruction, since this affects both the noise properties of the image and the under-sampling artifacts which can arise in the case of sparse-view acquisitions. Our results demonstrate that fewer projection views should be used in order to increase HO performance, which in this case constitutes an upper-bound on human observer performance. However, the impact on HO SNR of using fewer projection views, each with a higher dose, is not as significant as the impact of employing regularization in the FBP reconstruction through a Hanning filter.

  11. Metal artifact reduction and image quality evaluation of lumbar spine CT images using metal sinogram segmentation.

    PubMed

    Kaewlek, Titipong; Koolpiruck, Diew; Thongvigitmanee, Saowapak; Mongkolsuk, Manus; Thammakittiphan, Sastrawut; Tritrakarn, Siri-on; Chiewvit, Pipat

    2015-01-01

    Metal artifacts often appear in the images of computed tomography (CT) imaging. In the case of lumbar spine CT images, artifacts disturb the images of critical organs. These artifacts can affect the diagnosis, treatment, and follow up care of the patient. One approach to metal artifact reduction is the sinogram completion method. A mixed-variable thresholding (MixVT) technique to identify the suitable metal sinogram is proposed. This technique consists of four steps: 1) identify the metal objects in the image by using k-mean clustering with the soft cluster assignment, 2) transform the image by separating it into two sinograms, one of which is the sinogram of the metal object, with the surrounding tissue shown in the second sinogram. The boundary of the metal sinogram is then found by the MixVT technique, 3) estimate the new value of the missing data in the metal sinogram by linear interpolation from the surrounding tissue sinogram, 4) reconstruct a modified sinogram by using filtered back-projection and complete the image by adding back the image of the metal object into the reconstructed image to form the complete image. The quantitative and clinical image quality evaluation of our proposed technique demonstrated a significant improvement in image clarity and detail, which enhances the effectiveness of diagnosis and treatment.

  12. CT Image Contrast of High-Z Elements: Phantom Imaging Studies and Clinical Implications

    PubMed Central

    Colborn, Robert E.; Edic, Peter M.; Lambert, Jack W.; Torres, Andrew S.; Bonitatibus, Peter J.; Yeh, Benjamin M.

    2016-01-01

    Purpose To quantify the computed tomographic (CT) image contrast produced by potentially useful contrast material elements in clinically relevant imaging conditions. Materials and Methods Equal mass concentrations (grams of active element per milliliter of solution) of seven radiodense elements, including iodine, barium, gadolinium, tantalum, ytterbium, gold, and bismuth, were formulated as compounds in aqueous solutions. The compounds were chosen such that the active element dominated the x-ray attenuation of the solution. The solutions were imaged within a modified 32-cm CT dose index phantom at 80, 100, 120, and 140 kVp at CT. To simulate larger body sizes, 0.2-, 0.5-, and 1.0-mm-thick copper filters were applied. CT image contrast was measured and corrected for measured concentrations and presence of chlorine in some compounds. Results Each element tested provided higher image contrast than iodine at some tube potential levels. Over the range of tube potentials that are clinically practical for average-sized and larger adults—that is, 100 kVp and higher—barium, gadolinium, ytterbium, and tantalum provided consistently increased image contrast compared with iodine, respectively demonstrating 39%, 56%, 34%, and 24% increases at 100 kVp; 39%, 66%, 53%, and 46% increases at 120 kVp; and 40%, 72%, 65%, and 60% increases at 140 kVp, with no added x-ray filter. Conclusion The consistently high image contrast produced with 100–140 kVp by tantalum compared with bismuth and iodine at equal mass concentration suggests that tantalum could potentially be favorable for use as a clinical CT contrast agent. © RSNA, 2015 Online supplemental material is available for this article. PMID:26356064

  13. 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.

  14. Realistic simulation of reduced-dose CT with noise modeling and sinogram synthesis using DICOM CT images

    SciTech Connect

    Won Kim, Chang; Kim, Jong Hyo

    2014-01-15

    Purpose: Reducing the patient dose while maintaining the diagnostic image quality during CT exams is the subject of a growing number of studies, in which simulations of reduced-dose CT with patient data have been used as an effective technique when exploring the potential of various dose reduction techniques. Difficulties in accessing raw sinogram data, however, have restricted the use of this technique to a limited number of institutions. Here, we present a novel reduced-dose CT simulation technique which provides realistic low-dose images without the requirement of raw sinogram data. Methods: Two key characteristics of CT systems, the noise equivalent quanta (NEQ) and the algorithmic modulation transfer function (MTF), were measured for various combinations of object attenuation and tube currents by analyzing the noise power spectrum (NPS) of CT images obtained with a set of phantoms. Those measurements were used to develop a comprehensive CT noise model covering the reduced x-ray photon flux, object attenuation, system noise, and bow-tie filter, which was then employed to generate a simulated noise sinogram for the reduced-dose condition with the use of a synthetic sinogram generated from a reference CT image. The simulated noise sinogram was filtered with the algorithmic MTF and back-projected to create a noise CT image, which was then added to the reference CT image, finally providing a simulated reduced-dose CT image. The simulation performance was evaluated in terms of the degree of NPS similarity, the noise magnitude, the bow-tie filter effect, and the streak noise pattern at photon starvation sites with the set of phantom images. Results: The simulation results showed good agreement with actual low-dose CT images in terms of their visual appearance and in a quantitative evaluation test. The magnitude and shape of the NPS curves of the simulated low-dose images agreed well with those of real low-dose images, showing discrepancies of less than +/−3.2% in

  15. A hybrid technique for medical image segmentation.

    PubMed

    Nyma, Alamgir; Kang, Myeongsu; Kwon, Yung-Keun; Kim, Cheol-Hong; Kim, Jong-Myon

    2012-01-01

    Medical image segmentation is an essential and challenging aspect in computer-aided diagnosis and also in pattern recognition research. This paper proposes a hybrid method for magnetic resonance (MR) image segmentation. We first remove impulsive noise inherent in MR images by utilizing a vector median filter. Subsequently, Otsu thresholding is used as an initial coarse segmentation method that finds the homogeneous regions of the input image. Finally, an enhanced suppressed fuzzy c-means is used to partition brain MR images into multiple segments, which employs an optimal suppression factor for the perfect clustering in the given data set. To evaluate the robustness of the proposed approach in noisy environment, we add different types of noise and different amount of noise to T1-weighted brain MR images. Experimental results show that the proposed algorithm outperforms other FCM based algorithms in terms of segmentation accuracy for both noise-free and noise-inserted MR images.

  16. CT imaging of the internal human ear: Test of a high resolution scanner

    NASA Astrophysics Data System (ADS)

    Bettuzzi, M.; Brancaccio, R.; Morigi, M. P.; Gallo, A.; Strolin, S.; Casali, F.; Lamanna, Ernesto; Ariù, Marilù

    2011-08-01

    During the course of 2009, in the framework of a project supported by the National Institute of Nuclear Physics, a number of tests were carried out at the Department of Physics of the University of Bologna in order to achieve a good quality CT scan of the internal human ear. The work was carried out in collaboration with the local “S. Orsola” Hospital in Bologna and a company (CEFLA) already involved in the production and commercialization of a CT scanner dedicated to dentistry. A laboratory scanner with a simple concept detector (CCD camera-lens-mirror-scintillator) was used to see to what extent it was possible to enhance the quality of a conventional CT scanner when examining the internal human ear. To test the system, some conventional measurements were made, such as the spatial resolution calculation with the MTF and dynamic range evaluation. Different scintillators were compared to select the most suitable for the purpose. With 0.5 mm thick structured cesium iodide and a field of view of 120×120 mm2, a spatial resolution of 6.5l p/mm at 5% MTF was obtained. The CT of a pair of human head phantoms was performed at an energy of 120 kVp. The first phantom was a rough representation of the human head shape, with soft tissue made of coarse slabs of Lucite. Some inserts, like small aluminum cylinders and cubes, with 1 mm diameter drilled holes, were used to simulate the channels that one finds inside the human inner ear. The second phantom is a plastic PVC fused head with a real human cranium inside. The bones in the cranium are well conserved and the inner ear features, such as the cochlea and semicircular channels, are clearly detectable. After a number of CT tests we obtained good results as far as structural representation and channel detection are concerned. Some images of the 3D rendering of the CT volume are shown below. The doctors of the local hospital who followed our experimentation expressed their satisfaction. The CT was compared to a virtual

  17. Nanoengineered multimodal contrast agent for medical image guidance

    NASA Astrophysics Data System (ADS)

    Perkins, Gregory J.; Zheng, Jinzi; Brock, Kristy; Allen, Christine; Jaffray, David A.

    2005-04-01

    Multimodality imaging has gained momentum in radiation therapy planning and image-guided treatment delivery. Specifically, computed tomography (CT) and magnetic resonance (MR) imaging are two complementary imaging modalities often utilized in radiation therapy for visualization of anatomical structures for tumour delineation and accurate registration of image data sets for volumetric dose calculation. The development of a multimodal contrast agent for CT and MR with prolonged in vivo residence time would provide long-lasting spatial and temporal correspondence of the anatomical features of interest, and therefore facilitate multimodal image registration, treatment planning and delivery. The multimodal contrast agent investigated consists of nano-sized stealth liposomes encapsulating conventional iodine and gadolinium-based contrast agents. The average loading achieved was 33.5 +/- 7.1 mg/mL of iodine for iohexol and 9.8 +/- 2.0 mg/mL of gadolinium for gadoteridol. The average liposome diameter was 46.2 +/- 13.5 nm. The system was found to be stable in physiological buffer over a 15-day period, releasing 11.9 +/- 1.1% and 11.2 +/- 0.9% of the total amounts of iohexol and gadoteridol loaded, respectively. 200 minutes following in vivo administration, the contrast agent maintained a relative contrast enhancement of 81.4 +/- 13.05 differential Hounsfield units (ΔHU) in CT (40% decrease from the peak signal value achieved 3 minutes post-injection) and 731.9 +/- 144.2 differential signal intensity (ΔSI) in MR (46% decrease from the peak signal value achieved 3 minutes post-injection) in the blood (aorta), a relative contrast enhancement of 38.0 +/- 5.1 ΔHU (42% decrease from the peak signal value achieved 3 minutes post-injection) and 178.6 +/- 41.4 ΔSI (62% decrease from the peak signal value achieved 3 minutes post-injection) in the liver (parenchyma), a relative contrast enhancement of 9.1 +/- 1.7 ΔHU (94% decrease from the peak signal value achieved 3 minutes

  18. Medical image registration using fuzzy theory.

    PubMed

    Pan, Meisen; Tang, Jingtian; Xiong, Qi

    2012-01-01

    Mutual information (MI)-based registration, which uses MI as the similarity measure, is a representative method in medical image registration. It has an excellent robustness and accuracy, but with the disadvantages of a large amount of calculation and a long processing time. In this paper, by computing the medical image moments, the centroid is acquired. By applying fuzzy c-means clustering, the coordinates of the medical image are divided into two clusters to fit a straight line, and the rotation angles of the reference and floating images are computed, respectively. Thereby, the initial values for registering the images are determined. When searching the optimal geometric transformation parameters, we put forward the two new concepts of fuzzy distance and fuzzy signal-to-noise ratio (FSNR), and we select FSNR as the similarity measure between the reference and floating images. In the experiments, the Simplex method is chosen as multi-parameter optimisation. The experimental results show that this proposed method has a simple implementation, a low computational cost, a fast registration and good registration accuracy. Moreover, it can effectively avoid trapping into the local optima. It is adapted to both mono-modality and multi-modality image registrations.

  19. CT image construction of a totally deflated lung using deformable model extrapolation

    SciTech Connect

    Sadeghi Naini, Ali; Pierce, Greg; Lee, Ting-Yim; and others

    2011-02-15

    Purpose: A novel technique is proposed to construct CT image of a totally deflated lung from a free-breathing 4D-CT image sequence acquired preoperatively. Such a constructed CT image is very useful in performing tumor ablative procedures such as lung brachytherapy. Tumor ablative procedures are frequently performed while the lung is totally deflated. Deflating the lung during such procedures renders preoperative images ineffective for targeting the tumor. Furthermore, the problem cannot be solved using intraoperative ultrasound (U.S.) images because U.S. images are very sensitive to small residual amount of air remaining in the deflated lung. One possible solution to address these issues is to register high quality preoperative CT images of the deflated lung with their corresponding low quality intraoperative U.S. images. However, given that such preoperative images correspond to an inflated lung, such CT images need to be processed to construct CT images pertaining to the lung's deflated state. Methods: To obtain the CT images of deflated lung, we present a novel image construction technique using extrapolated deformable registration to predict the deformation the lung undergoes during full deflation. The proposed construction technique involves estimating the lung's air volume in each preoperative image automatically in order to track the respiration phase of each 4D-CT image throughout a respiratory cycle; i.e., the technique does not need any external marker to form a respiratory signal in the process of curve fitting and extrapolation. The extrapolated deformation field is then applied on a preoperative reference image in order to construct the totally deflated lung's CT image. The technique was evaluated experimentally using ex vivo porcine lung. Results: The ex vivo lung experiments led to very encouraging results. In comparison with the CT image of the deflated lung we acquired for the purpose of validation, the constructed CT image was very similar. The

  20. 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

  1. 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.

  2. 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..

  3. Concurrent Diffuse Pyelonephritis and Prostatitis: Discordant Findings on Sequential FDG PET/CT and 67Ga SPECT/CT Imaging.

    PubMed

    Lucaj, Robert; Achong, Dwight M

    2017-01-01

    A 45-year-old man underwent FDG PET/CT for initial imaging evaluation of recurrent Escherichia coli urinary tract infections, which demonstrated no significant FDG uptake in either kidney and subtle FDG uptake in the right prostate lobe. Subsequent Ga SPECT/CT demonstrated abnormal intense gallium uptake throughout the right kidney and entire prostate gland, clearly discordant with PET/CT findings and consistent with unexpected concurrent pyelonephritis and prostatitis. Although FDG has effectively replaced Ga in everyday clinical practice, the current case serves as a reminder that there is still a role for Ga in the evaluation of genitourinary infections.

  4. US-CT 3D dual imaging by mutual display of the same sections for depicting minor changes in hepatocellular carcinoma.

    PubMed

    Fukuda, Hiroyuki; Ito, Ryu; Ohto, Masao; Sakamoto, Akio; Otsuka, Masayuki; Togawa, Akira; Miyazaki, Masaru; Yamagata, Hitoshi

    2012-09-01

    The purpose of this study was to evaluate the usefulness of ultrasound-computed tomography (US-CT) 3D dual imaging for the detection of small extranodular growths of hepatocellular carcinoma (HCC). The clinical and pathological profiles of 10 patients with single nodular type HCC with extranodular growth (extranodular growth) who underwent a hepatectomy were evaluated using two-dimensional (2D) ultrasonography (US), three-dimensional (3D) US, 3D computed tomography (CT) and 3D US-CT dual images. Raw 3D data was converted to DICOM (Digital Imaging and Communication in Medicine) data using Echo to CT (Toshiba Medical Systems Corp., Tokyo, Japan), and the 3D DICOM data was directly transferred to the image analysis system (ZioM900, ZIOSOFT Inc., Tokyo, Japan). By inputting the angle number (x, y, z) of the 3D CT volume data into the ZioM900, multiplanar reconstruction (MPR) images of the 3D CT data were displayed in a manner such that they resembled the conventional US images. Eleven extranodular growths were detected pathologically in 10 cases. 2D US was capable of depicting only 2 of the 11 extranodular growths. 3D CT was capable of depicting 4 of the 11 extranodular growths. On the other hand, 3D US was capable of depicting 10 of the 11 extranodular growths, and 3D US-CT dual images, which enable the dual analysis of the CT and US planes, revealed all 11 extranodular growths. In conclusion, US-CT 3D dual imaging may be useful for the detection of small extranodular growths.

  5. Iodine contrast cone beam CT imaging of breast cancer

    NASA Astrophysics Data System (ADS)

    Partain, Larry; Prionas, Stavros; Seppi, Edward; Virshup, Gary; Roos, Gerhard; Sutherland, Robert; Boone, John

    2007-03-01

    An iodine contrast agent, in conjunction with an X-ray cone beam CT imaging system, was used to clearly image three, biopsy verified, cancer lesions in two patients. The lesions were approximately in the 10 mm to 6 mm diameter range. Additional regions were also enhanced with approximate dimensions down to 1 mm or less in diameter. A flat panel detector, with 194 μm pixels in 2 x 2 binning mode, was used to obtain 500 projection images at 30 fps with an 80 kVp X-ray system operating at 112 mAs, for an 8-9 mGy dose - equivalent to two view mammography for these women. The patients were positioned prone, while the gantry rotated in the horizontal plane around the uncompressed, pendant breasts. This gantry rotated 360 degrees during the patient's 16.6 sec breath hold. A volume of 100 cc of 320 mg/ml iodine-contrast was power injected at 4 cc/sec, via catheter into the arm vein of the patient. The resulting 512 x 512 x 300 cone beam CT data set of Feldkamp reconstructed ~(0.3 mm) 3 voxels were analyzed. An interval of voxel contrast values, characteristic of the regions with iodine contrast enhancement, were used with surface rendering to clearly identify up to a total of 13 highlighted volumes. This included the three largest lesions, that were previously biopsied and confirmed to be malignant. The other ten highlighted regions, of smaller diameters, are likely areas of increased contrast trapping unrelated to cancer angiogenesis. However the technique itself is capable of resolving lesions that small.

  6. Perfusion measurements by micro-CT using prior image constrained compressed sensing (PICCS): initial phantom results.

    PubMed

    Nett, Brian E; Brauweiler, Robert; Kalender, Willi; Rowley, Howard; Chen, Guang-Hong

    2010-04-21

    Micro-CT scanning has become an accepted standard for anatomical imaging in small animal disease and genome mutation models. Concurrently, perfusion imaging via tracking contrast dynamics after injection of an iodinated contrast agent is a well-established tool for clinical CT scanners. However, perfusion imaging is not yet commercially available on the micro-CT platform due to limitations in both radiation dose and temporal resolution. Recent hardware developments in micro-CT scanners enable continuous imaging of a given volume through the use of a slip-ring gantry. Now that dynamic CT imaging is feasible, data may be acquired to measure tissue perfusion using a micro-CT scanner (CT Imaging, Erlangen, Germany). However, rapid imaging using micro-CT scanners leads to high image noise in individual time frames. Using the standard filtered backprojection (FBP) image reconstruction, images are prohibitively noisy for calculation of voxel-by-voxel perfusion maps. In this study, we apply prior image constrained compressed sensing (PICCS) to reconstruct images with significantly lower noise variance. In perfusion phantom experiments performed on a micro-CT scanner, the PICCS reconstruction enabled a reduction to 1/16 of the noise variance of standard FBP reconstruction, without compromising the spatial or temporal resolution. This enables a significant increase in dose efficiency, and thus, significantly less exposure time is needed to acquire images amenable to perfusion processing. This reduction in required irradiation time enables voxel-by-voxel perfusion maps to be generated on micro-CT scanners. Sample perfusion maps using a deconvolution-based perfusion analysis are included to demonstrate the improvement in image quality using the PICCS algorithm.

  7. SU-E-I-73: Clinical Evaluation of CT Image Reconstructed Using Interior Tomography

    SciTech Connect

    Zhang, J; Ge, G; Winkler, M; Cong, W; Wang, G

    2014-06-01

    Purpose: Radiation dose reduction has been a long standing challenge in CT imaging of obese patients. Recent advances in interior tomography (reconstruction of an interior region of interest (ROI) from line integrals associated with only paths through the ROI) promise to achieve significant radiation dose reduction without compromising image quality. This study is to investigate the application of this technique in CT imaging through evaluating imaging quality reconstructed from patient data. Methods: Projection data were directly obtained from patients who had CT examinations in a Dual Source CT scanner (DSCT). Two detectors in a DSCT acquired projection data simultaneously. One detector provided projection data for full field of view (FOV, 50 cm) while another detectors provided truncated projection data for a FOV of 26 cm. Full FOV CT images were reconstructed using both filtered back projection and iterative algorithm; while interior tomography algorithm was implemented to reconstruct ROI images. For comparison reason, FBP was also used to reconstruct ROI images. Reconstructed CT images were evaluated by radiologists and compared with images from CT scanner. Results: The results show that the reconstructed ROI image was in excellent agreement with the truth inside the ROI, obtained from images from CT scanner, and the detailed features in the ROI were quantitatively accurate. Radiologists evaluation shows that CT images reconstructed with interior tomography met diagnosis requirements. Radiation dose may be reduced up to 50% using interior tomography, depending on patient size. Conclusion: This study shows that interior tomography can be readily employed in CT imaging for radiation dose reduction. It may be especially useful in imaging obese patients, whose subcutaneous tissue is less clinically relevant but may significantly increase radiation dose.

  8. Three-dimensional segmentation of bone structures in CT images

    NASA Astrophysics Data System (ADS)

    Boehm, Guenther; Knoll, Christian J.; Grau Colomer, Vincente; Alcaniz-Raya, Mariano L.; Albalat, Salvador E.

    1999-05-01

    This work is concerned with the implementation of a fully 3D-consistent, automatic segmentation of bone structures in CT images. The morphological watersheds algorithm has been chosen as the base of the low-level segmentation. The over- segmentation, a phenomenon normally involved with this transformation, has been sorted out successfully by inserting modifying modules that act already within the algorithm. When dealing with a maxillofacial image, this approach also includes the possibility to provide two different divisions of the image: a fine-grained tessellation geared to the following high-level segmentation and a more coarse-grained one for the segmentation of the teeth. In the knowledge-based high-level segmentation, probabilistic considerations make use of specific properties of the 3D low-level regions to find the most probable tissue for each region. Low-level regions that cannot be classified with the necessary certainty are passed to a second stage, where--embedded in their respective environment--they are compared with structural patterns deduced from anatomical knowledge. The tooth segmentation takes the coarse-grained tessellation as its starting point. The few regions making up each tooth are grouped to 3D envelopes--one envelope per tooth. Matched filtering detects the bases of these envelopes. After a refinement they are fitted into the fine- grained, high-level segmented image.

  9. X-space MPI: magnetic nanoparticles for safe medical imaging.

    PubMed

    Goodwill, Patrick William; Saritas, Emine Ulku; Croft, Laura Rose; Kim, Tyson N; Krishnan, Kannan M; Schaffer, David V; Conolly, Steven M

    2012-07-24

    One quarter of all iodinated contrast X-ray clinical imaging studies are now performed on Chronic Kidney Disease (CKD) patients. Unfortunately, the iodine contrast agent used in X-ray is often toxic to CKD patients' weak kidneys, leading to significant morbidity and mortality. Hence, we are pioneering a new medical imaging method, called Magnetic Particle Imaging (MPI), to replace X-ray and CT iodinated angiography, especially for CKD patients. MPI uses magnetic nanoparticle contrast agents that are much safer than iodine for CKD patients. MPI already offers superb contrast and extraordinary sensitivity. The iron oxide nanoparticle tracers required for MPI are also used in MRI, and some are already approved for human use, but the contrast agents are far more effective at illuminating blood vessels when used in the MPI modality. We have recently developed a systems theoretic framework for MPI called x-space MPI, which has already dramatically improved the speed and robustness of MPI image reconstruction. X-space MPI has allowed us to optimize the hardware for fi ve MPI scanners. Moreover, x-space MPI provides a powerful framework for optimizing the size and magnetic properties of the iron oxide nanoparticle tracers used in MPI. Currently MPI nanoparticles have diameters in the 10-20 nanometer range, enabling millimeter-scale resolution in small animals. X-space MPI theory predicts that larger nanoparticles could enable up to 250 micrometer resolution imaging, which would represent a major breakthrough in safe imaging for CKD patients.

  10. High-accuracy registration of intraoperative CT imaging

    NASA Astrophysics Data System (ADS)

    Oentoro, A.; Ellis, R. E.

    2010-02-01

    Image-guided interventions using intraoperative 3D imaging can be less cumbersome than systems dependent on preoperative images, especially by needing neither potentially invasive image-to-patient registration nor a lengthy process of segmenting and generating a 3D surface model. In this study, a method for computer-assisted surgery using direct navigation on intraoperative imaging is presented. In this system the registration step of a navigated procedure was divided into two stages: preoperative calibration of images to a ceiling-mounted optical tracking system, and intraoperative tracking during acquisition of the 3D medical image volume. The preoperative stage used a custom-made multi-modal calibrator that could be optically tracked and also contained fiducial spheres for radiological detection; a robust registration algorithm was used to compensate for the very high false-detection rate that was due to the high physical density of the optical light-emitting diodes. Intraoperatively, a tracking device was attached to plastic bone models that were also instrumented with radio-opaque spheres; A calibrated pointer was used to contact the latter spheres as a validation of the registration. Experiments showed that the fiducial registration error of the preoperative calibration stage was approximately 0.1 mm. The target registration error in the validation stage was approximately 1.2 mm. This study suggests that direct registration, coupled with procedure-specific graphical rendering, is potentially a highly accurate means of performing image-guided interventions in a fast, simple manner.

  11. 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.

  12. MRIdb: medical image management for biobank research.

    PubMed

    Woodbridge, Mark; Fagiolo, Gianlorenzo; O'Regan, Declan P

    2013-10-01

    Clinical picture archiving and communications systems provide convenient, efficient access to digital medical images from multiple modalities but can prove challenging to deploy, configure and use. MRIdb is a self-contained image database, particularly suited to the storage and management of magnetic resonance imaging data sets for population phenotyping. It integrates a mature image archival system with an intuitive web-based user interface that provides visualisation and export functionality. In addition, utilities for auditing, data migration and system monitoring are included in a virtual machine image that is easily deployed with minimal configuration. The result is a freely available turnkey solution, designed to support epidemiological and imaging genetics research. It allows the management of patient data sets in a secure, scalable manner without requiring the installation of any bespoke software on end users' workstations. MRIdb is an open-source software, available for download at http://www3.imperial.ac.uk/bioinfsupport/resources/software/mridb .

  13. Stereo display of CT images for lung cancer screening: a pilot study

    NASA Astrophysics Data System (ADS)

    Wang, Xiao Hui; Durick, Janet E.; Herbert, David L.; Lu, Amy; Golla, Sarawathi K.; Shinde, Dilip D.; Piracha, Samaia; Foley, Kristin; Fuhrman, Carl R.; Shindel, Betty E.; Leader, J. Ken; Good, Walter F.

    2007-03-01

    To improve radiologist's performance in lesion detection and diagnosis on 3D medical image dataset, we have conducted a pilot study to test viability and efficiency of the stereo display for lung nodule detection and classification. Using our previously developed stereo compositing methods, stereo image pairs were prestaged and precalculated from CT slices for real-time interactive display. Three display modes (i.e., stereoscopic 3D, orthogonal MIP and slice-by-slice) were compared for lung nodule detection and total of eight radiologists have participated this pilot study to interpret the images. The performance of lung nodule detection was analyzed and compared between the modes using FROC analysis. Subjective assessment indicates that stereo display was well accepted by the radiologists, despite some uncertainty of beneficial results due to the novelty of the display. The FROC analysis indicates a trend that, among the three display modes, stereo display resulted in the best performance of nodule detection followed by slice-based display, although no statistically significant difference was shown between the three modes. The stereo display of a stack of thin CT slices has the potential to clarify three-dimensional structures, while avoiding ambiguities due to tissue superposition. Few studies, however, have addressed actual utility of stereo display for medical diagnosis. Our preliminary results suggest a potential role of stereo display for improving radiologists' performance in medical detection and diagnosis, and also indicate some factors likely affect the performance with new display, such as novelty of the display, training effect from projected radiography interpretation and confidence with the new technology.

  14. TU-G-303-02: Robust Radiomics Methods for PET and CT Imaging

    SciTech Connect

    Aerts, H.

    2015-06-15

    ‘Radiomics’ refers to studies that extract a large amount of quantitative information from medical imaging studies as a basis for characterizing a specific aspect of patient health. Radiomics models can be built to address a wide range of outcome predictions, clinical decisions, basic cancer biology, etc. For example, radiomics models can be built to predict the aggressiveness of an imaged cancer, cancer gene expression characteristics (radiogenomics), radiation therapy treatment response, etc. Technically, radiomics brings together quantitative imaging, computer vision/image processing, and machine learning. In this symposium, speakers will discuss approaches to radiomics investigations, including: longitudinal radiomics, radiomics combined with other biomarkers (‘pan-omics’), radiomics for various imaging modalities (CT, MRI, and PET), and the use of registered multi-modality imaging datasets as a basis for radiomics. There are many challenges to the eventual use of radiomics-derived methods in clinical practice, including: standardization and robustness of selected metrics, accruing the data required, building and validating the resulting models, registering longitudinal data that often involve significant patient changes, reliable automated cancer segmentation tools, etc. Despite the hurdles, results achieved so far indicate the tremendous potential of this general approach to quantifying and using data from medical images. Specific applications of radiomics to be presented in this symposium will include: the longitudinal analysis of patients with low-grade gliomas; automatic detection and assessment of patients with metastatic bone lesions; image-based monitoring of patients with growing lymph nodes; predicting radiotherapy outcomes using multi-modality radiomics; and studies relating radiomics with genomics in lung cancer and glioblastoma. Learning Objectives: Understanding the basic image features that are often used in radiomic models. Understanding

  15. Molecular PET/CT imaging-guided radiation therapy treatment planning.

    PubMed

    Zaidi, Habib; Vees, Hansjörg; Wissmeyer, Michael

    2009-09-01

    The role of positron emission tomography (PET) during the past decade has evolved rapidly from that of a pure research tool to a methodology of enormous clinical potential. (18)F-fluorodeoxyglucose (FDG)-PET is currently the most widely used probe in the diagnosis, staging, assessment of tumor response to treatment, and radiation therapy planning because metabolic changes generally precede the more conventionally measured parameter of change in tumor size. Data accumulated rapidly during the last decade, thus validating the efficacy of FDG imaging and many other tracers in a wide variety of malignant tumors with sensitivities and specificities often in the high 90 percentile range. As a result, PET/computed tomography (CT) had a significant impact on the management of patients because it obviated the need for further evaluation, guided further diagnostic procedures, and assisted in planning therapy for a considerable number of patients. On the other hand, the progress in radiation therapy technology has been enormous during the last two decades, now offering the possibility to plan highly conformal radiation dose distributions through the use of sophisticated beam targeting techniques such as intensity-modulated radiation therapy (IMRT) using tomotherapy, volumetric modulated arc therapy, and many other promising technologies for sculpted three-dimensional (3D) dose distribution. The foundation of molecular imaging-guided radiation therapy lies in the use of advanced imaging technology for improved definition of tumor target volumes, thus relating the absorbed dose information to image-based patient representations. This review documents technological advancements in the field concentrating on the conceptual role of molecular PET/CT imaging in radiation therapy treatment planning and related image processing issues with special emphasis on segmentation of medical images for the purpose of defining target volumes. There is still much more work to be done and many of

  16. ConvNet-Based Localization of Anatomical Structures in 3D Medical Images.

    PubMed

    de Vos, Bob; Wolterink, Jelmer; de Jong, Pim; Leiner, Tim; Viergever, Max; Isgum, Ivana

    2017-02-23

    Localization of anatomical structures is a prerequisite for many tasks in medical image analysis. We propose a method for automatic localization of one or more anatomical structures in 3D medical images through detection of their presence in 2D image slices using a convolutional neural network (ConvNet). A single ConvNet is trained to detect presence of the anatomical structure of interest in axial, coronal, and sagittal slices extracted from a 3D image. To allow the ConvNet to analyze slices of different sizes, spatial pyramid pooling is applied. After detection, 3D bounding boxes are created by combining the output of the ConvNet in all slices. In the experiments 200 chest CT, 100 cardiac CT angiography (CTA), and 100 abdomen CT scans were used. The heart, ascending aorta, aortic arch, and descending aorta were localized in chest CT scans, the left cardiac ventricle in cardiac CTA scans, and the liver in abdomen CT scans. Localization was evaluated using the distances between automatically and manually defined reference bounding box centroids and walls. The best results were achieved in localization of structures with clearly defined boundaries (e.g. aortic arch) and the worst when the structure boundary was not clearly visible (e.g. liver). The method was more robust and accurate in localization multiple structures.

  17. A novel stereoscopic projection display system for CT images of fractures

    PubMed Central

    LIU, XIUJUAN; JIANG, HONG; LANG, YUEDONG; WANG, HONGBO; SUN, NA

    2013-01-01

    The present study proposed a novel projection display system based on a virtual reality enhancement environment. The proposed system displays stereoscopic images of fractures and enhances the computed tomography (CT) images. The diagnosis and treatment of fractures primarily depend on the post-processing of CT images. However, two-dimensional (2D) images do not show overlapping structures in fractures since they are displayed without visual depth and these structures are too small to be simultaneously observed by a group of clinicians. Stereoscopic displays may solve this problem and allow clinicians to obtain more information from CT images. Hardware with which to generate stereoscopic images was designed. This system utilized the conventional equipment found in meeting rooms. The off-axis algorithm was adopted to convert the CT images into stereo image pairs, which were used as the input for a stereo generator. The final stereoscopic images were displayed using a projection system. Several CT fracture images were imported into the system for comparison with traditional 2D CT images. The results showed that the proposed system aids clinicians in group discussions by producing large stereoscopic images. The results demonstrated that the enhanced stereoscopic CT images generated by the system appear clearer and smoother, such that the sizes, displacement and shapes of bone fragments are easier to assess. Certain fractures that were previously not visible on 2D CT images due to vision overlap became vividly evident in the stereo images. The proposed projection display system efficiently, economically and accurately displayed three-dimensional (3D) CT images. The system may help clinicians improve the diagnosis and treatment of fractures. PMID:23837053

  18. A novel stereoscopic projection display system for CT images of fractures.

    PubMed

    Liu, Xiujuan; Jiang, Hong; Lang, Yuedong; Wang, Hongbo; Sun, Na

    2013-06-01

    The present study proposed a novel projection display system based on a virtual reality enhancement environment. The proposed system displays stereoscopic images of fractures and enhances the computed tomography (CT) images. The diagnosis and treatment of fractures primarily depend on the post-processing of CT images. However, two-dimensional (2D) images do not show overlapping structures in fractures since they are displayed without visual depth and these structures are too small to be simultaneously observed by a group of clinicians. Stereoscopic displays may solve this problem and allow clinicians to obtain more information from CT images. Hardware with which to generate stereoscopic images was designed. This system utilized the conventional equipment found in meeting rooms. The off-axis algorithm was adopted to convert the CT images into stereo image pairs, which were used as the input for a stereo generator. The final stereoscopic images were displayed using a projection system. Several CT fracture images were imported into the system for comparison with traditional 2D CT images. The results showed that the proposed system aids clinicians in group discussions by producing large stereoscopic images. The results demonstrated that the enhanced stereoscopic CT images generated by the system appear clearer and smoother, such that the sizes, displacement and shapes of bone fragments are easier to assess. Certain fractures that were previously not visible on 2D CT images due to vision overlap became vividly evident in the stereo images. The proposed projection display system efficiently, economically and accurately displayed three-dimensional (3D) CT images. The system may help clinicians improve the diagnosis and treatment of fractures.

  19. Incorporating multislice imaging into x-ray CT polymer gel dosimetry

    SciTech Connect

    Johnston, H.; Hilts, M.; Jirasek, A.

    2015-04-15

    Purpose: To evaluate multislice computed tomography (CT) scanning for fast and reliable readout of radiation therapy (RT) dose distributions using CT polymer gel dosimetry (PGD) and to establish a baseline assessment of image noise and uniformity in an unirradiated gel dosimeter. Methods: A 16-slice CT scanner was used to acquire images through a 1 L cylinder filled with water. Additional images were collected using a single slice machine. The variability in CT number (N{sub CT}) associated with the anode heel effect was evaluated and used to define a new slice-by-slice background subtraction artifact removal technique for CT PGD. Image quality was assessed for the multislice system by evaluating image noise and uniformity. The agreement in N{sub CT} for slices acquired simultaneously using the multislice detector array was also examined. Further study was performed to assess the effects of increasing x-ray tube load on the constancy of measured N{sub CT} and overall scan time. In all cases, results were compared to the single slice machine. Finally, images were collected throughout the volume of an unirradiated gel dosimeter to quantify image noise and uniformity before radiation is delivered. Results: Slice-by-slice background subtraction effectively removes the variability in N{sub CT} observed across images acquired simultaneously using the multislice scanner and is the recommended background subtraction method when using a multislice CT system. Image noise was higher for the multislice system compared to the single slice scanner, but overall image quality was comparable between the two systems. Further study showed N{sub CT} was consistent across image slices acquired simultaneously using the multislice detector array for each detector configuration of the slice thicknesses examined. In addition, the multislice system was found to eliminate variations in N{sub CT} due to increasing x-ray tube load and reduce scanning time by a factor of 4 when compared to

  20. Resolution enhancement in medical ultrasound imaging

    PubMed Central

    Ploquin, Marie; Basarab, Adrian; Kouamé, Denis

    2015-01-01

    Abstract. Image resolution enhancement is a problem of considerable interest in all medical imaging modalities. Unlike general purpose imaging or video processing, for a very long time, medical image resolution enhancement has been based on optimization of the imaging devices. Although some recent works purport to deal with image postprocessing, much remains to be done regarding medical image enhancement via postprocessing, especially in ultrasound imaging. We face a resolution improvement issue in the case of medical ultrasound imaging. We propose to investigate this problem using multidimensional autoregressive (AR) models. Noting that the estimation of the envelope of an ultrasound radio frequency (RF) signal is very similar to the estimation of classical Fourier-based power spectrum estimation, we theoretically show that a domain change and a multidimensional AR model can be used to achieve super-resolution in ultrasound imaging provided the order is estimated correctly. Here, this is done by means of a technique that simultaneously estimates the order and the parameters of a multidimensional model using relevant regression matrix factorization. Doing so, the proposed method specifically fits ultrasound imaging and provides an estimated envelope. Moreover, an expression that links the theoretical image resolution to both the image acquisition features (such as the point spread function) and a postprocessing feature (the AR model) order is derived. The overall contribution of this work is threefold. First, it allows for automatic resolution improvement. Through a simple model and without any specific manual algorithmic parameter tuning, as is used in common methods, the proposed technique simply and exclusively uses the ultrasound RF signal as input and provides the improved B-mode as output. Second, it allows for the a priori prediction of the improvement in resolution via the knowledge of the parametric model order before actual processing. Finally, to achieve

  1. Resolution enhancement in medical ultrasound imaging.

    PubMed

    Ploquin, Marie; Basarab, Adrian; Kouamé, Denis

    2015-01-01

    Image resolution enhancement is a problem of considerable interest in all medical imaging modalities. Unlike general purpose imaging or video processing, for a very long time, medical image resolution enhancement has been based on optimization of the imaging devices. Although some recent works purport to deal with image postprocessing, much remains to be done regarding medical image enhancement via postprocessing, especially in ultrasound imaging. We face a resolution improvement issue in the case of medical ultrasound imaging. We propose to investigate this problem using multidimensional autoregressive (AR) models. Noting that the estimation of the envelope of an ultrasound radio frequency (RF) signal is very similar to the estimation of classical Fourier-based power spectrum estimation, we theoretically show that a domain change and a multidimensional AR model can be used to achieve super-resolution in ultrasound imaging provided the order is estimated correctly. Here, this is done by means of a technique that simultaneously estimates the order and the parameters of a multidimensional model using relevant regression matrix factorization. Doing so, the proposed method specifically fits ultrasound imaging and provides an estimated envelope. Moreover, an expression that links the theoretical image resolution to both the image acquisition features (such as the point spread function) and a postprocessing feature (the AR model) order is derived. The overall contribution of this work is threefold. First, it allows for automatic resolution improvement. Through a simple model and without any specific manual algorithmic parameter tuning, as is used in common methods, the proposed technique simply and exclusively uses the ultrasound RF signal as input and provides the improved B-mode as output. Second, it allows for the a priori prediction of the improvement in resolution via the knowledge of the parametric model order before actual processing. Finally, to achieve the

  2. Segmentation of the thoracic aorta in noncontrast cardiac CT images.

    PubMed

    Avila-Montes, Olga C; Kurkure, Uday; Nakazato, Ryo; Berman, Daniel S; Dey, Damini; Kakadiaris, Ioannis A

    2013-09-01

    Studies have shown that aortic calcification is associated with cardiovascular disease. In this study, a method for localization, centerline extraction, and segmentation of the thoracic aorta in noncontrast cardiac-computed tomography (CT) images, toward the detection of aortic calcification, is presented. The localization of the right coronary artery ostium slice is formulated as a regression problem whose input variables are obtained from simple intensity features computed from a pyramid representation of the slice. The localization, centerline extraction, and segmentation of the aorta are formulated as optimal path detection problems. Dynamic programming is applied in the Hough space for localizing key center points in the aorta which guide the centerline tracing using a fast marching-based minimal path extraction framework. The input volume is then resampled into a stack of 2-D cross-sectional planes orthogonal to the obtained centerline. Dynamic programming is again applied for the segmentation of the aorta in each slice of the resampled volume. The obtained segmentation is finally mapped back to its original volume space. The performance of the proposed method was assessed on cardiac noncontrast CT scans and promising results were obtained.

  3. Watermarked cardiac CT image segmentation using deformable models and the Hermite transform

    NASA Astrophysics Data System (ADS)

    Gomez-Coronel, Sandra L.; Moya-Albor, Ernesto; Escalante-Ramírez, Boris; Brieva, Jorge

    2015-01-01

    Medical image watermarking is an open area for research and is a solution for the protection of copyright and intellectual property. One of the main challenges of this problem is that the marked images should not differ perceptually from the original images allowing a correct diagnosis and authentication. Furthermore, we also aim at obtaining watermarked images with very little numerical distortion so that computer vision tasks such as segmentation of important anatomical structures do not be impaired or affected. We propose a preliminary watermarking application in cardiac CT images based on a perceptive approach that includes a brightness model to generate a perceptive mask and identify the image regions where the watermark detection becomes a difficult task for the human eye. We propose a normalization scheme of the image in order to improve robustness against geometric attacks. We follow a spread spectrum technique to insert an alphanumeric code, such as patient's information, within the watermark. The watermark scheme is based on the Hermite transform as a bio-inspired image representation model. In order to evaluate the numerical integrity of the image data after watermarking, we perform a segmentation task based on deformable models. The segmentation technique is based on a vector-value level sets method such that, given a curve in a specific image, and subject to some constraints, the curve can evolve in order to detect objects. In order to stimulate the curve evolution we introduce simultaneously some image features like the gray level and the steered Hermite coefficients as texture descriptors. Segmentation performance was assessed by means of the Dice index and the Hausdorff distance. We tested different mark sizes and different insertion schemes on images that were later segmented either automatic or manual by physicians.

  4. 3D nonrigid medical image registration using a new information theoretic measure

    NASA Astrophysics Data System (ADS)

    Li, Bicao; Yang, Guanyu; Coatrieux, Jean Louis; Li, Baosheng; Shu, Huazhong

    2015-11-01

    This work presents a novel method for the nonrigid registration of medical images based on the Arimoto entropy, a generalization of the Shannon entropy. The proposed method employed the Jensen-Arimoto divergence measure as a similarity metric to measure the statistical dependence between medical images. Free-form deformations were adopted as the transformation model and the Parzen window estimation was applied to compute the probability distributions. A penalty term is incorporated into the objective function to smooth the nonrigid transformation. The goal of registration is to optimize an objective function consisting of a dissimilarity term and a penalty term, which would be minimal when two deformed images are perfectly aligned using the limited memory BFGS optimization method, and thus to get the optimal geometric transformation. To validate the performance of the proposed method, experiments on both simulated 3D brain MR images and real 3D thoracic CT data sets were designed and performed on the open source elastix package. For the simulated experiments, the registration errors of 3D brain MR images with various magnitudes of known deformations and different levels of noise were measured. For the real data tests, four data sets of 4D thoracic CT from four patients were selected to assess the registration performance of the method, including ten 3D CT images for each 4D CT data covering an entire respiration cycle. These results were compared with the normalized cross correlation and the mutual information methods and show a slight but true improvement in registration accuracy.

  5. [Promoting "well-treatment" in medical imaging].

    PubMed

    Renouf, Nicole; Llop, Marc

    2012-12-01

    A project to promote "well-treatment" has been initiated in the medical imaging department of a Parisian hospital. With the aim of promoting the well-being of the patient and developing shared values of empathy and respect, the members of this medico-technical team have undertaken to build a culture of "well-treatment" which respects the patient's dignity and rights.

  6. Medical Imaging with Ultrasound: Some Basic Physics.

    ERIC Educational Resources Information Center

    Gosling, R.

    1989-01-01

    Discussed are medical applications of ultrasound. The physics of the wave nature of ultrasound including its propagation and production, return by the body, spatial and contrast resolution, attenuation, image formation using pulsed echo ultrasound techniques, measurement of velocity and duplex scanning are described. (YP)

  7. A patient-centric distribution architecture for medical image sharing.

    PubMed

    Constantinescu, Liviu; Kim, Jinman; Kumar, Ashnil; Haraguchi, Daiki; Wen, Lingfeng; Feng, Dagan

    2013-01-01

    Over the past decade, rapid development of imaging technologies has resulted in the introduction of improved imaging devices, such as multi-modality scanners that produce combined positron emission tomography-computed tomography (PET-CT) images. The adoption of picture archiving and communication systems (PACS) in hospitals have dramatically improved the ability to digitally share medical image studies via portable storage, mobile devices and the Internet. This has in turn led to increased productivity, greater flexibility, and improved communication between hospital staff, referring physicians, and outpatients. However, many of these sharing and viewing capabilities are limited to proprietary vendor-specific applications. Furthermore, there are still interoperability and deployment issues which reduce the rate of adoption of such technologies, thus leaving many stakeholders, particularly outpatients and referring physicians, with access to only traditional still images with no ability to view or interpret the data in full. In this paper, we present a distribution architecture for medical image display across numerous devices and media, which uses a preprocessor and an in-built networking framework to improve compatibility and promote greater accessibility of medical data. Our INVOLVE2 system consists of three main software modules: 1) a preprocessor, which collates and converts imaging studies into a compressed and distributable format; 2) a PACS-compatible workflow for self-managing distribution of medical data, e.g. via CD USB, network etc; 3) support for potential mobile and web-based data access. The focus of this study was on cultivating patient-centric care, by allowing outpatient users to comfortably access and interpret their own data. As such, the image viewing software included on our cross-platform CDs was designed with a simple and intuitive user-interface (UI) for use by outpatients and referring physicians. Furthermore, digital image access via

  8. Improving abdomen tumor low-dose CT images using a fast dictionary learning based processing

    NASA Astrophysics Data System (ADS)

    Chen, Yang; Yin, Xindao; Shi, Luyao; Shu, Huazhong; Luo, Limin; Coatrieux, Jean-Louis; Toumoulin, Christine

    2013-08-01

    In abdomen computed tomography (CT), repeated radiation exposures are often inevitable for cancer patients who receive surgery or radiotherapy guided by CT images. Low-dose scans should thus be considered in order to avoid the harm of accumulative x-ray radiation. This work is aimed at improving abdomen tumor CT images from low-dose scans by using a fast dictionary learning (DL) based processing. Stemming from sparse representation theory, the proposed patch-based DL approach allows effective suppression of both mottled noise and streak artifacts. The experiments carried out on clinical data show that the proposed method brings encouraging improvements in abdomen low-dose CT images with tumors.

  9. Clinical applications of dual-energy CT in head and neck imaging.

    PubMed

    Ginat, Daniel Thomas; Mayich, Michael; Daftari-Besheli, Laleh; Gupta, Rajiv

    2016-03-01

    Dual-energy CT provides insights into the material properties of the tissues and can differentiate between tissues that have similar attenuation on conventional, single energy CT imaging. It has several useful and promising applications in head and neck imaging that an otolaryngologist could use to deliver improved clinical care. These applications include metal artifact reduction, atherosclerotic plaque and tumor characterization, detection of parathyroid lesions, and delineation of paranasal sinus ventilation. Dual-energy CT can potentially improve image quality, reduce radiation dose, and provide specific diagnostic information for certain head and neck lesions. This article reviews some current and potential otolaryngology applications of dual-energy CT.

  10. Medical image registration using sparse coding of image patches.

    PubMed

    Afzali, Maryam; Ghaffari, Aboozar; Fatemizadeh, Emad; Soltanian-Zadeh, Hamid

    2016-06-01

    Image registration is a basic task in medical image processing applications like group analysis and atlas construction. Similarity measure is a critical ingredient of image registration. Intensity distortion of medical images is not considered in most previous similarity measures. Therefore, in the presence of bias field distortions, they do not generate an acceptable registration. In this paper, we propose a sparse based similarity measure for mono-modal images that considers non-stationary intensity and spatially-varying distortions. The main idea behind this measure is that the aligned image is constructed by an analysis dictionary trained using the image patches. For this purpose, we use "Analysis K-SVD" to train the dictionary and find the sparse coefficients. We utilize image patches to construct the analysis dictionary and then we employ the proposed sparse similarity measure to find a non-rigid transformation using free form deformation (FFD). Experimental results show that the proposed approach is able to robustly register 2D and 3D images in both simulated and real cases. The proposed method outperforms other state-of-the-art similarity measures and decreases the transformation error compared to the previous methods. Even in the presence of bias field distortion, the proposed method aligns images without any preprocessing.

  11. Advanced ultrasound probes for medical imaging

    NASA Astrophysics Data System (ADS)

    Wildes, Douglas G.; Smith, L. Scott

    2012-05-01

    New medical ultrasound probe architectures and materials build upon established 1D phased array technology and provide improved imaging performance and clinical value. Technologies reviewed include 1.25D and 1.5D arrays for elevation slice thickness control; electro-mechanical and 2D array probes for real-time 3D imaging; catheter probes for imaging during minimally-invasive procedures; single-crystal piezoelectric materials for greater frequency bandwidth; and cMUT arrays using silicon MEMS in place of piezo materials.

  12. Model observers in medical imaging research.

    PubMed

    He, Xin; Park, Subok

    2013-10-04

    Model observers play an important role in the optimization and assessment of imaging devices. In this review paper, we first discuss the basic concepts of model observers, which include the mathematical foundations and psychophysical considerations in designing both optimal observers for optimizing imaging systems and anthropomorphic observers for modeling human observers. Second, we survey a few state-of-the-art computational techniques for estimating model observers and the principles of implementing these techniques. Finally, we review a few applications of model observers in medical imaging research.

  13. Temporal and spectral imaging with micro-CT

    SciTech Connect

    Johnston, Samuel M.; Johnson, G. Allan; Badea, Cristian T.

    2012-08-15

    Purpose: Micro-CT is widely used for small animal imaging in preclinical studies of cardiopulmonary disease, but further development is needed to improve spatial resolution, temporal resolution, and material contrast. We present a technique for visualizing the changing distribution of iodine in the cardiac cycle with dual source micro-CT. Methods: The approach entails a retrospectively gated dual energy scan with optimized filters and voltages, and a series of computational operations to reconstruct the data. Projection interpolation and five-dimensional bilateral filtration (three spatial dimensions + time + energy) are used to reduce noise and artifacts associated with retrospective gating. We reconstruct separate volumes corresponding to different cardiac phases and apply a linear transformation to decompose these volumes into components representing concentrations of water and iodine. Since the resulting material images are still compromised by noise, we improve their quality in an iterative process that minimizes the discrepancy between the original acquired projections and the projections predicted by the reconstructed volumes. The values in the voxels of each of the reconstructed volumes represent the coefficients of linear combinations of basis functions over time and energy. We have implemented the reconstruction algorithm on a graphics processing unit (GPU) with CUDA. We tested the utility of the technique in simulations and applied the technique in an in vivo scan of a C57BL/6 mouse injected with blood pool contrast agent at a dose of 0.01 ml/g body weight. Postreconstruction, at each cardiac phase in the iodine images, we segmented the left ventricle and computed its volume. Using the maximum and minimum volumes in the left ventricle, we calculated the stroke volume, the ejection fraction, and the cardiac output. Results: Our proposed method produces five-dimensional volumetric images that distinguish different materials at different points in time, and

  14. 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.

  15. Evaluation of the robustness of the preprocessing technique improving reversible compressibility of CT images: Tested on various CT examinations

    SciTech Connect

    Jeon, Chang Ho; Kim, Bohyoung; Gu, Bon Seung; Lee, Jong Min; Kim, Kil Joong; Lee, Kyoung Ho; Kim, Tae Ki

    2013-10-15

    Purpose: To modify the preprocessing technique, which was previously proposed, improving compressibility of computed tomography (CT) images to cover the diversity of three dimensional configurations of different body parts and to evaluate the robustness of the technique in terms of segmentation correctness and increase in reversible compression ratio (CR) for various CT examinations.Methods: This study had institutional review board approval with waiver of informed patient consent. A preprocessing technique was previously proposed to improve the compressibility of CT images by replacing pixel values outside the body region with a constant value resulting in maximizing data redundancy. Since the technique was developed aiming at only chest CT images, the authors modified the segmentation method to cover the diversity of three dimensional configurations of different body parts. The modified version was evaluated as follows. In randomly selected 368 CT examinations (352 787 images), each image was preprocessed by using the modified preprocessing technique. Radiologists visually confirmed whether the segmented region covers the body region or not. The images with and without the preprocessing were reversibly compressed using Joint Photographic Experts Group (JPEG), JPEG2000 two-dimensional (2D), and JPEG2000 three-dimensional (3D) compressions. The percentage increase in CR per examination (CR{sub I}) was measured.Results: The rate of correct segmentation was 100.0% (95% CI: 99.9%, 100.0%) for all the examinations. The median of CR{sub I} were 26.1% (95% CI: 24.9%, 27.1%), 40.2% (38.5%, 41.1%), and 34.5% (32.7%, 36.2%) in JPEG, JPEG2000 2D, and JPEG2000 3D, respectively.Conclusions: In various CT examinations, the modified preprocessing technique can increase in the CR by 25% or more without concerning about degradation of diagnostic information.

  16. 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.

  17. A Segmentation Framework of Pulmonary Nodules in Lung CT Images.

    PubMed

    Mukhopadhyay, Sudipta

    2016-02-01

    Accurate segmentation of pulmonary nodules is a prerequisite for acceptable performance of computer-aided detection (CAD) system designed for diagnosis of lung cancer from lung CT images. Accurate segmentation helps to improve the quality of machine level features which could improve the performance of the CAD system. The well-circumscribed solid nodules can be segmented using thresholding, but segmentation becomes difficult for part-solid, non-solid, and solid nodules attached with pleura or vessels. We proposed a segmentation framework for all types of pulmonary nodules based on internal texture (solid/part-solid and non-solid) and external attachment (juxta-pleural and juxta-vascular). In the proposed framework, first pulmonary nodules are categorized into solid/part-solid and non-solid category by analyzing intensity distribution in the core of the nodule. Two separate segmentation methods are developed for solid/part-solid and non-solid nodules, respectively. After determining the category of nodule, the particular algorithm is set to remove attached pleural surface and vessels from the nodule body. The result of segmentation is evaluated in terms of four contour-based metrics and six region-based metrics for 891 pulmonary nodules from Lung Image Database Consortium and Image Database Resource Initiative (LIDC/IDRI) public database. The experimental result shows that the proposed segmentation framework is reliable for segmentation of various types of pulmonary nodules with improved accuracy compared to existing segmentation methods.

  18. Neural networks: Application to medical imaging

    NASA Technical Reports Server (NTRS)

    Clarke, Laurence P.

    1994-01-01

    The research mission is the development of computer assisted diagnostic (CAD) methods for improved diagnosis of medical images including digital x-ray sensors and tomographic imaging modalities. The CAD algorithms include advanced methods for adaptive nonlinear filters for image noise suppression, hybrid wavelet methods for feature segmentation and enhancement, and high convergence neural networks for feature detection and VLSI implementation of neural networks for real time analysis. Other missions include (1) implementation of CAD methods on hospital based picture archiving computer systems (PACS) and information networks for central and remote diagnosis and (2) collaboration with defense and medical industry, NASA, and federal laboratories in the area of dual use technology conversion from defense or aerospace to medicine.

  19. HIPAA compliant auditing system for medical images.

    PubMed

    Zhou, Zheng; Liu, Brent J

    2005-01-01

    As an official regulation for healthcare privacy and security, Health Insurance Portability and Accountability Act (HIPAA) mandates health institutions to protect health information against unauthorized use or disclosure. One such method proposed by HIPAA Security Standards is audit trail, which records and examines health information access activities. HIPAA mandates healthcare providers to have the ability to generate audit trails on data access activities for any specific patient. Although current medical imaging systems generate activity logs, there is a lack of formal methodology to interpret these large volumes of log data and generate HIPAA compliant auditing trails. This paper outlines the design of a HIPAA compliant auditing system (HCAS) for medical images in imaging systems such as PACS and discusses the development of a security monitoring (SM) toolkit based on some of the partial components in HCAS.

  20. Ultra-low dose comprehensive cardiac CT imaging in a patient with acute myocarditis.

    PubMed

    Tröbs, Monique; Brand, Michael; Achenbach, Stephan; Marwan, Mohamed

    2014-01-01

    The ability of contrast-enhanced CT to detect "late enhancement" in a fashion similar to magnetic resonance imaging has been previously reported. We report a case of acute myocarditis with coronary CT angiography as well as "late enhancement" imaging with ultra-low effective radiation dose.

  1. 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.

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

    PubMed

    Thing, Rune Slot; Bernchou, Uffe; Mainegra-Hing, Ernesto; Hansen, Olfred; Brink, Carsten

    2016-08-07

    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.

  3. Polyimide MEMS actuators for medical imaging

    NASA Astrophysics Data System (ADS)

    Zara, Jason M.; Mills, Patrick; Patterson, Paul

    2005-01-01

    This paper provides an overview of several years of research in the use of polyimide MEMS actuators for medical imaging applications, including high frequency ultrasound and optical coherence tomography (OCT). These scanning devices are microfabricated out of polyimide substrates using conventional integrated circuit technology. The material properties of the polyimide allow very large scan angles to be realized and also allow the resonant frequencies of the structures to be in the appropriate ranges for real-time imaging. The primary application of these probes is endoscopic and catheter-based imaging procedures. The microfabrication enables the creation of very small devices essential for compact imaging probes. In addition, they can be fabricated in bulk, reducing their cost and potentially making them disposable to reduce the cost of patient care and minimize the potential for patient cross-contamination. Several different scanning geometries and actuators have been investigated for imaging applications, including both forward-viewing and side-scanning configurations. Probes that utilize both electrostatic polyimide actuators and piezoelectric bimorphs to mechanically scan the ultrasound or OCT imaging beams will be presented. These probes have been developed for both use in both ultrasound and OCT imaging systems. Medical applications of these probes include the early detection of cancerous and precancerous conditions in the bladder and other mucosal tissues. These imaging probes will allow the physician to visualize the subsurface microstructure of the tissues and detect abnormalities not visible through the use of conventional endoscopic imaging techniques. Prototype devices have been used to image geometric wire phantoms, in vitro porcine tissue, and in vivo subjects. The progress made over the last several years in the development of these polyimide scanning probes will be presented.

  4. Novel and powerful 3D adaptive crisp active contour method applied in the segmentation of CT lung images.

    PubMed

    Rebouças Filho, Pedro Pedrosa; Cortez, Paulo César; da Silva Barros, Antônio C; C Albuquerque, Victor Hugo; R S Tavares, João Manuel

    2017-01-01

    The World Health Organization estimates that 300 million people have asthma, 210 million people have Chronic Obstructive Pulmonary Disease (COPD), and, according to WHO, COPD will become the third major cause of death worldwide in 2030. Computational Vision systems are commonly used in pulmonology to address the task of image segmentation, which is essential for accurate medical diagnoses. Segmentation defines the regions of the lungs in CT images of the thorax that must be further analyzed by the system or by a specialist physician. This work proposes a novel and powerful technique named 3D Adaptive Crisp Active Contour Method (3D ACACM) for the segmentation of CT lung images. The method starts with a sphere within the lung to be segmented that is deformed by forces acting on it towards the lung borders. This process is performed iteratively in order to minimize an energy function associated with the 3D deformable model used. In the experimental assessment, the 3D ACACM is compared against three approaches commonly used in this field: the automatic 3D Region Growing, the level-set algorithm based on coherent propagation and the semi-automatic segmentation by an expert using the 3D OsiriX toolbox. When applied to 40 CT scans of the chest the 3D ACACM had an average F-measure of 99.22%, revealing its superiority and competency to segment lungs in CT images.

  5. Automatic localization of IASLC-defined mediastinal lymph node stations on CT images using fuzzy models

    NASA Astrophysics Data System (ADS)

    Matsumoto, Monica M. S.; Beig, Niha G.; Udupa, Jayaram K.; Archer, Steven; Torigian, Drew A.

    2014-03-01

    Lung cancer is associated with the highest cancer mortality rates among men and women in the United States. The accurate and precise identification of the lymph node stations on computed tomography (CT) images is important for staging disease and potentially for prognosticating outcome in patients with lung cancer, as well as for pretreatment planning and response assessment purposes. To facilitate a standard means of referring to lymph nodes, the International Association for the Study of Lung Cancer (IASLC) has recently proposed a definition of the different lymph node stations and zones in the thorax. However, nodal station identification is typically performed manually by visual assessment in clinical radiology. This approach leaves room for error due to the subjective and potentially ambiguous nature of visual interpretation, and is labor intensive. We present a method of automatically recognizing the mediastinal IASLC-defined lymph node stations by modifying a hierarchical fuzzy modeling approach previously developed for body-wide automatic anatomy recognition (AAR) in medical imagery. Our AAR-lymph node (AAR-LN) system follows the AAR methodology and consists of two steps. In the first step, the various lymph node stations are manually delineated on a set of CT images following the IASLC definitions. These delineations are then used to build a fuzzy hierarchical model of the nodal stations which are considered as 3D objects. In the second step, the stations are automatically located on any given CT image of the thorax by using the hierarchical fuzzy model and object recognition algorithms. Based on 23 data sets used for model building, 22 independent data sets for testing, and 10 lymph node stations, a mean localization accuracy of within 1-6 voxels has been achieved by the AAR-LN system.

  6. A preliminary study of CT imaging of water in a carnation flower

    NASA Astrophysics Data System (ADS)

    Nakanishi, T. M.; Furukawa, J.; Matsubayashi, M.

    1999-11-01

    We present the trial to determine the water deletion part in a carnation flower tissue while drying by neutron computer tomography (CT). The flower part was fixed on a rotating disk and thermal neutrons were irradiated for 4 s per projection. The total neutron dose was 6.0×10 8 n/cm 2 per projection. The neutrons penetrating the sample were converted to photons by a fluorescence converter. The photon image was guided to a cooled CCD camera using two mirrors. The sample was rotated, stepwise, every 1°, up to 180°, i.e. 180 images were obtained for the CT construction. Horizontal CT images of several slices of the flower were taken before and after the drying treatment. Vertical CT images of the flower were also constructed based on horizontal CT images. It was found that the water around the ovule was selectively removed by the drying treatment.

  7. The impact of spectral filtration on image quality in micro-CT system.

    PubMed

    Ren, Liqiang; Ghani, Muhammad U; Wu, Di; Zheng, Bin; Chen, Yong; Yang, Kai; Wu, Xizeng; Liu, Hong

    2016-01-08

    This paper aims to evaluate the impact of spectral filtration on image quality in a microcomputed tomography (micro-CT) system. A mouse phantom comprising 11rods for modeling lung, muscle, adipose, and bones was scanned with 17 s and 2min, respectively. The current (μA) for each scan was adjusted to achieve identical entrance exposure to the phantom, providing a baseline for image quality evaluation. For each region of interest (ROI) within specific composition, CT number variations, noise levels, and contrast-to-noise ratios (CNRs) were evaluated from the reconstructed images. CT number variations and CNRs for bone with high density, muscle, and adipose were compared with theoretical predictions. The results show that the impact of spectral filtration on image quality indicators, such as CNR in a micro-CT system, is significantly associated with tissue characteristics. The findings may provide useful references for optimizing the scanning parameters of general micro-CT systems in future imaging applications.

  8. Validated Automatic Brain Extraction of Head CT Images

    PubMed Central

    Muschelli, John; Ullman, Natalie L.; Mould, W. Andrew; Vespa, Paul; Hanley, Daniel F.; Crainiceanu, Ciprian M.

    2015-01-01

    Background X-ray Computed Tomography (CT) imaging of the brain is commonly used in diagnostic settings. Although CT scans are primarily used in clinical practice, they are increasingly used in research. A fundamental processing step in brain imaging research is brain extraction – the process of separating the brain tissue from all other tissues. Methods for brain extraction have either been 1) validated but not fully automated, or 2) fully automated and informally proposed, but never formally validated. Aim To systematically analyze and validate the performance of FSL's brain extraction tool (BET) on head CT images of patients with intracranial hemorrhage. This was done by comparing the manual gold standard with the results of several versions of automatic brain extraction and by estimating the reliability of automated segmentation of longitudinal scans. The effects of the choice of BET parameters and data smoothing is studied and reported. Methods All images were thresholded using a 0 – 100 Hounsfield units (HU) range. In one variant of the pipeline, data were smoothed using a 3-dimensional Gaussian kernel (σ = 1mm3) and re-thresholded to 0 – 100 HU; in the other, data were not smoothed. BET was applied using 1 of 3 fractional intensity (FI) thresholds: 0.01, 0.1, or 0.35 and any holes in the brain mask were filled. For validation against a manual segmentation, 36 images from patients with intracranial hemorrhage were selected from 19 different centers from the MISTIE (Minimally Invasive Surgery plus recombinant-tissue plasminogen activator for Intracerebral Evacuation) stroke trial. Intracranial masks of the brain were manually created by one expert CT reader. The resulting brain tissue masks were quantitatively compared to the manual segmentations using sensitivity, specificity, accuracy, and the Dice Similarity Index (DSI). Brain extraction performance across smoothing and FI thresholds was compared using the Wilcoxon signed-rank test. The intracranial

  9. Metal artifact reduction strategies for improved attenuation correction in hybrid PET/CT imaging

    SciTech Connect

    Abdoli, Mehrsima; Dierckx, Rudi A. J. O.; Zaidi, Habib

    2012-06-15

    Metallic implants are known to generate bright and dark streaking artifacts in x-ray computed tomography (CT) images, which in turn propagate to corresponding functional positron emission tomography (PET) images during the CT-based attenuation correction procedure commonly used on hybrid clinical PET/CT scanners. Therefore, visual artifacts and overestimation and/or underestimation of the tracer uptake in regions adjacent to metallic implants are likely to occur and as such, inaccurate quantification of the tracer uptake and potential erroneous clinical interpretation of PET images is expected. Accurate quantification of PET data requires metal artifact reduction (MAR) of the CT images prior to the application of the CT-based attenuation correction procedure. In this review, the origins of metallic artifacts and their impact on clinical PET/CT imaging are discussed. Moreover, a brief overview of proposed MAR methods and their advantages and drawbacks is presented. Although most of the presented MAR methods are mainly developed for diagnostic CT imaging, their potential application in PET/CT imaging is highlighted. The challenges associated with comparative evaluation of these methods in a clinical environment in the absence of a gold standard are also discussed.

  10. Atlas image labeling of subcortical structures and vascular territories in brain CT images.

    PubMed

    Du, Kaifang; Zhang, Li; Nguyen, Tony; Ordy, Vincent; Fichte, Heinz; Ditt, Hendrik; Chefd'hotel, Christophe

    2013-01-01

    We propose a multi-atlas labeling method for subcortical structures and cerebral vascular territories in brain CT images. Each atlas image is registered to the query image by a non-rigid registration and the deformation is then applied to the labeling of the atlas image to obtain the labeling of the query image. Four label fusion strategies (single atlas, most similar atlas, major voting, and STAPLE) were compared. Image similarity values in non-rigid registration were calculated and used to select and rank atlases. Major voting fusion strategy gave the best accuracy, with DSC (Dice similarity coefficient) around 0.85 ± 0.03 for caudate, putamen, and thalamus. The experimental results also show that fusing more atlases does not necessarily yield higher accuracy and we should be able to improve accuracy and decrease computation cost at the same time by selecting a preferred set with the minimum number of atlases.

  11. Region quad-tree decomposition based edge detection for medical images.

    PubMed

    Dua, Sumeet; Kandiraju, Naveen; Chowriappa, Pradeep

    2010-05-28

    Edge detection in medical images has generated significant interest in the medical informatics community, especially in recent years. With the advent of imaging technology in biomedical and clinical domains, the growth in medical digital images has exceeded our capacity to analyze and store them for efficient representation and retrieval, especially for data mining applications. Medical decision support applications frequently demand the ability to identify and locate sharp discontinuities in an image for feature extraction and interpretation of image content, which can then be exploited for decision support analysis. However, due to the inherent high dimensional nature of the image content and the presence of ill-defined edges, edge detection using classical procedures is difficult, if not impossible, for sensitive and specific medical informatics-based discovery. In this paper, we propose a new edge detection technique based on the regional recursive hierarchical decomposition using quadtree and post-filtration of edges using a finite difference operator. We show that in medical images of common origin, focal and/or penumbral blurred edges can be characterized by an estimable intensity gradient. This gradient can further be used for dismissing false alarms. A detailed validation and comparison with related works on diabetic retinopathy images and CT scan images show that the proposed approach is efficient and accurate.

  12. Interactive Medical Image Segmentation using PDE Control of Active Contours

    PubMed Central

    Karasev, Peter; Kolesov, Ivan; Fritscher, Karl; Vela, Patricio; Mitchell, Phillip; Tannenbaum, Allen

    2014-01-01

    Segmentation of injured or unusual anatomic structures in medical imagery is a problem that has continued to elude fully automated solutions. In this paper, the goal of easy-to-use and consistent interactive segmentation is transformed into a control synthesis problem. A nominal level set PDE is assumed to be given; this open-loop system achieves correct segmentation under ideal conditions, but does not agree with a human expert's ideal boundary for real image data. Perturbing the state and dynamics of a level set PDE via the accumulated user input and an observer-like system leads to desirable closed-loop behavior. The input structure is designed such that a user can stabilize the boundary in some desired state without needing to understand any mathematical parameters. Effectiveness of the technique is illustrated with applications to the challenging segmentations of a patellar tendon in MR and a shattered femur in CT. PMID:23893712

  13. Material Science Image Analysis using Quant-CT in ImageJ

    SciTech Connect

    Ushizima, Daniela M.; Bianchi, Andrea G. C.; DeBianchi, Christina; Bethel, E. Wes

    2015-01-05

    We introduce a computational analysis workflow to access properties of solid objects using nondestructive imaging techniques that rely on X-ray imaging. The goal is to process and quantify structures from material science sample cross sections. The algorithms can differentiate the porous media (high density material) from the void (background, low density media) using a Boolean classifier, so that we can extract features, such as volume, surface area, granularity spectrum, porosity, among others. Our workflow, Quant-CT, leverages several algorithms from ImageJ, such as statistical region merging and 3D object counter. It also includes schemes for bilateral filtering that use a 3D kernel, for parallel processing of sub-stacks, and for handling over-segmentation using histogram similarities. The Quant-CT supports fast user interaction, providing the ability for the user to train the algorithm via subsamples to feed its core algorithms with automated parameterization. Quant-CT plugin is currently available for testing by personnel at the Advanced Light Source and Earth Sciences Divisions and Energy Frontier Research Center (EFRC), LBNL, as part of their research on porous materials. The goal is to understand the processes in fluid-rock systems for the geologic sequestration of CO2, and to develop technology for the safe storage of CO2 in deep subsurface rock formations. We describe our implementation, and demonstrate our plugin on porous material images. This paper targets end-users, with relevant information for developers to extend its current capabilities.

  14. Biomechanical deformable image registration of longitudinal lung CT images using vessel information

    NASA Astrophysics Data System (ADS)

    Cazoulat, Guillaume; Owen, Dawn; Matuszak, Martha M.; Balter, James M.; Brock, Kristy K.

    2016-07-01

    Spatial correlation of lung tissue across longitudinal images, as the patient responds to treatment, is a critical step in adaptive radiotherapy. The goal of this work is to expand a biomechanical model-based deformable registration algorithm (Morfeus) to achieve accurate registration in the presence of significant anatomical changes. Six lung cancer patients previously treated with conventionally fractionated radiotherapy were retrospectively evaluated. Exhale CT scans were obtained at treatment planning and following three weeks of treatment. For each patient, the planning CT was registered to the follow-up CT using Morfeus, a biomechanical model-based deformable registration algorithm. To model the complex response of the lung, an extension to Morfeus has been developed: an initial deformation was estimated with Morfeus consisting of boundary conditions on the chest wall and incorporating a sliding interface with the lungs. It was hypothesized that the addition of boundary conditions based on vessel tree matching would provide a robust reduction of the residual registration error. To achieve this, the vessel trees were segmented on the two images by thresholding a vesselness image based on the Hessian matrix’s eigenvalues. For each point on the reference vessel tree centerline, the displacement vector was estimated by applying a variant of the Demons registration algorithm between the planning CT and the deformed follow-up CT. An expert independently identified corresponding landmarks well distributed in the lung to compute target registration errors (TRE). The TRE was: 5.8+/- 2.9 , 3.4+/- 2.3 and 1.6+/- 1.3 mm after rigid registration, Morfeus and Morfeus with boundary conditions on the vessel tree, respectively. In conclusion, the addition of boundary conditions on the vessels significantly improved the accuracy in modeling the response of the lung and tumor over the course of radiotherapy. Minimizing and modeling these geometrical uncertainties will enable

  15. Registration and Summation of Respiratory-Gated or Breath-Hold PET Images Based on Deformation Estimation of Lung from CT Image

    PubMed Central

    Kanai, Masayuki; Tamai, Yoshitaka; Sakohira, Atsushi; Suga, Kazuyoshi

    2016-01-01

    Lung motion due to respiration causes image degradation in medical imaging, especially in nuclear medicine which requires long acquisition times. We have developed a method for image correction between the respiratory-gated (RG) PET images in different respiration phases or breath-hold (BH) PET images in an inconsistent respiration phase. In the method, the RG or BH-PET images in different respiration phases are deformed under two criteria: similarity of the image intensity distribution and smoothness of the estimated motion vector field (MVF). However, only these criteria may cause unnatural motion estimation of lung. In this paper, assuming the use of a PET-CT scanner, we add another criterion that is the similarity for the motion direction estimated from inhalation and exhalation CT images. The proposed method was first applied to a numerical phantom XCAT with tumors and then applied to BH-PET image data for seven patients. The resultant tumor contrasts and the estimated motion vector fields were compared with those obtained by our previous method. Through those experiments we confirmed that the proposed method can provide an improved and more stable image quality for both RG and BH-PET images. PMID:28096896

  16. Adaptive geodesic transform for segmentation of vertebrae on CT images

    NASA Astrophysics Data System (ADS)

    Gaonkar, Bilwaj; Shu, Liao; Hermosillo, Gerardo; Zhan, Yiqiang

    2014-03-01

    Vertebral segmentation is a critical first step in any quantitative evaluation of vertebral pathology using CT images. This is especially challenging because bone marrow tissue has the same intensity profile as the muscle surrounding the bone. Thus simple methods such as thresholding or adaptive k-means fail to accurately segment vertebrae. While several other algorithms such as level sets may be used for segmentation any algorithm that is clinically deployable has to work in under a few seconds. To address these dual challenges we present here, a new algorithm based on the geodesic distance transform that is capable of segmenting the spinal vertebrae in under one second. To achieve this we extend the theory of the geodesic distance transforms proposed in1 to incorporate high level anatomical knowledge through adaptive weighting of image gradients. Such knowledge may be provided by the user directly or may be automatically generated by another algorithm. We incorporate information 'learnt' using a previously published machine learning algorithm2 to segment the L1 to L5 vertebrae. While we present a particular application here, the adaptive geodesic transform is a generic concept which can be applied to segmentation of other organs as well.

  17. Evaluation of accuracy of 3D reconstruction images using multi-detector CT and cone-beam CT

    PubMed Central

    Kim, Mija; YI, Won-Jin; Heo, Min-Suk; Lee, Sam-Sun; Choi, Soon-Chul

    2012-01-01

    Purpose This study was performed to determine the accuracy of linear measurements on three-dimensional (3D) images using multi-detector computed tomography (MDCT) and cone-beam computed tomography (CBCT). Materials and Methods MDCT and CBCT were performed using 24 dry skulls. Twenty-one measurements were taken on the dry skulls using digital caliper. Both types of CT data were imported into OnDemand software and identification of landmarks on the 3D surface rendering images and calculation of linear measurements were performed. Reproducibility of the measurements was assessed using repeated measures ANOVA and ICC, and the measurements were statistically compared using a Student t-test. Results All assessments under the direct measurement and image-based measurements on the 3D CT surface rendering images using MDCT and CBCT showed no statistically difference under the ICC examination. The measurements showed no differences between the direct measurements of dry skull and the image-based measurements on the 3D CT surface rendering images (P>.05). Conclusion Three-dimensional reconstructed surface rendering images using MDCT and CBCT would be appropriate for 3D measurements. PMID:22474645

  18. Locally-constrained Boundary Regression for Segmentation of Prostate and Rectum in the Planning CT Images

    PubMed Central

    Shao, Yeqin; Gao, Yaozong; Wang, Qian; Yang, Xin; Shen, Dinggang

    2015-01-01

    Automatic and accurate segmentation of the prostate and rectum in planning CT images is a challenging task due to low image contrast, unpredictable organ (relative) position, and uncertain existence of bowel gas across different patients. Recently, regression forest was adopted for organ deformable segmentation on 2D medical images by training one landmark detector for each point on the shape model. However, it seems impractical for regression forest to guide 3D deformable segmentation as a landmark detector, due to large number of vertices in the 3D shape model as well as the difficulty in building accurate 3D vertex correspondence for each landmark detector. In this paper, we propose a novel boundary detection method by exploiting the power of regression forest for prostate and rectum segmentation. The contributions of this paper are as follows: 1) we introduce regression forest as a local boundary regressor to vote the entire boundary of a target organ, which avoids training a large number of landmark detectors and building an accurate 3D vertex correspondence for each landmark detector; 2) an auto-context model is integrated with regression forest to improve the accuracy of the boundary regression; 3) we further combine a deformable segmentation method with the proposed local boundary regressor for the final organ segmentation by integrating organ shape priors. Our method is evaluated on a planning CT image dataset with 70 images from 70 different patients. The experimental results show that our proposed boundary regression method outperforms the conventional boundary classification method in guiding the deformable model for prostate and rectum segmentations. Compared with other state-of-the-art methods, our method also shows a competitive performance. PMID:26439938

  19. Locally-constrained boundary regression for segmentation of prostate and rectum in the planning CT images.

    PubMed

    Shao, Yeqin; Gao, Yaozong; Wang, Qian; Yang, Xin; Shen, Dinggang

    2015-12-01

    Automatic and accurate segmentation of the prostate and rectum in planning CT images is a challenging task due to low image contrast, unpredictable organ (relative) position, and uncertain existence of bowel gas across different patients. Recently, regression forest was adopted for organ deformable segmentation on 2D medical images by training one landmark detector for each point on the shape model. However, it seems impractical for regression forest to guide 3D deformable segmentation as a landmark detector, due to large number of vertices in the 3D shape model as well as the difficulty in building accurate 3D vertex correspondence for each landmark detector. In this paper, we propose a novel boundary detection method by exploiting the power of regression forest for prostate and rectum segmentation. The contributions of this paper are as follows: (1) we introduce regression forest as a local boundary regressor to vote the entire boundary of a target organ, which avoids training a large number of landmark detectors and building an accurate 3D vertex correspondence for each landmark detector; (2) an auto-context model is integrated with regression forest to improve the accuracy of the boundary regression; (3) we further combine a deformable segmentation method with the proposed local boundary regressor for the final organ segmentation by integrating organ shape priors. Our method is evaluated on a planning CT image dataset with 70 images from 70 different patients. The experimental results show that our proposed boundary regression method outperforms the conventional boundary classification method in guiding the deformable model for prostate and rectum segmentations. Compared with other state-of-the-art methods, our method also shows a competitive performance.

  20. Simplified labeling process for medical image segmentation.

    PubMed

    Gao, Mingchen; Huang, Junzhou; Huang, Xiaolei; Zhang, Shaoting; Metaxas, Dimitris N

    2012-01-01

    Image segmentation plays a crucial role in many medical imaging applications by automatically locating the regions of interest. Typically supervised learning based segmentation methods require a large set of accurately labeled training data. However, thel labeling process is tedious, time consuming and sometimes not necessary. We propose a robust logistic regression algorithm to handle label outliers such that doctors do not need to waste time on precisely labeling images for training set. To validate its effectiveness and efficiency, we conduct carefully designed experiments on cervigram image segmentation while there exist label outliers. Experimental results show that the proposed robust logistic regression algorithms achieve superior performance compared to previous methods, which validates the benefits of the proposed algorithms.

  1. Estimating CT Image from MRI Data Using Structured Random Forest and Auto-context Model

    PubMed Central

    Huynh, Tri; Gao, Yaozong; Kang, Jiayin; Wang, Li; Zhang, Pei; Lian, Jun; Shen, Dinggang

    2015-01-01

    Computed tomography (CT) imaging is an essential tool in various clinical diagnoses and radiotherapy treatment planning. Since CT image intensities are directly related to positron emission tomography (PET) attenuation coefficients, they are indispensable for attenuation correction (AC) of the PET images. However, due to the relatively high dose of radiation exposure in CT scan, it is advised to limit the acquisition of CT images. In addition, in the new PET and magnetic resonance (MR) imaging scanner, only MR images are available, which are unfortunately not directly applicable to AC. These issues greatly motivate the development of methods for reliable estimate of CT image from its corresponding MR image of the same subject. In this paper, we propose a learning-based method to tackle this challenging problem. Specifically, we first partition a given MR image into a set of patches. Then, for each patch, we use the structured random forest to directly predict a CT patch as a structured output, where a new ensemble model is also used to ensure the robust prediction. Image features are innovatively crafted to achieve multi-level sensitivity, with spatial information integrated through only rigid-body alignment to help avoiding the error-prone inter-subject deformable registration. Moreover, we use an auto-context model to iteratively refine the prediction. Finally, we combine all of the predicted CT patches to obtain the final prediction for the given MR image. We demonstrate the efficacy of our method on two datasets: human brain and prostate images. Experimental results show that our method can accurately predict CT images in various scenarios, even for the images undergoing large shape variation, and also outperforms two state-of-the-art methods. PMID:26241970

  2. Reconstruction of 4D-CT from a Single Free-Breathing 3D-CT by Spatial-Temporal Image Registration

    PubMed Central

    Wu, Guorong; Wang, Qian; Lian, Jun; Shen, Dinggang

    2011-01-01

    In the radiation therapy of lung cancer, a free-breathing 3D-CT image is usually acquired in the treatment day for image-guided patient setup, by registering with the free-breathing 3D-CT image acquired in the planning day. In this way, the optimal dose plan computed in the planning day can be transferred onto the treatment day for cancer radiotherapy. However, patient setup based on the simple registration of the free-breathing 3D-CT images of the planning and the treatment days may mislead the radiotherapy, since the free-breathing 3D-CT is actually the mixed-phase image, with different slices often acquired from different respiratory phases. Moreover, a 4D-CT that is generally acquired in the planning day for improvement of dose planning is often ignored for guiding patient setup in the treatment day. To overcome these limitations, we present a novel two-step method to reconstruct the 4D-CT from a single free-breathing 3D-CT of the treatment day, by utilizing the 4D-CT model built in the planning day. Specifically, in the first step, we proposed a new spatial-temporal registration algorithm to align all phase images of the 4D-CT acquired in the planning day, for building a 4D-CT model with temporal correspondences established among all respiratory phases. In the second step, we first determine the optimal phase for each slice of the free-breathing (mixed-phase) 3D-CT of the treatment day by comparing with the 4D-CT of the planning day and thus obtain a sequence of partial 3D-CT images for the treatment day, each with only the incomplete image information in certain slices; and then we reconstruct a complete 4D-CT for the treatment day by warping the 4D-CT of the planning day (with complete information) to the sequence of partial 3D-CT images of the treatment day, under the guidance of the 4D-CT model built in the planning day. We have comprehensively evaluated our 4D-CT model building algorithm on a public lung image database, achieving the best registration

  3. Automatic Classification of Normal and Cancer Lung CT Images Using Multiscale AM-FM Features.

    PubMed

    Magdy, Eman; Zayed, Nourhan; Fakhr, Mahmoud

    2015-01-01

    Computer-aided diagnostic (CAD) systems provide fast and reliable diagnosis for medical images. In this paper, CAD system is proposed to analyze and automatically segment the lungs and classify each lung into normal or cancer. Using 70 different patients' lung CT dataset, Wiener filtering on the original CT images is applied firstly as a preprocessing step. Secondly, we combine histogram analysis with thresholding and morphological operations to segment the lung regions and extract each lung separately. Amplitude-Modulation Frequency-Modulation (AM-FM) method thirdly, has been used to extract features for ROIs. Then, the significant AM-FM features have been selected using Partial Least Squares Regression (PLSR) for classification step. Finally, K-nearest neighbour (KNN), support vector machine (SVM), naïve Bayes, and linear classifiers have been used with the selected AM-FM features. The performance of each classifier in terms of accuracy, sensitivity, and specificity is evaluated. The results indicate that our proposed CAD system succeeded to differentiate between normal and cancer lungs and achieved 95% accuracy in case of the linear classifier.

  4. Automatic Classification of Normal and Cancer Lung CT Images Using Multiscale AM-FM Features

    PubMed Central

    Magdy, Eman; Zayed, Nourhan; Fakhr, Mahmoud

    2015-01-01

    Computer-aided diagnostic (CAD) systems provide fast and reliable diagnosis for medical images. In this paper, CAD system is proposed to analyze and automatically segment the lungs and classify each lung into normal or cancer. Using 70 different patients' lung CT dataset, Wiener filtering on the original CT images is applied firstly as a preprocessing step. Secondly, we combine histogram analysis with thresholding and morphological operations to segment the lung regions and extract each lung separately. Amplitude-Modulation Frequency-Modulation (AM-FM) method thirdly, has been used to extract features for ROIs. Then, the significant AM-FM features have been selected using Partial Least Squares Regression (PLSR) for classification step. Finally, K-nearest neighbour (KNN), support vector machine (SVM), naïve Bayes, and linear classifiers have been used with the selected AM-FM features. The performance of each classifier in terms of accuracy, sensitivity, and specificity is evaluated. The results indicate that our proposed CAD system succeeded to differentiate between normal and cancer lungs and achieved 95% accuracy in case of the linear classifier. PMID:26451137

  5. Multi-detector CT imaging in the postoperative orthopedic patient with metal hardware.

    PubMed

    Vande Berg, Bruno; Malghem, Jacques; Maldague, Baudouin; Lecouvet, Frederic

    2006-12-01

    Multi-detector CT imaging (MDCT) becomes routine imaging modality in the assessment of the postoperative orthopedic patients with metallic instrumentation that degrades image quality at MR imaging. This article reviews the physical basis and CT appearance of such metal-related artifacts. It also addresses the clinical value of MDCT in postoperative orthopedic patients with emphasis on fracture healing, spinal fusion or arthrodesis, and joint replacement. MDCT imaging shows limitations in the assessment of the bone marrow cavity and of the soft tissues for which MR imaging remains the imaging modality of choice despite metal-related anatomic distortions and signal alteration.

  6. Optimization of Proton CT Detector System and Image Reconstruction Algorithm for On-Line Proton Therapy.

    PubMed

    Lee, Chae Young; Song, Hankyeol; Park, Chan Woo; Chung, Yong Hyun; Kim, Jin Sung; Park, Justin C

    2016-01-01

    The purposes of this study were to optimize a proton computed tomography system (pCT) for proton range verification and to confirm the pCT image reconstruction algorithm based on projection images generated with optimized parameters. For this purpose, we developed a new pCT scanner using the Geometry and Tracking (GEANT) 4.9.6 simulation toolkit. GEANT4 simulations were performed to optimize the geometric parameters representing the detector thickness and the distance between the detectors for pCT. The system consisted of four silicon strip detectors for particle tracking and a calorimeter to measure the residual energies of the individual protons. The optimized pCT system design was then adjusted to ensure that the solution to a CS-based convex optimization problem would converge to yield the desired pCT images after a reasonable number of iterative corrections. In particular, we used a total variation-based formulation that has been useful in exploiting prior knowledge about the minimal variations of proton attenuation characteristics in the human body. Examinations performed using our CS algorithm showed that high-quality pCT images could be reconstructed using sets of 72 projections within 20 iterations and without any streaks or noise, which can be caused by under-sampling and proton starvation. Moreover, the images yielded by this CS algorithm were found to be of higher quality than those obtained using other reconstruction algorithms. The optimized pCT scanner system demonstrated the potential to perform high-quality pCT during on-line image-guided proton therapy, without increasing the imaging dose, by applying our CS based proton CT reconstruction algorithm. Further, we make our optimized detector system and CS-based proton CT reconstruction algorithm potentially useful in on-line proton therapy.

  7. Optimization of Proton CT Detector System and Image Reconstruction Algorithm for On-Line Proton Therapy

    PubMed Central

    Lee, Chae Young; Song, Hankyeol; Park, Chan Woo; Chung, Yong Hyun; Park, Justin C.

    2016-01-01

    The purposes of this study were to optimize a proton computed tomography system (pCT) for proton range verification and to confirm the pCT image reconstruction algorithm based on projection images generated with optimized parameters. For this purpose, we developed a new pCT scanner using the Geometry and Tracking (GEANT) 4.9.6 simulation toolkit. GEANT4 simulations were performed to optimize the geometric parameters representing the detector thickness and the distance between the detectors for pCT. The system consisted of four silicon strip detectors for particle tracking and a calorimeter to measure the residual energies of the individual protons. The optimized pCT system design was then adjusted to ensure that the solution to a CS-based convex optimization problem would converge to yield the desired pCT images after a reasonable number of iterative corrections. In particular, we used a total variation-based formulation that has been useful in exploiting prior knowledge about the minimal variations of proton attenuation characteristics in the human body. Examinations performed using our CS algorithm showed that high-quality pCT images could be reconstructed using sets of 72 projections within 20 iterations and without any streaks or noise, which can be caused by under-sampling and proton starvation. Moreover, the images yielded by this CS algorithm were found to be of higher quality than those obtained using other reconstruction algorithms. The optimized pCT scanner system demonstrated the potential to perform high-quality pCT during on-line image-guided proton therapy, without increasing the imaging dose, by applying our CS based proton CT reconstruction algorithm. Further, we make our optimized detector system and CS-based proton CT reconstruction algorithm potentially useful in on-line proton therapy. PMID:27243822

  8. An assessment of the potential for interpretation of CT images by radiological technologists

    NASA Astrophysics Data System (ADS)

    Matsumoto, Toru; Matsumoto, Mitsuomi; Nagao, Keiichi; Kakinuma, Ryutaro; Sone, Shusuke; Furukawa, Akira; Fujino, Yuichi; Wada, Shinichi; Yamamoto, Shinji; Murao, Kohei; Endo, Masahiro

    2005-04-01

    The increasing number of CT images to be interpreted in mass screening requires radiologists to interpret a huge number of CT images, and the capacity for screening has therefore been limited by the capacity to process images. To remedy this situation we considered paramedical staff, especially radiological technologists, as "potential screeners," and investigated their capacity to detect abnormalities in CT images of lung cancer screening with and without the assistance of a computer-aided diagnosis (CAD) system. We then compared their performances with those of physicians. A set of 100 slices of thoracic CT images from 100 cases ( 73 abnormal and 27 normal), one slice per case, was interpreted by 43 paramedical college students. A second interpretation by the students was performed after they had been instructed on how to interpret CT images, and a third interpretation was assisted by a virtual CAD system. We calculated the areas under the ROC curve (Az values) for both students and physicians. For the first set of interpretations, the Az values of 40% out of students placed the Az values within the range of Az values of the physicians, which varied from 0.870 to 0.964. For the second set of interpretations after the students had been instructed on CT image interpretation, the students' rate was 86%, and for the third set of virtual CAD-assisted interpretations it was 95%. The performance of paramedical college students in detecting abnormalities from thoracic CT images proved to be sufficient to qualify them as "potential screeners."

  9. CT segmentation of dental shapes by anatomy-driven reformation imaging and B-spline modelling.

    PubMed

    Barone, S; Paoli, A; Razionale, A V

    2016-06-01

    Dedicated imaging methods are among the most important tools of modern computer-aided medical applications. In the last few years, cone beam computed tomography (CBCT) has gained popularity in digital dentistry for 3D imaging of jawbones and teeth. However, the anatomy of a maxillofacial region complicates the assessment of tooth geometry and anatomical location when using standard orthogonal views of the CT data set. In particular, a tooth is defined by a sub-region, which cannot be easily separated from surrounding tissues by only considering pixel grey-intensity values. For this reason, an image enhancement is usually necessary in order to properly segment tooth geometries. In this paper, an anatomy-driven methodology to reconstruct individual 3D tooth anatomies by processing CBCT data is presented. The main concept is to generate a small set of multi-planar reformation images along significant views for each target tooth, driven by the individual anatomical geometry of a specific patient. The reformation images greatly enhance the clearness of the target tooth contours. A set of meaningful 2D tooth contours is extracted and used to automatically model the overall 3D tooth shape through a B-spline representation. The effectiveness of the methodology has been verified by comparing some anatomy-driven reconstructions of anterior and premolar teeth with those obtained by using standard tooth segmentation tools. Copyright © 2015 John Wiley & Sons, Ltd.

  10. Medical imaging displays and their use in image interpretation.

    PubMed

    Kagadis, George C; Walz-Flannigan, Alisa; Krupinski, Elizabeth A; Nagy, Paul G; Katsanos, Konstantinos; Diamantopoulos, Athanasios; Langer, Steve G

    2013-01-01

    The adequate and repeatable performance of the image display system is a key element of information technology platforms in a modern radiology department. However, despite the wide availability of high-end computing platforms and advanced color and gray-scale monitors, the quality and properties of the final displayed medical image may often be inadequate for diagnostic purposes if the displays are not configured and maintained properly. In this article-an expanded version of the Radiological Society of North America educational module "Image Display"-the authors discuss fundamentals of image display hardware, quality control and quality assurance processes for optimal image interpretation settings, and parameters of the viewing environment that influence reader performance. Radiologists, medical physicists, and other allied professionals should strive to understand the role of display technology and proper usage for a quality radiology practice. The display settings and display quality control and quality assurance processes described in this article can help ensure high standards of perceived image quality and image interpretation accuracy.

  11. WE-D-207-00: CT Lung Cancer Screening and the Medical Physicist: Moving Forward

    SciTech Connect

    2015-06-15

    In the United States, Lung Cancer is responsible for more cancer deaths than the next four cancers combined. In addition, the 5 year survival rate for lung cancer patients has not improved over the past 40 to 50 years. To combat this deadly disease, in 2002 the National Cancer Institute launched a very large Randomized Control Trial called the National Lung Screening Trial (NLST). This trial would randomize subjects who had substantial risk of lung cancer (due to age and smoking history) into either a Chest X-ray arm or a low dose CT arm. In November 2010, the National Cancer Institute announced that the NLST had demonstrated 20% fewer lung cancer deaths among those who were screened with low-dose CT than with chest X-ray. In December 2013, the US Preventive Services Task Force recommended the use of Lung Cancer Screening using low dose CT and a little over a year later (Feb. 2015), CMS announced that Medicare would also cover Lung Cancer Screening using low dose CT. Thus private and public insurers are required to provide Lung Cancer Screening programs using CT to the appropriate population(s). The purpose of this Symposium is to inform medical physicists and prepare them to support the implementation of Lung Screening programs. This Symposium will focus on the clinical aspects of lung cancer screening, requirements of a screening registry for systematically capturing and tracking screening patients and results (such as required Medicare data elements) as well as the role of the medical physicist in screening programs, including the development of low dose CT screening protocols. Learning Objectives: To understand the clinical basis and clinical components of a lung cancer screening program, including eligibility criteria and other requirements. To understand the data collection requirements, workflow, and informatics infrastructure needed to support the tracking and reporting components of a screening program. To understand the role of the medical physicist in

  12. Machine learning for medical images analysis.

    PubMed

    Criminisi, A

    2016-10-01

    This article discusses the application of machine learning for the analysis of medical images. Specifically: (i) We show how a special type of learning models can be thought of as automatically optimized, hierarchically-structured, rule-based algorithms, and (ii) We discuss how the issue of collecting large labelled datasets applies to both conventional algorithms as well as machine learning techniques. The size of the training database is a function of model complexity rather than a characteristic of machine learning methods.

  13. Renal Cell Carcinoma with Paraneoplastic Manifestations: Imaging with CT and F-18 FDG PET/CT.

    PubMed

    Nguyen, Ba D; Roarke, Michael C

    2007-01-01

    We present a case of renal cell carcinoma with prominent inflammatory and paraneoplastic manifestations. The initial CT detection of renal malignancy and subsequent post-therapeutic F-18 FDG PET/CT diagnosis of occult osseous metastasis were based on the patient's anemia, thrombocytosis and abnormally increased levels of serum C-reactive protein.

  14. Computerized characterization of lung nodule subtlety using thoracic CT images

    NASA Astrophysics Data System (ADS)

    He, Xin; Sahiner, Berkman; Gallas, Brandon D.; Chen, Weijie; Petrick, Nicholas

    2014-02-01

    The goal of this work is to design computerized image analysis techniques for automatically characterizing lung nodule subtlety in CT images. Automated subtlety estimation methods may help in computer-aided detection (CAD) assessment by quantifying dataset difficulty and facilitating comparisons among different CAD algorithms. A dataset containing 813 nodules from 499 patients was obtained from the Lung Image Database Consortium. Each nodule was evaluated by four radiologists regarding nodule subtlety using a 5-point rating scale (1: most subtle). We developed a 3D technique for segmenting lung nodules using a prespecified initial ROI. Texture and morphological features were automatically extracted from the segmented nodules and their margins. The dataset was partitioned into trainers and testers using a 1:1 ratio. An artificial neural network (ANN) was trained with average reader subtlety scores as the reference. Effective features for characterizing nodule subtlety were selected based on the training set using the ANN and a stepwise feature selection method. The performance of the classifier was evaluated using prediction probability (PK) as an agreement measure, which is considered a generalization of the area under the receiver operating characteristic curve when the reference standard is multi-level. Using an ANN classifier trained with a set of 2 features (selected from a total of 30 features), including compactness and average gray value, the test concordance between computer scores and the average reader scores was 0.789 ± 0.014. Our results show that the proposed method had strong agreement with the average of subtlety scores provided by radiologists.

  15. Paediatric cerebrovascular CT angiography—towards better image quality

    PubMed Central

    Thust, Stefanie C.; Chong, Wui Khean Kling; Gunny, Roxana; Mazumder, Asif; Poitelea, Marius; Welsh, Anna; Ederies, Ash

    2014-01-01

    Background Paediatric cerebrovascular CT angiography (CTA) can be challenging to perform due to variable cardiovascular physiology between different age groups and the risk of movement artefact. This analysis aimed to determine what proportion of CTA at our institution was of diagnostic quality and identify technical factors which could be improved. Materials and methods a retrospective analysis of 20 cases was performed at a national paediatric neurovascular centre assessing image quality with a subjective scoring system and Hounsfield Unit (HU) measurements. Demographic data, contrast dose, flow rate and triggering times were recorded for each patient. Results Using a qualitative scoring system, 75% of studies were found to be of diagnostic quality (n=9 ‘good’, n=6 ‘satisfactory’) and 25% (n=5) were ‘poor’. Those judged subjectively to be poor had arterial contrast density measured at less than 250 HU. Increased arterial opacification was achieved for cases performed with an increased flow rate (2.5-4 mL/s) and higher intravenous contrast dose (2 mL/kg). Triggering was found to be well timed in nine cases, early in four cases and late in seven cases. Of the scans triggered early, 75% were poor. Of the scans triggered late, less (29%) were poor. Conclusions High flow rates (>2.5 mL/s) were a key factor for achieving high quality paediatric cerebrovascular CTA imaging. However, appropriate triggering by starting the scan immediately on contrast opacification of the monitoring vessel plays an important role and could maintain image quality when flow rates were lower. Early triggering appeared more detrimental than late. PMID:25525579

  16. Self-guided clinical cases for medical students based on postmortem CT scans of cadavers.

    PubMed

    Bohl, Michael; Francois, Webster; Gest, Thomas

    2011-07-01

    In the summer of 2009, we began full body computed tomography (CT) scanning of the pre-embalmed cadavers in the University of Michigan Medical School (UMMS) dissection lab. We theorized that implementing web-based, self-guided clinical cases based on postmortem CT (PMCT) scans would result in increased student appreciation for the clinical relevance of anatomy, increased knowledge of cross-sectional anatomy, and increased ability to identify common pathologies on CT scans. The PMCT scan of each cadaver was produced as a DICOM dataset, and then converted into a Quicktime movie file using Osirix software. Clinical cases were researched and written by the authors, and consist of at least one Quicktime movie of a PMCT scan surrounded by a novel navigation interface. To assess the value of these clinical cases we surveyed medical students at UMMS who are currently using the clinical cases in their coursework. Students felt the clinical cases increased the clinical relevance of anatomy (mean response 7.77/10), increased their confidence finding anatomical structures on CT (7.00/10), and increased their confidence recognizing common pathologies on CT (6.17/10). Students also felt these clinical cases helped them synthesize material from numerous courses into an overall picture of a given disease process (7.01/10). These results support the conclusion that our clinical cases help to show students why the anatomy they are learning is foundational to their other coursework. We would recommend the use of similar clinical cases to any medical school utilizing cadaver dissection as a primary teaching method in anatomy education.

  17. Comparison of stroke infarction between CT perfusion and diffusion weighted imaging: preliminary results

    NASA Astrophysics Data System (ADS)

    Abd. Rahni, Ashrani Aizzuddin; Arka, Israna Hossain; Chellappan, Kalaivani; Mukari, Shahizon Azura; Law, Zhe Kang; Sahathevan, Ramesh

    2016-03-01

    In this paper we present preliminary results of comparison of automatic segmentations of the infarct core, between that obtained from CT perfusion (based on time to peak parameter) and diffusion weighted imaging (DWI). For each patient, the two imaging volumes were automatically co-registered to a common frame of reference based on an acquired CT angiography image. The accuracy of image registration is measured by the overlap of the segmented brain from both images (CT perfusion and DWI), measured within their common field of view. Due to the limitations of the study, DWI was acquired as a follow up scan up to a week after initial CT based imaging. However, we found significant overlap of the segmented brain (Jaccard indices of approximately 0.8) and the percentage of infarcted brain tissue from the two modalities were still fairly highly correlated (correlation coefficient of approximately 0.9). The results are promising with more data needed in future for clinical inference.

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

    SciTech Connect

    Madhogarhia, Manish; Munshi, P.; Lukose, Sijo; Subramanian, M. P.; Muralidhar, C.

    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 scan 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.

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

    NASA Astrophysics Data System (ADS)

    Madhogarhia, Manish; Munshi, P.; Lukose, Sijo; Subramanian, M. P.; Muralidhar, C.

    2008-09-01

    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 scan 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.

  20. Development of Prior Image-Based, High-Quality, Low-Dose Kilovoltage Cone Beam CT for Use in Adaptive Radiotherapy of Prostate Cancer

    DTIC Science & Technology

    2013-05-01

    mathematically ready for reconstruction. 1.1.4 Scatter compensation for synthesized physical phantom data Compared to diagnostic CT where X - ray beam spanning a...Truncated, Diagnostic -CT Data", SPIE Medical Imaging, Lake Buena Vista, Florida, 2013 37. X . Han, E. Pearson, C. A. Pelizzari, X . Pan, “Investigation of...Prince, C. A. Pelizzari, and X . Pan,“Evaluation of sparse-view reconstruction from flat - panel -detector cone-beam CT,” Physics in Medicine and Biology

  1. WE-D-9A-02: Automated Landmark-Guided CT to Cone-Beam CT Deformable Image Registration

    SciTech Connect

    Kearney, V; Gu, X; Chen, S; Jiang, L; Liu, H; Chiu, T; Yordy, J; Nedzi, L; Mao, W

    2014-06-15

    Purpose: The anatomical changes that occur between the simulation CT and daily cone-beam CT (CBCT) are investigated using an automated landmark-guided deformable image registration (LDIR) algorithm with simultaneous intensity correction. LDIR was designed to be accurate in the presence of tissue intensity mismatch and heavy noise contamination. Method: An auto-landmark generation algorithm was used in conjunction with a local small volume (LSV) gradient matching search engine to map corresponding landmarks between the CBCT and planning CT. The LSVs offsets were used to perform an initial deformation, generate landmarks, and correct local intensity mismatch. The landmarks act as stabilizing controlpoints in the Demons objective function. The accuracy of the LDIR algorithm was evaluated on one synthetic case with ground truth and data of ten head and neck cancer patients. The deformation vector field (DVF) accuracy was accessed using a synthetic case. The Root mean square error of the 3D canny edge (RMSECE), mutual information (MI), and feature similarity index metric (FSIM) were used to access the accuracy of LDIR on the patient data. The quality of the corresponding deformed contours was verified by an attending physician. Results: The resulting 90 percentile DVF error for the synthetic case was within 5.63mm for the original demons algorithm, 2.84mm for intensity correction alone, 2.45mm using controlpoints without intensity correction, and 1.48 mm for the LDIR algorithm. For the five patients the mean RMSECE of the original CT, Demons deformed CT, intensity corrected Demons CT, control-point stabilized deformed CT, and LDIR CT was 0.24, 0.26, 0.20, 0.20, and 0.16 respectively. Conclusion: LDIR is accurate in the presence of multimodal intensity mismatch and CBCT noise contamination. Since LDIR is GPU based it can be implemented with minimal additional strain on clinical resources. This project has been supported by a CPRIT individual investigator award RP11032.

  2. Low contrast detectability performance of model observers based on CT phantom images: kVp influence.

    PubMed

    Hernandez-Giron, I; Calzado, A; Geleijns, J; Joemai, R M S; Veldkamp, W J H

    2015-11-01

    This paper studies low contrast detectability (LCD) performance of two model observers in CT phantom images acquired at different kVp levels and compares the results with humans in a 2-alternative forced choice experiment (2-AFC). Images of the Catphan phantom with objects of different contrasts (0.5 and 1%) and diameters (2-15 mm) were acquired in an Aquilion ONE 320-detector row CT (Toshiba Medical Systems, Tokyo, Japan), in two experiments, selecting (80-100-120-135 kV) with fixed mAs and varying the mAs to keep the dose constant, respectively. Four human observers evaluated the objects visibility obtaining a proportion correct (PC) for each case. LCD was also analyzed with two model observers (non-prewhitening matched filter with an eye filter, NPWE, and channelized Hotelling observer with Gabor channels, CHO). Object contrast was affected by kV, with differences up to 17% between the lowest and highest kV. Both models overestimated human performance and were corrected by efficiency and internal noise factors. The NPWE model reproduced better the human PC values trends showing Pearson's correlation coefficients ≥0.976 (0.954-0.987, 95% CI) for both experiments, whereas for CHO they were ≥0.706 (0.493-0.839). Bland-Altman plots showed better agreement between NPWE and humans being the average difference Δ and the range of the differences Δ±2σ (σ, standard deviation) of Δ=-0.3%, Δ±2σ = [-4.0%,4.5%]. For CHO, Δ=-1.2%, Δ± 2σ= [-10.7%,8.3%]. The NPWE model can be a useful tool to predict human performance in CT low contrast detection tasks in a standard phantom and be potentially used in protocol optimization based on kV selection.

  3. Xenon-enhanced CT imaging of local pulmonary ventilation

    NASA Astrophysics Data System (ADS)

    Tajik, Jehangir K.; Tran, Binh Q.; Hoffman, Eric A.

    1996-04-01

    We are using the unique features of electron beam CT (EBCT) in conjunction with respiratory and cardiac gating to explore the use of non-radioactive xenon gas as a pulmonary ventilation contrast agent. The goal is to construct accurate and quantitative high-resolution maps of local pulmonary ventilation in humans. We are evaluating xenon-enhanced computed tomography in the pig model with dynamic tracer washout/dilution and single breath inhalation imaging protocols. Scanning is done via an EBCT scanner which offers 50 msec scan aperture speeds. CT attenuation coefficients (image gray scale value) show a linear increase with xenon concentration (r equals 0.99). We measure a 1.55 Hounsfield Unit (HU) enhancement (kV equals 130, mA equals 623) per percentage increase in xenon gas concentration giving an approximately 155 HU enhancement with 100% xenon gas concentration as measured in a plexiglass super-syringe. Early results indicate that a single breath (from functional residual capacity to total lung capacity) of 100% xenon gas provides an average 32 +/- 1.85 (SE) HU enhancement in the lung parenchyma (maximum 50 HU) and should not encounter unwanted xenon side effects. However, changes in lung density occurring during even short breath holds (as short as 10 seconds) may limit using a single breath technique to synchronous volumetric scanning, currently possible only with EBCT. Preliminary results indicate close agreement between measured regional xenon concentration-time curves and theoretical predictions for the same sample. More than 10 breaths with inspirations to as high as 25 cmH2O airway pressure were needed to clear tracer from all lung regions and some regions had nearly linear rather than mono-exponential clearance curves. When regional parenchymal xenon concentration-time curves were analyzed, vertical gradients in ventilation and redistribution of ventilation at higher inspiratory flow rates were consistent with known pulmonary physiology. We present

  4. Managing waiting times in diagnostic medical imaging

    PubMed Central

    Nuti, Sabina; Vainieri, Milena

    2012-01-01

    Objective This paper aims to analyse the variation in the delivery of diagnostic imaging services in order to suggest possible solutions for the reduction of waiting times, increase the quality of services and reduce financial costs. Design This study provides a logic model to manage waiting times in a regional context. Waiting times measured per day were compared on the basis of the variability in the use rates of CT and MRI examinations in Tuscany for the population, as well as on the basis of the capacity offered with respect to the number of radiologists available. The analysis was performed at the local health authority level to support the decision-making process of local managers. Setting Diagnostic imaging services, in particular the CT and MRI examinations. The study involved all the 12 local health authorities that provide services for 3.7 million inhabitants of the Italian Tuscany Region. Primary and secondary outcome measures Participants: the study uses regional administrative data on outpatients and survey data on inpatient diagnostic examinations in order to measure productivity. Primary and secondary outcome measures The study uses the volumes per 1000 inhabitants, the days of waiting times and the number of examinations per radiologist. Variability was measured using the traditional SD measures. Results A significant variation in areas considered homogeneous in terms of age, gender or mortality may indicate that the use of radiological services is not optimal and underuse or overuse occurs and that there is room for improvement in the service organisation. Conclusions Considering that there is a high level of variability among district use rates and waiting times, this study provides managers with a specific tool to find the cause of the problem, identify a possible solution, assess the financial impact and initiate the eventual reduction of waste. PMID:23242480

  5. Imaging of Orthotopic Glioblastoma Xenografts in Mice Using a Clinical CT Scanner: Comparison with Micro-CT and Histology

    PubMed Central

    Kirschner, Stefanie; Mürle, Bettina; Felix, Manuela; Arns, Anna; Groden, Christoph; Wenz, Frederik; Hug, Andreas; Glatting, Gerhard; Kramer, Martin

    2016-01-01

    Purpose There is an increasing need for small animal in vivo imaging in murine orthotopic glioma models. Because dedicated small animal scanners are not available ubiquitously, the applicability of a clinical CT scanner for visualization and measurement of intracerebrally growing glioma xenografts in living mice was validated. Materials and Methods 2.5x106 U87MG cells were orthotopically implanted in NOD/SCID/ᵞc-/- mice (n = 9). Mice underwent contrast-enhanced (300 μl Iomeprol i.v.) imaging using a micro-CT (80 kV, 75 μAs, 360° rotation, 1,000 projections, scan time 33 s, resolution 40 x 40 x 53 μm) and a clinical CT scanner (4-row multislice detector; 120 kV, 150 mAs, slice thickness 0.5 mm, feed rotation 0.5 mm, resolution 98 x 98 x 500 μm). Mice were sacrificed and the brain was worked up histologically. In all modalities tumor volume was measured by two independent readers. Contrast-to-noise ratio (CNR) and Signal-to-noise ratio (SNR) were measured from reconstructed CT-scans (0.5 mm slice thickness; n = 18). Results Tumor volumes (mean±SD mm3) were similar between both CT-modalities (micro-CT: 19.8±19.0, clinical CT: 19.8±18.8; Wilcoxon signed-rank test p = 0.813). Moreover, between reader analyses for each modality showed excellent agreement as demonstrated by correlation analysis (Spearman-Rho >0.9; p<0.01 for all correlations). Histologically measured tumor volumes (11.0±11.2) were significantly smaller due to shrinkage artifacts (p<0.05). CNR and SNR were 2.1±1.0 and 1.1±0.04 for micro-CT and 23.1±24.0 and 1.9±0.7 for the clinical CTscanner, respectively. Conclusion Clinical CT scanners may reliably be used for in vivo imaging and volumetric analysis of brain tumor growth in mice. PMID:27829015

  6. [Quality control of the research on mechanisms of acupuncture therapy by using PET-CT imaging techniques].

    PubMed

    Liu, Mai-lan; Lan, Lei; Zeng, Fang; Li, Xue-zhi; Liu, Xu-guang; Liang, Fan-rong

    2010-02-01

    Combining the functional metabolic imaging and anatomical imaging, PET-CT stands for the highest level of current nuclear medical imaging techniques, and has been applying increasingly in acupuncture studies. However, owning to complexity of the brain function and sensitivity of brain metabolism, the lower reproducibility of cerebral function imaging even may reverse many results. This has been provoked more and more attention by researchers. Its main cause is intimately related to poor experimental methodology. For this reason, the present paper raises the quality control of the research on mechanisms of acupuncture in the process of application of PET-CT techniques from (1) the included standards of participants, (2) the preparation of participants during the scanning process of PET-CT, (3) the setting of the scanning parameters, (4) the used machine and the imaging reagent, (5) the analysis of dada, (6) the standardization of acupuncture manipulation, and (7) the designs of the acupuncture operation, needling opportunity and scanning opportunity, hoping to offer some beneficial information for the coming researches.

  7. 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.

  8. Correlation between model observer and human observer performance in CT imaging when lesion location is uncertain

    NASA Astrophysics Data System (ADS)

    Leng, Shuai; Yu, Lifeng; Chen, Lingyun; Ramirez Giraldo, Juan C.; McCollough, Cynthia H.

    2012-03-01

    The purpose of this study is to investigate how well model observer can correlate with human observer in the lesion detection and localization task when the location of lesion is uncertain in CT imaging. A 35 × 26 cm oblong-shaped water phantom was scanned with and without two cylindrical rods (3 mm and 5 mm diameters) to simulate lesions with - 15HU contrast. Scans were repeated 100 times with the rods and 100 times without for each of 4 dose levels. Signal and background images were generated by selecting ROIs with 128x128 pixels, with the location of signal in each ROI randomly distributed. Human observer studies were conducted as three medical physicists identified the presence or absence of lesion, indicated the lesion location in each image and scored confidence level with a 6-point scale. ROC curves were fitted and area under curve (AUC) was calculated. The same data set was also analyzed using a Channelized Hottelling model observer with Gabor channels. Internal noise was added to the test variables for model observer study. AUC of ROC and LROC curves were calculated using non-parametric approach. The performance of human observer and model observer was compared. The Peason's product-moment correlation coefficients were 0.994 and 0.998 for 3mm and 5mm diameter lesions in ROC analysis and 0.987 and 0.999 in LROC analysis, indicating that model observer performance was highly correlated with the human observer performance for different size of lesions and different dose levels when signal location is uncertain. These results provide the potential of using model observer that correlates with human observer to assess CT image quality, optimize scanning protocol and reduce radiation dose.

  9. GPU-accelerated Block Matching Algorithm for Deformable Registration of Lung CT Images

    PubMed Central

    Li, Min; Xiang, Zhikang; Xiao, Liang; Castillo, Edward; Castillo, Richard; Guerrero, Thomas

    2016-01-01

    Deformable registration (DR) is a key technology in the medical field. However, many of the existing DR methods are time-consuming and the registration accuracy needs to be improved, which prevents their clinical applications. In this study, we propose a parallel block matching algorithm for lung CT image registration, in which the sum of squared difference metric is modified as the cost function and the moving least squares approach is used to generate the full displacement field. The algorithm is implemented on Graphic Processing Unit (GPU) with the Compute Unified Device Architecture (CUDA). Results show that the proposed parallel block matching method achieves a fast runtime while maintaining an average registration error (standard deviation) of 1.08 (0.69) mm. PMID:28042622

  10. GPU-accelerated Block Matching Algorithm for Deformable Registration of Lung CT Images.

    PubMed

    Li, Min; Xiang, Zhikang; Xiao, Liang; Castillo, Edward; Castillo, Richard; Guerrero, Thomas

    2015-12-01

    Deformable registration (DR) is a key technology in the medical field. However, many of the existing DR methods are time-consuming and the registration accuracy needs to be improved, which prevents their clinical applications. In this study, we propose a parallel block matching algorithm for lung CT image registration, in which the sum of squared difference metric is modified as the cost function and the moving least squares approach is used to generate the full displacement field. The algorithm is implemented on Graphic Processing Unit (GPU) with the Compute Unified Device Architecture (CUDA). Results show that the proposed parallel block matching method achieves a fast runtime while maintaining an average registration error (standard deviation) of 1.08 (0.69) mm.

  11. Image reconstruction and image quality evaluation for a 16-slice CT scanner.

    PubMed

    Flohr, Th; Stierstorfer, K; Bruder, H; Simon, J; Polacin, A; Schaller, S

    2003-05-01

    We present a theoretical overview and a performance evaluation of a novel approximate reconstruction algorithm for cone-beam spiral CT, the adaptive multiple plane reconstruction (AMPR), which has been introduced by Schaller, Flohr et al. [Proc. SPIE Int. Symp. Med. Imag. 4322, 113-127 (2001)] AMPR has been implemented in a recently introduced 16-slice CT scanner. We present a detailed algorithmic description of AMPR which allows for a free selection of the spiral pitch. We show that dose utilization is better than 90% independent of the pitch. We give an overview on the z-reformation functions chosen to allow for a variable selection of the spiral slice width at arbitrary pitch values. To investigate AMPR image quality we present images of anthropomorphic phantoms and initial patient results. We present measurements of spiral slice sensitivity profiles (SSPs) and measurements of the maximum achievable transverse resolution, both in the isocenter and off-center. We discuss the pitch dependence of image noise measured in a centered 20 cm water phantom. Using the AMPR approach, cone-beam artifacts are considerably reduced for the 16-slice scanner investigated. Image quality in MPRs is independent of the pitch and equivalent to a single-slice CT system at pitch p approximately 1.5. The full width at half-maximum (FWHM) of the spiral SSPs shows only minor variations as a function of the pitch, nominal, and measured values differ by less than 0.2 mm. With 16 x 0.75 mm collimation, the measured FWHM of the smallest reconstructed slice is about 0.9 mm. Using this slice width and overlapping image reconstruction, cylindrical holes with 0.6 mm diameter can be resolved in a z-resolution phantom. Image noise for constant effective mAs is nearly independent of the pitch. Measured and theoretically expected dose utilization are in good agreement. Meanwhile, clinical practice has demonstrated the excellent image quality and the increased diagnostic capability that is obtained

  12. TU-G-207-01: CT Imaging Using Energy-Sensitive Photon-Counting Detectors

    SciTech Connect

    Taguchi, K.

    2015-06-15

    Last few years has witnessed the development of novel of X-ray imaging modalities, such as spectral CT, phase contrast CT, and X-ray acoustic/fluorescence/luminescence imaging. This symposium will present the recent advances of these emerging X-ray imaging modalities and update the attendees with knowledge in various related topics, including X-ray photon-counting detectors, X-ray physics underlying the emerging applications beyond the traditional X-ray imaging, image reconstruction for the novel modalities, characterization and evaluation of the systems, and their practical implications. In addition, the concept and practical aspects of X-ray activatable targeted nanoparticles for molecular X-ray imaging will be discussed in the context of X-ray fluorescence and luminescence CT. Learning Objectives: Present background knowledge of various emerging X-ray imaging techniques, such as spectral CT, phase contrast CT and X-ray fluorescence/luminescence CT. Discuss the practical need, technical aspects and current status of the emerging X-ray imaging modalities. Describe utility and future impact of the new generation of X-ray imaging applications.

  13. ICG fluorescence imaging and its medical applications

    NASA Astrophysics Data System (ADS)

    Miwa, Mitsuharu; Shikayama, Takahiro

    2008-12-01

    This paper presents a novel optical angiography system, and introduces its medical applications. We developed the optical enhanced imaging system which can observe the blood and lymphatic vessels as the Indocyanine green (ICG) fluorescence image. The imaging system consists of 760nm light emitted diode (LED) as excite light, CCD camera as a detector, a high-pass optical filter in front of the CCD and video processing system. The advantage of ICG fluorescence method is safe (radiation free), high sensitive, real time monitoring of blood and/or lymphatic flow, small size, easy to operate and cost effective compared to conventional X-ray angiography or scintigraphy. We have applied this method to several clinical applications such as breast cancer sentinel lymph node (SLN) navigation, lymph edema diagnostic and identification of liver segmentation. In each application, ICG fluorescence method shows useful result. It's indicated that this method is promising technique as optical angiography.

  14. Multiphase Systems for Medical Image Region Classification

    NASA Astrophysics Data System (ADS)

    Garamendi, J. F.; Malpica, N.; Schiavi, E.

    2009-05-01

    Variational methods for region classification have shown very promising results in medical image analysis. The Chan-Vese model is one of the most popular methods, but its numerical resolution is slow and it has serious drawbacks for most multiphase applications. In this work, we extend the link, stablished by Chambolle, between the two classes binary Chan-Vese model and the Rudin-Osher-Fatemi (ROF) model to a multiphase four classes minimal partition problem. We solve the ROF image restoration model and then we threshold the image by means of a genetic algorithm. This strategy allows for a more efficient algorithm due to the fact that only one well posed elliptic problem is solved instead of solving the coupled parabolic equations arising in the original multiphase Chan-Vese model.

  15. The quest for standards in medical imaging.

    PubMed

    Gibaud, Bernard

    2011-05-01

    This article focuses on standards supporting interoperability and system integration in the medical imaging domain. We introduce the basic concepts and actors and we review the most salient achievements in this domain, especially with the DICOM standard, and the definition of IHE integration profiles. We analyze and discuss what was successful, and what could still be more widely adopted by industry. We then sketch out a perspective of what should be done next, based on our vision of new requirements for the next decade. In particular, we discuss the challenges of a more explicit sharing of image and image processing semantics, and we discuss the help that semantic web technologies (and especially ontologies) may bring to achieving this goal.

  16. Survey: interpolation methods in medical image processing.

    PubMed

    Lehmann, T M; Gönner, C; Spitzer, K

    1999-11-01

    Image interpolation techniques often are required in medical imaging for image generation (e.g., discrete back projection for inverse Radon transform) and processing such as compression or resampling. Since the ideal interpolation function spatially is unlimited, several interpolation kernels of finite size have been introduced. This paper compares 1) truncated and windowed sinc; 2) nearest neighbor; 3) linear; 4) quadratic; 5) cubic B-spline; 6) cubic; g) Lagrange; and 7) Gaussian interpolation and approximation techniques with kernel sizes from 1 x 1 up to 8 x 8. The comparison is done by: 1) spatial and Fourier analyses; 2) computational complexity as well as runtime evaluations; and 3) qualitative and quantitative interpolation error determinations for particular interpolation tasks which were taken from common situations in medical image processing. For local and Fourier analyses, a standardized notation is introduced and fundamental properties of interpolators are derived. Successful methods should be direct current (DC)-constant and interpolators rather than DC-inconstant or approximators. Each method's parameters are tuned with respect to those properties. This results in three novel kernels, which are introduced in this paper and proven to be within the best choices for medical image interpolation: the 6 x 6 Blackman-Harris windowed sinc interpolator, and the C2-continuous cubic kernels with N = 6 and N = 8 supporting points. For quantitative error evaluations, a set of 50 direct digital X rays was used. They have been selected arbitrarily from clinical routine. In general, large kernel sizes were found to be superior to small interpolation masks. Except for truncated sinc interpolators, all kernels with N = 6 or larger sizes perform significantly better than N = 2 or N = 3 point methods (p < 0.005). However, the differences within the group of large-sized kernels were not significant. Summarizing the results, the cubic 6 x 6 interpolator with continuous

  17. Determination of CT-to-density conversion relationship for image-based treatment planning systems.

    PubMed

    Saw, Cheng B; Loper, Alphonse; Komanduri, Krishna; Combine, Tony; Huq, Saiful; Scicutella, Carol

    2005-01-01

    The implementation of tissue inhomogeneity correction in image-based treatment planning will improve the accuracy of radiation dose calculations for patients undergoing external-beam radiotherapy. Before the tissue inhomogeneity correction can be applied, the relationship between the computed tomography (CT) value and density must be established. This tissue characterization relationship allows the conversion of CT value in each voxel of the CT images into density for use in the dose calculations. This paper describes the proper procedure of establishing the CT value to density conversion relationship. A tissue characterization phantom with 17 inserts made of different materials was scanned using a GE Lightspeed Plus CT scanner (120 kVp). These images were then downloaded into the Eclipse and Pinnacle treatment planning systems. At the treatment planning workstation, the axial images were retrieved to determine the CT value of the inserts. A region of interest was drawn on the central portion of the insert and the mean CT value and its standard deviation were determined. The mean CT value was plotted against the density of the tissue inserts and fitted with bilinear equations. A new set of CT values vs. densities was generated from the bilinear equations and then entered into the treatment planning systems. The need to obtain CT values through the treatment planning system is very clear. The 2 treatment planning systems use different CT value ranges, one from -1024 to 3071 and the other from 0 to 4096. If the range is correct, it would result in inappropriate use of the conversion curve. In addition to the difference in the range of CT values, one treatment planning system uses physical density, while the other uses relative electron density.

  18. Automatic 3D pulmonary nodule detection in CT images: A survey.

    PubMed

    Valente, Igor Rafael S; Cortez, Paulo César; Neto, Edson Cavalcanti; Soares, José Marques; de Albuquerque, Victor Hugo C; Tavares, João Manuel R S

    2016-02-01

    This work presents a systematic review of techniques for the 3D automatic detection of pulmonary nodules in computerized-tomography (CT) images. Its main goals are to analyze the latest technology being used for the development of computational diagnostic tools to assist in the acquisition, storage and, mainly, processing and analysis of the biomedical data. Also, this work identifies the progress made, so far, evaluates the challenges to be overcome and provides an analysis of future prospects. As far as the authors know, this is the first time that a review is devoted exclusively to automated 3D techniques for the detection of pulmonary nodules from lung CT images, which makes this work of noteworthy value. The research covered the published works in the Web of Science, PubMed, Science Direct and IEEEXplore up to December 2014. Each work found that referred to automated 3D segmentation of the lungs was individually analyzed to identify its objective, methodology and results. Based on the analysis of the selected works, several studies were seen to be useful for the construction of medical diagnostic aid tools. However, there are certain aspects that still require attention such as increasing algorithm sensitivity, reducing the number of false positives, improving and optimizing the algorithm detection of different kinds of nodules with different sizes and shapes and, finally, the ability to integrate with the Electronic Medical Record Systems and Picture Archiving and Communication Systems. Based on this analysis, we can say that further research is needed to develop current techniques and that new algorithms are needed to overcome the identified drawbacks.

  19. A general approach to liver lesion segmentation in CT images

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

    Lesion segmentation has remained a challenge in different body regions. Generalizability is lacking in published methods as variability in results is common, even for a given organ and modality, such that it becomes difficult to establish standardized methods of disease quantification and reporting. This paper makes an attempt at a generalizable method based on classifying lesions along with their background into groups using clinically used visual attributes. Using an Iterative Relative Fuzzy Connectedness (IRFC) delineation engine, the ideas are implemented for the task of liver lesion segmentation in computed tomography (CT) images. For lesion groups with the same background properties, a few subjects are chosen as the training set to obtain the optimal IRFC parameters for the background tissue components. For lesion groups with similar foreground properties, optimal foreground parameters for IRFC are set as the median intensity value of the training lesion subset. To segment liver lesions belonging to a certain group, the devised method requires manual loading of the corresponding parameters, and correct setting of the foreground and background seeds. The segmentation is then completed in seconds. Segmentation accuracy and repeatability with respect to seed specification are evaluated. Accuracy is assessed by the assignment of a delineation quality score (DQS) to each case. Inter-operator repeatability is assessed by the difference between segmentations carried out independently by two operators. Experiments on 80 liver lesion cases show that the proposed method achieves a mean DQS score of 4.03 and inter-operator repeatability of 92.3%.

  20. Algorithm of pulmonary emphysema extraction using thoracic 3D CT images

    NASA Astrophysics Data System (ADS)

    Saita, Shinsuke; Kubo, Mitsuru; Kawata, Yoshiki; Niki, Noboru; Nakano, Yasutaka; Ohmatsu, Hironobu; Tominaga, Keigo; Eguchi, Kenji; Moriyama, Noriyuki

    2007-03-01

    Recently, due to aging and smoking, emphysema patients are increasing. The restoration of alveolus which was destroyed by emphysema is not possible, thus early detection of emphysema is desired. We describe a quantitative algorithm for extracting emphysematous lesions and quantitatively evaluate their distribution patterns using low dose thoracic 3-D CT images. The algorithm identified lung anatomies, and extracted low attenuation area (LAA) as emphysematous lesion ca