Descriptor: "MESH: Radiographic Image Enhancement" - Searchworks@Jio Institute Digital Library Search Results

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20 results on '"MESH: Radiographic Image Enhancement"'

1. High-resolution CT by diffraction-enhanced x-ray imaging: mapping of breast tissue samples and comparison with their histo-pathology

Author: Petri Sipilä, Pekka Virkkunen, Manuel Fernández, Mikko Tenhunen, Marja-Liisa Karjalainen-Lindsberg, Christian Nemoz, Stefan Fiedler, Marjut Leidenius, Jani Keyriläinen, Pekka Suortti, Karl von Smitten, Alberto Bravin, European Synchrotron Radiation Facility (ESRF), Department of Oncology and Radiotherapy, Turku University Central Hospital, Grenoble Institut des Neurosciences (GIN), Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de la Santé et de la Recherche Médicale (INSERM), European Molecular Biology Laboratory [Hamburg] (EMBL), Department of Pathology, Helsinki University Central Hospital, Department of Physics, Helsinki University Central Hospital-HUCH Cancer Center, Helsinki Medical Imaging Center, Breast surgery unit, Radiation Metrology Laboratory, Radiation and Nuclear Safety Authority, Department of Physical Sciences [Helsinki], Helsingin yliopisto = Helsingfors universitet = University of Helsinki, INCA, Serduc, Raphael, University of Helsinki, Bravin, A, Keyrilainen, J, Fernandez, M, Fiedler, S, Nemoz, C, Karjalainen-Lindsberg, M, Tenhunen, M, Virkkunen, P, Leidenius, M, von Smitten, K, Sipila, P, and Suortti, P
Subjects: Diffraction, Materials science, Image quality, Radiography, media_common.quotation_subject, MESH: Mammography, FIS/07 - FISICA APPLICATA (A BENI CULTURALI, AMBIENTALI, BIOLOGIA E MEDICINA), Synchrotron radiation, Breast Neoplasms, MESH: Algorithms, [SDV.IB.MN]Life Sciences [q-bio]/Bioengineering/Nuclear medicine, High-resolution CT, diffraction-enhanced x-ray imaging, Sensitivity and Specificity, [SDV.IB.MN] Life Sciences [q-bio]/Bioengineering/Nuclear medicine, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, X-Ray Diffraction, MESH: Radiographic Image Interpretation, Computer-Assisted, Humans, Contrast (vision), Radiology, Nuclear Medicine and imaging, media_common, MESH: Humans, [PHYS.PHYS.PHYS-MED-PH] Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], Radiological and Ultrasound Technology, business.industry, MESH: X-Ray Diffraction, X-ray, Reproducibility of Results, Refraction, MESH: Sensitivity and Specificity, 3. Good health, Radiographic Image Enhancement, MESH: Reproducibility of Results, MESH: Radiographic Image Enhancement, 030220 oncology & carcinogenesis, [PHYS.PHYS.PHYS-MED-PH]Physics [physics]/Physics [physics]/Medical Physics [physics.med-ph], Radiographic Image Interpretation, Computer-Assisted, Female, Monochromatic color, Tomography, X-Ray Computed, MESH: Tomography, X-Ray Computed, Nuclear medicine, business, MESH: Female, Algorithms, MESH: Breast Neoplasms, Mammography
Abstract: International audience; The aim of this study was to introduce high-resolution computed tomography (CT) of breast tumours using the diffraction-enhanced x-ray imaging (DEI) technique and to compare results with radiological and histo-pathological examinations. X-ray CT images of tumour-bearing breast tissue samples were acquired by monochromatic synchrotron radiation (SR). Due to the narrow beam and a large sample-to-detector distance scattering is rejected in the absorption contrast images (SR-CT). Large contrast enhancement is achieved by the use of the DEI-CT method, where the effects of refraction and scatter rejection are analysed by crystal optics. Clinical mammograms and CT images were recorded as reference material for a radiological examination. Three malignant and benign samples were studied in detail. Their radiographs were compared with optical images of stained histological sections. The DEI-CT images map accurately the morphology of the samples, including collagen strands and micro-calcifications of dimensions less than 0.1 mm. Histo-pathological examination and reading of the radiographs were done independently, and the conclusions were in general agreement. High-resolution DEI-CT images show strong contrast and permit visualization of details invisible in clinical radiographs. The radiation dose may be reduced by an order of magnitude without compromising image quality, which would make possible clinical in vivo DEI-CT with future compact SR sources.
Published: 2007

2. Iodixanol in multidetector-row computed tomography angiography (MDCTA): diagnostic accuracy for abdominal aorta and abdominal aortic major-branch diseases using four-, eight- and 16-detector-row CT scanners

Author: Vinay Duddalwar, M. F. Reiser, P. Simons, F. Thouveny, M. Nonent, G. Liessi, O. Cappeliez, L. Bonomo, Groupe d'Etude de la Thrombose de Bretagne Occidentale (GETBO), Université de Brest (UBO)-Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO)-Université de Brest (UBO), Service d'Imagerie (CHRU - CB), and Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)
Subjects: Male, MESH: Aorta, Abdominal, Contrast Media, 030204 cardiovascular system & hematology, 030218 nuclear medicine & medical imaging, Aortic aneurysm, MESH: Aged, 80 and over, 0302 clinical medicine, Image Processing, Computer-Assisted, Aorta, Abdominal, Computed tomography angiography, Aged, 80 and over, MESH: Aged, MESH: Middle Aged, MESH: Arterial Occlusive Diseases, Radiological and Ultrasound Technology, medicine.diagnostic_test, Abdominal aorta, General Medicine, Middle Aged, MESH: Image Processing, Computer-Assisted, 3. Good health, Radiographic Image Enhancement, MESH: Reproducibility of Results, MESH: Diagnostic Errors, Female, Radiology, MESH: Tomography, X-Ray Computed, MESH: Aortic Aneurysm, Abdominal, medicine.drug, Adult, MESH: Triiodobenzoic Acids, medicine.medical_specialty, Arterial Occlusive Diseases, MESH: Imaging, Three-Dimensional, 03 medical and health sciences, Imaging, Three-Dimensional, Aneurysm, Triiodobenzoic Acids, MESH: Contrast Media, medicine.artery, medicine, Humans, MESH: Angiography, Digital Subtraction, Radiology, Nuclear Medicine and imaging, Diagnostic Errors, Aged, MESH: Humans, business.industry, Angiography, Digital Subtraction, Reproducibility of Results, MESH: Adult, Digital subtraction angiography, medicine.disease, Iodixanol, MESH: Male, Stenosis, MESH: Radiographic Image Enhancement, Angiography, Tomography, X-Ray Computed, business, MESH: Female, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Aortic Aneurysm, Abdominal
Abstract: Purpose: To compare iodixanol-enhanced multidetector-row computed tomography angiography (MDCTA) with digital subtraction angiography (DSA), perioperative angiography, or surgical findings in the evaluation of the abdominal aorta and its main branches. Material and Methods: 173 patients with known or suspected aortic aneurysms or stenosis/occlusion of the abdominal aorta or its major branches were enrolled. The iso-osmolar contrast medium iodixanol (320 mg Ι/ml) was used, and data were acquired using four-, eight-, or 16-active-detector-row scanners. Reference diagnoses were provided by surgical findings, interventional findings, or DSA. Diagnostic accuracy was estimated with reference to surgery or interventional arteriography or DSA. Image quality was assessed as excellent, good, sufficient, or insufficient, and correlations were made with attenuation values in the aortic lumen. Tolerability of iodixanol was monitored during the injection for discomfort and other adverse events, and for 72 hours after contrast injection. Results: In 132 of 136 evaluable cases, MDCTA diagnosis matched the reference diagnosis, yielding an agreement rate of 97.1% (95% CI 92.6–99.2%). The quality of most MDCTA scans (147/173) was rated as excellent. Overall mean attenuation was 305.7 HU. MDCTA appeared more accurate than DSA for identification of lesion calcification, thrombus, irregularity, and ulceration. Tolerability of iodixanol was good, and no serious adverse events were reported. Conclusion: MDCTA using iodixanol is a promising, noninvasive alternative for evaluating patients with abdominal aortic disease.
Published: 2007

3. Cerebral Venous Thrombosis and Multidetector CT Angiography: Tips and Tricks

Author: Marc Zins, Jean-Michel Colombani, Annick Hélias, Mathieu H. Rodallec, Marie-Christine Jullès, Alexandre Krainik, Véronique Marteau, Antoine Feydy, Service de radiologie, Fondation Hôpital Saint-Joseph, Service d'Imagerie par Résonance Magnétique (IRM), CHU Grenoble, Assistance publique - Hôpitaux de Paris (AP-HP) - CHU Cochin [AP-HP] - Université Paris Descartes - Paris 5 (UPD5), Assistance publique - Hôpitaux de Paris (AP-HP) - Hôpital Beaujon, Dojat, Michel, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Cochin [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris Descartes - Paris 5 (UPD5), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Beaujon [AP-HP], and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)
Subjects: medicine.medical_specialty, MESH: Cerebral Angiography, medicine.medical_treatment, Venography, Contrast Media, MESH: Phlebography, MESH: Imaging, Three-Dimensional, Multidetector ct, MESH: Cerebral Veins, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, Imaging, Three-Dimensional, 0302 clinical medicine, MESH: Practice Guidelines as Topic, MESH: Contrast Media, Humans, Medicine, Radiology, Nuclear Medicine and imaging, Practice Patterns, Physicians', MESH: Physician's Practice Patterns, Vein, Venous Thrombosis, MESH: Humans, medicine.diagnostic_test, business.industry, Phlebography, Thrombolysis, medicine.disease, Cerebral Veins, Cerebral Angiography, 3. Good health, Radiographic Image Enhancement, Venous thrombosis, medicine.anatomical_structure, MESH: Radiographic Image Enhancement, Maximum intensity projection, Practice Guidelines as Topic, MESH: Venous Thrombosis, Angiography, Radiology, Tomography, Tomography, X-Ray Computed, MESH: Tomography, X-Ray Computed, business, 030217 neurology & neurosurgery
Abstract: International audience; Because of the great diversity of clinical features, its unforeseeable evolution, and a small proportion of cases that will worsen in the acute phase, cerebral venous thrombosis must be diagnosed as early as possible so that specific treatment can be started, typically transcatheter thrombolysis or systemic anticoagulation. Unenhanced computed tomography (CT) is usually the first imaging study performed on an emergency basis. Unenhanced CT allows detection of ischemic changes related to venous insufficiency and sometimes demonstrates a hyperattenuating thrombosed dural sinus or vein. Helical multidetector CT venography with bolus power injection of contrast material and combined use of two-dimensional and three-dimensional reformations (maximum intensity projection, integral display, and volume rendering) provides exquisite anatomic detail of the deep and superficial intracranial venous system and can demonstrate filling defects. However, common variants of the sinovenous system should not be mistaken for sinus thrombosis. A comprehensive diagnostic approach facilitates imaging of cerebral venous thrombosis with multidetector CT.
Published: 2006

4. Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge

Author: Julia A. Schnabel, Olivier Commowick, Grégoire Malandain, Kaifang Du, Mattias P. Heinrich, Jamie R. McClelland, M. de Bruijne, Nicholas Ayache, Max A. Viergever, Manuel Werlberger, Nicholas J. Tustison, Sascha E. A. Muenzing, Nassir Navab, Jan Ehrhardt, Dante De Nigris, Kunlin Cao, Marc Modat, Xiang Deng, Martin Urschler, D. L. Collins, James C. Gee, Cristian Lorenz, Gregory C. Sharp, Berend C. Stoel, Joseph M. Reinhardt, Rui Li, Xiao Han, Keelin Murphy, Jef Vandemeulebroucke, Simon Rit, M. Peroni, Tom Vercauteren, Sven Kabus, Stefan Klein, Marius Staring, Nikos Paragios, Gang Song, Dirk Loeckx, Dirk Smeets, David Sarrut, Sebastien Ourselin, Josien P. W. Pluim, B. van Ginneken, Jon Sporring, V. Garcia, Alexander Schmidt-Richberg, Kai Ding, Vladlena Gorbunova, Ben Glocker, Brian B. Avants, René Werner, Tal Arbel, Gary E. Christensen, Mark Jenkinson, Image sciences institute - University of Utrecht (ISI), University Medical Center [Utrecht], Department of Electrical and Computer Engineering [Iowa], University of Iowa [Iowa City], Philips Research [Germany], Philips Research, Siemens [Beijing], China Corporate Technology, State Key Laboratory of Chemical Engineering (Polymerization Division), Zhejiang University, Service DREAM, Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Mauna Kea Technologies, Analysis and Simulation of Biomedical Images (ASCLEPIOS), Vision, Action et Gestion d'informations en Santé (VisAGeS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), CentraleSupélec-Télécom Bretagne-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Télécom Bretagne-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), Computer Aided Medical Procedures & Augmented Reality (CAMPAR), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Organ Modeling through Extraction, Representation and Understanding of Medical Image Content (GALEN), Ecole Centrale Paris-Inria Saclay - Ile de France, Mathématiques Appliquées aux Systèmes - EA 4037 (MAS), Ecole Centrale Paris, Department of Computer Science [Copenhagen] (DIKU), Faculty of Science [Copenhagen], University of Copenhagen = Københavns Universitet (KU)-University of Copenhagen = Københavns Universitet (KU), Biomedical Imaging Group [Rotterdam] (BIG), Erasmus University Medical Center [Rotterdam] (Erasmus MC), CMS Software, Elekta Inc. [Maryland Heights], Institute of Biomedical Engineering [Oxford] (IBME), University of Oxford [Oxford], Department of Clinical Neurology [Oxford], University of Oxford [Oxford]-FMRIB Centre- John Radcliffe Hospital [Oxford University Hospital], Centre for Medical Image Computing (CMIC), University College of London [London] (UCL), Centre for Intelligent Machines (CIM), McGill University = Université McGill [Montréal, Canada], Montreal Neurological Institute and Hospital, McConnell Brain Imaging Centre (MNI), McGill University = Université McGill [Montréal, Canada]-McGill University = Université McGill [Montréal, Canada], Massachusetts General Hospital [Boston], Institute of Medical Informatics [Lübeck], Universität zu Lübeck [Lübeck], Medical imaging research center [Leuven], Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven)-Faculty of Engineering, Penn Image Computing & Science Lab [Philadelphia] (PICSL), University of Pennsylvania [Philadelphia], Department of radiology and medical imaging [Charlottesville], University of Virginia [Charlottesville], Division of image processing [Leiden], Leiden University Medical Center (LUMC)-Department of Radiology, Institute for Computer Graphics and Vision [Graz] (ICG), Graz University of Technology [Graz] (TU Graz), Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (CREATIS), Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Imagerie Tomographique et Radiothérapie, Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Jean Monnet [Saint-Étienne] (UJM)-Hospices Civils de Lyon (HCL)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Commowick, Olivier, Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Ecole Centrale Paris, University of Copenhagen = Københavns Universitet (UCPH)-University of Copenhagen = Københavns Universitet (UCPH), University of Oxford, University of Oxford-FMRIB Centre- John Radcliffe Hospital [Oxford University Hospital], Universität zu Lübeck = University of Lübeck [Lübeck], University of Pennsylvania, University of Virginia, Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Hospices Civils de Lyon (HCL)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Electronics and Informatics, Leiden University Medical Center (LUMC), Universiteit Leiden-Universiteit Leiden-Department of Radiology, Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Jean Monnet - Saint-Étienne (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Medical Image Analysis, Rehabilitation Medicine, Radiology & Nuclear Medicine, and Neurology
Subjects: Databases, Factual, Computer science, Software Validation, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, Computed tomography, Aetiology, screening and detection [ONCOL 5], MESH: Observer Variation, 030218 nuclear medicine & medical imaging, Task (project management), 0302 clinical medicine, MESH: Animals, Segmentation, Observer Variation, evaluation, Radiological and Ultrasound Technology, medicine.diagnostic_test, Reference Standards, Thorax, Computer Science Applications, Test (assessment), Radiographic Image Enhancement, MESH: Reproducibility of Results, Chest, Radiographic Image Interpretation, Computer-Assisted, Radiography, Thoracic, MESH: Reference Standards, [SDV.IB]Life Sciences [q-bio]/Bioengineering, MESH: Tomography, X-Ray Computed, Algorithms, medicine.medical_specialty, MESH: Sheep, Image registration, MESH: Algorithms, Sensitivity and Specificity, MESH: Thorax, lung, Set (abstract data type), 03 medical and health sciences, registration, MESH: Radiographic Image Interpretation, Computer-Assisted, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Medical imaging, medicine, Animals, MESH: Lung, Medical physics, Electrical and Electronic Engineering, [SDV.IB] Life Sciences [q-bio]/Bioengineering, Sheep, MESH: Software Validation, Information retrieval, Poverty-related infectious diseases [N4i 3], computed tomography, Image segmentation, MESH: Radiography, Thoracic, MESH: Databases, Factual, MESH: Sensitivity and Specificity, MESH: Radiographic Image Enhancement, Algorithm design, reproducibility of results, Tomography, X-Ray Computed, 030217 neurology & neurosurgery, Software
Abstract: Contains fulltext : 96888.pdf (Publisher’s version ) (Open Access) EMPIRE10 (Evaluation of Methods for Pulmonary Image REgistration 2010) is a public platform for fair and meaningful comparison of registration algorithms which are applied to a database of intrapatient thoracic CT image pairs. Evaluation of nonrigid registration techniques is a nontrivial task. This is compounded by the fact that researchers typically test only on their own data, which varies widely. For this reason, reliable assessment and comparison of different registration algorithms has been virtually impossible in the past. In this work we present the results of the launch phase of EMPIRE10, which comprised the comprehensive evaluation and comparison of 20 individual algorithms from leading academic and industrial research groups. All algorithms are applied to the same set of 30 thoracic CT pairs. Algorithm settings and parameters are chosen by researchers expert in the configuration of their own method and the evaluation is independent, using the same criteria for all participants. All results are published on the EMPIRE10 website (http://empire10.isi.uu.nl). The challenge remains ongoing and open to new participants. Full results from 24 algorithms have been published at the time of writing. This paper details the organization of the challenge, the data and evaluation methods and the outcome of the initial launch with 20 algorithms. The gain in knowledge and future work are discussed.
Published: 2011

5. Similarity enhancement for automatic segmentation of cardiac structures in computed tomography volumes

Author: Rubén Medina, Antonio Bravo, Miguel Vera, Mireille Garreau, Senhadji, Lotfi, Grupo de Ingeniería Biomédica de la Universidad de los Andes (GIBULA), Universidad de Los Andes [Mérida, Venezuela] (ULA), Decanato de Investigaci, Grupo de Bio-Ingenierıa (GBI), Universidad Nacional Eperimental del Tachira-Universidad Nacional Eperimental del Tachira, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), ECOS-NORD - FONACIT grant PI-20100000299, Universidad de Los Andes [Venezuela] (ULA), Université de Rennes 1 (UR1), and Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Subjects: Computer science, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, Heart Ventricles, Gaussian, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Computed tomography, MESH: Algorithms, 02 engineering and technology, computer.software_genre, Article, 030218 nuclear medicine & medical imaging, Automation, 03 medical and health sciences, symbols.namesake, 0302 clinical medicine, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Voxel, MESH: Automation, MESH: Cone-Beam Computed Tomography, 0202 electrical engineering, electronic engineering, information engineering, Medical imaging, medicine, Humans, Segmentation, Computer vision, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, [SDV.IB] Life Sciences [q-bio]/Bioengineering, MESH: Humans, medicine.diagnostic_test, business.industry, Heart, Image segmentation, Cone-Beam Computed Tomography, Radiographic Image Enhancement, MESH: Heart, MESH: Radiographic Image Enhancement, symbols, 020201 artificial intelligence & image processing, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Tomography, Artificial intelligence, MESH: Heart Ventricles, business, computer, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Algorithms
Abstract: International audience; The aim of this research is proposing a 3-D similarity enhancement technique useful for improving the segmentation of cardiac structures in Multi-Slice Computerized Tomography (MSCT) volumes. The similarity enhancement is obtained by subtracting the intensity of the current voxel and the gray levels of their adjacent voxels in two volumes resulting after preprocessing. Such volumes are: a. - a volume obtained after applying a Gaussian distribution and a morphological top-hat filter to the input and b. - a smoothed volume generated by processing the input with an average filter. Then, the similarity volume is used as input to a region growing algorithm. This algorithm is applied to extract the shape of cardiac structures, such as left and right ventricles, in MSCT volumes. Qualitative and quantitative results show the good performance of the proposed approach for discrimination of cardiac cavities.
Published: 2011

6. Construction of patient specific atlases from locally most similar anatomical pieces

Author: Grégoire Malandain, Liliane Ramus, Olivier Commowick, Analysis and Simulation of Biomedical Images (ASCLEPIOS), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), DOSIsoft, Vision, Action et Gestion d'informations en Santé (VisAGeS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-SIGNAUX ET IMAGES NUMÉRIQUES, ROBOTIQUE (IRISA-D5), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), CentraleSupélec-Télécom Bretagne-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Télécom Bretagne-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Université de Bretagne Sud (UBS)-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA), and Commowick, Olivier
Subjects: Models, Anatomic, MESH: Subtraction Technique, Computer science, MESH: Models, Anatomic, Pattern Recognition, Automated, 030218 nuclear medicine & medical imaging, 0302 clinical medicine, MESH: Pattern Recognition, Automated, Computer vision, Segmentation, Head and neck, Contouring, Patient specific, Radiographic Image Enhancement, MESH: Reproducibility of Results, medicine.anatomical_structure, Piecewise, Radiographic Image Interpretation, Computer-Assisted, MESH: Head, [SDV.IB]Life Sciences [q-bio]/Bioengineering, MESH: Tomography, X-Ray Computed, MESH: Neck, Algorithms, MESH: Algorithms, [SDV.CAN]Life Sciences [q-bio]/Cancer, MESH: Imaging, Three-Dimensional, Sensitivity and Specificity, Article, 03 medical and health sciences, Imaging, Three-Dimensional, [SDV.CAN] Life Sciences [q-bio]/Cancer, MESH: Computer Simulation, Atlas (anatomy), medicine, MESH: Radiographic Image Interpretation, Computer-Assisted, Humans, Computer Simulation, [SDV.IB] Life Sciences [q-bio]/Bioengineering, MESH: Humans, business.industry, Reproducibility of Results, MESH: Sensitivity and Specificity, Subtraction Technique, MESH: Radiographic Image Enhancement, Artificial intelligence, Tomography, X-Ray Computed, business, Head, Neck, 030217 neurology & neurosurgery
Abstract: International audience; Radiotherapy planning requires accurate delineations of the critical structures. To avoid manual contouring, atlas-based segmentation can be used to get automatic delineations. However, the results strongly depend on the chosen atlas, especially for the head and neck region where the anatomical variability is high. To address this problem, atlases adapted to the patient's anatomy may allow for a better registration, and already showed an improvement in segmentation accuracy. However, building such atlases requires the definition of a criterion to select among a database the images that are the most similar to the patient. Moreover, the inter-expert variability of manual contouring may be high, and therefore bias the segmentation if selecting only one image for each region. To tackle these issues, we present an original method to design a piecewise most similar atlas. Given a query image, we propose an efficient criterion to select for each anatomical region the K most similar images among a database by considering local volume variations possibly induced by the tumor. Then, we present a new approach to combine the K images selected for each region into a piecewise most similar template. Our results obtained with 105 CT images of the head and neck show that our method reduces the over-segmentation seen with an average atlas while being robust to inter-expert manual segmentation variability.
Published: 2010

7. An improved 3D shape context based non-rigid registration method and its application to small animal skeletons registration

Author: Di Xiao, Catriona Wimberley, Marie-Claude Gregoire, Pierrick Bourgeat, Olivier Salvado, Oscar Acosta Tamayo, David Zahra, Paula Berghofer, CSIRO Information and Commuciation Technologies (CSIRO ICT Centre), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), Institute of materials engineering (Blackburn, Australia), Australian Nuclear Science and Technology Organisation [Australie] (ANSTO), and This project is supported by Australian Commonwealth Scientific and Industrial Research Organisation (CSIRO) and Australian Nuclear Science and Technology Organisation (ANSTO).
Subjects: Geodesic, MESH: Subtraction Technique, 02 engineering and technology, Pattern Recognition, Automated, 030218 nuclear medicine & medical imaging, Mice, 0302 clinical medicine, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, 0202 electrical engineering, electronic engineering, information engineering, MESH: Pattern Recognition, Automated, Computer vision, MESH: Animals, Micro-CT images, Mathematics, Radiological and Ultrasound Technology, MESH: Hindlimb, MESH: Bone and Bones, Computer Graphics and Computer-Aided Design, Hindlimb, Radiographic Image Enhancement, MESH: Reproducibility of Results, Spline (mathematics), Radiographic Image Interpretation, Computer-Assisted, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Computer Vision and Pattern Recognition, MESH: Tomography, X-Ray Computed, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Algorithms, Smoothing, MESH: Rats, Health Informatics, MESH: Algorithms, Non-rigid registration, MESH: Imaging, Three-Dimensional, Sensitivity and Specificity, Bone and Bones, 03 medical and health sciences, Imaging, Three-Dimensional, Artificial Intelligence, Small animal, MESH: Radiographic Image Interpretation, Computer-Assisted, Animals, MESH: Artificial Intelligence, Radiology, Nuclear Medicine and imaging, Shape context, 3D shape context, MESH: Mice, business.industry, Reproducibility of Results, 020207 software engineering, MESH: Sensitivity and Specificity, Rats, Subtraction Technique, MESH: Radiographic Image Enhancement, Artificial intelligence, Tomography, X-Ray Computed, business, Small animal skeleton registration
Abstract: International audience; 3D shape context is a method to define matching points between similar shapes. It can be used as a pre-processing step in a non-rigid registration. The main limitation of the method is point mismatching, which includes long geodesic distance mismatch causing wrong topological structure, and neighbors crossing mismatch between two adjacent points. In this paper, we propose a topological structure verification method to correct the long geodesic distance mismatch and a correspondence field smoothing method to correct the neighbors crossing mismatch. A robust 3D shape context model is generated and further combined with thin-plate spline model for non-rigid registration. The method was tested on phantoms and applied to rat hind limb and mouse hind limb skeletons registration from micro-CT images. Errors between the registered surfaces were reduced by using the proposed method. The robustness of the method is demonstrated.
Published: 2010

8. Quantification of inflammation within rabbit atherosclerotic plaques using the macrophage-specific CT contrast agent N1177: a comparison with 18F-FDG PET/CT and histology

Author: Zahi A. Fayad, Fabien Hyafil, Jean-Christophe Cornily, Josef Machac, James H.F. Rudd, Laurent J. Feldman, Service de cardiologie, Université Paris Diderot - Paris 7 (UPD7)-AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Département de Cardiologie (CHRU - Cardio), Centre Hospitalier Régional Universitaire de Brest (CHRU Brest), Optimisation des régulations physiologiques (ORPHY (EA 4324)), Université de Brest (UBO)-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO)-Université de Brest (UBO), and Université Paris Diderot - Paris 7 (UPD7)-AP-HP - Hôpital Bichat - Claude Bernard [Paris]-Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)
Subjects: MESH: Inflammation, Male, Pathology, medicine.medical_specialty, chemistry.chemical_element, MESH: Rabbits, Contrast Media, Inflammation, 030204 cardiovascular system & hematology, Iodine, 030218 nuclear medicine & medical imaging, MESH: Atherosclerosis, 03 medical and health sciences, 0302 clinical medicine, MESH: Fluorodeoxyglucose F18, Fluorodeoxyglucose F18, Hounsfield scale, medicine.artery, MESH: Contrast Media, medicine, [SDV.MHEP.PHY]Life Sciences [q-bio]/Human health and pathology/Tissues and Organs [q-bio.TO], Macrophage, Animals, Radiology, Nuclear Medicine and imaging, MESH: Animals, Aorta, medicine.diagnostic_test, business.industry, Macrophages, MESH: Macrophages, Histology, Atherosclerosis, MESH: Male, MESH: Positron-Emission Tomography, Radiographic Image Enhancement, chemistry, Positron emission tomography, MESH: Radiographic Image Enhancement, Positron-Emission Tomography, Tomography, Rabbits, medicine.symptom, Radiopharmaceuticals, Nuclear medicine, business, MESH: Tomography, X-Ray Computed, Tomography, X-Ray Computed, MESH: Radiopharmaceuticals
Abstract: International audience; UNLABELLED: Macrophages play a key role in atherosclerotic plaque rupture. The iodine-based contrast agent N1177 accumulates in macrophages, allowing for their detection with CT. In this study, we tested whether the intensity of enhancement detected with CT in the aortic wall of rabbits injected with N1177 correlated with inflammatory activity evaluated with (18)F-FDG PET/CT and macrophage density on histology. METHODS: Atherosclerotic plaques were induced in the aorta of New Zealand White rabbits (n = 7) by a repeated balloon injury (4 wk apart) and 4 mo of hyperlipemic diet. Noninjured rabbits, fed a chow diet, were used as controls (n = 3). A CT scan of the aorta (n = 10) was acquired in each rabbit before, during, and at 2 h after intravenous injection of N1177 (250 mg of iodine/kg). One week later, the same rabbits underwent PET/CT 3 h after injection of (18)F-FDG (37 MBq/kg [1 mCi/kg]). CT enhancement was calculated as the difference in aortic wall densities between images obtained before and images obtained at 2 h after injection of N1177. Mean standardized uptake values were measured on PET axial slices of the aorta in regions of interest encompassing the vessel wall. Macrophage density was measured by immunohistology (anti-RAM-11 antibody) on corresponding aortic cross-sections. RESULTS: N1177-enhanced CT measured stronger enhancement in the aortic wall of atherosclerotic rabbits than in control rabbits (10.0 +/- 5.2 vs. 2.0 +/- 2.1 Hounsfield units, respectively; P < 0.05). After the injection of (18)F-FDG, PET detected higher standardized uptake values in the aortic wall of atherosclerotic rabbits than in control rabbits (0.61 +/- 0.12 vs. 0.21 +/- 0.02; P < 0.05). The intensity of enhancement in the aortic wall measured with CT after injection of N1177 correlated with (18)F-FDG uptake on PET/CT (r = 0.61, P < 0.001) and macrophage density on immunohistology (r = 0.63, P < 0.001). CONCLUSION: The intensity of enhancement detected with CT in the aortic wall of rabbits injected with N1177 correlates with intense uptake of (18)F-FDG measured with PET and with macrophage density on histology, suggesting a role for N1177 in noninvasive identification of high-risk atherosclerotic plaques with CT.
Published: 2009

9. Motion compensated tomography reconstruction of coronary arteries in rotational angiography

Author: Jean-Jacques Bellanger, Guanyu Yang, C. Toumoulin, Alexandre Bousse, Jian Zhou, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de Recherche en Information Biomédicale sino-français (CRIBS), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Southeast University [Jiangsu]-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratory of Image Science and Technology [Nanjing] (LIST), Southeast University [Jiangsu]-School of Computer Science and Engineering, Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Rennes (UR)-Southeast University [Jiangsu]-Institut National de la Santé et de la Recherche Médicale (INSERM), and Senhadji, Lotfi
Subjects: Algebraic Reconstruction Technique, MESH: Models, Cardiovascular, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, deformable model, MESH: Motion, Quantitative Biology::Tissues and Organs, 0206 medical engineering, Biomedical Engineering, 02 engineering and technology, Iterative reconstruction, Coronary Angiography, Article, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, Motion, 0302 clinical medicine, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Motion estimation, Medical imaging, Computer vision, Projection (set theory), rotational X-ray, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, penalized least squares, [SDV.IB] Life Sciences [q-bio]/Bioengineering, Physics, Tomographic reconstruction, business.industry, Angiography, Models, Cardiovascular, 020601 biomedical engineering, MESH: Coronary Angiography, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Radiographic Image Enhancement, Rotational angiography, MESH: Radiographic Image Enhancement, inverse problem, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Artificial intelligence, Tomography, business, MESH: Tomography, X-Ray Computed, Tomography, X-Ray Computed, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, B-spline interpolation
Abstract: International audience; This paper deals with the 3-D reconstruction of the coronary tree from a rotational X-ray projection sequence. It describes the following three stages: the reconstruction of the 3-D coronary tree at different phases of the cardiac cycle, the motion estimation, and the motion-compensated tomographic reconstruction of the 3-D coronary tree at one given phase using all the available projections. Our method is tested on a series of simulated images computed from the projection of a segmented dynamic volume sequence acquired in multislice computed tomography imaging. Performances are comparable to those obtained by reconstruction of a statical coronary tree using an algebraic reconstruction technique algorithm.
Published: 2009

10. Mapping the zonal organization of tumor perfusion and permeability in a rat glioma model by using dynamic contrast-enhanced synchrotron radiation CT

Author: Irène Troprès, Géraldine Le Duc, Romain Billet, Daniel Balvay, Michel Peoc'h, Aurélie Joubert, Charles A. Cuenod, Méthodes d'imagerie des échanges transcapillaires (LRI), IFR94-Université Paris Descartes - Paris 5 (UPD5), Service de Radiologie, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), European Synchrotron Radiation Facility (ESRF), Rayonnement Synchrotron et Recherche Medicale (RSRM), Université Joseph Fourier - Grenoble 1 (UJF)-European Synchrotron Radiation Facility (ESRF)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service d'Anatomie et de Cytologie Pathologique, CHU Saint-Etienne-Hôpital Bellevue, French Radiology Society (SFR), European Synchrotron Radiation Facility (ESRF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de la Santé et de la Recherche Médicale (INSERM), Serduc, Raphael, IFR94 - Université Paris Descartes - Paris 5 (UPD5), Assistance publique - Hôpitaux de Paris (AP-HP) - Hôpital Européen Georges Pompidou [APHP] (HEGP), Université Joseph Fourier - Grenoble 1 (UJF) - ESRF - Institut National de la Santé et de la Recherche Médicale (INSERM), and CHU Saint-Etienne - Hôpital Bellevue
Subjects: Male, MESH: Rats, Contrast Media, Synchrotron radiation, [SDV.IB.MN]Life Sciences [q-bio]/Bioengineering/Nuclear medicine, MESH: Iopamidol, Sensitivity and Specificity, 030218 nuclear medicine & medical imaging, [SDV.IB.MN] Life Sciences [q-bio]/Bioengineering/Nuclear medicine, MESH: Glioma, 03 medical and health sciences, 0302 clinical medicine, In vivo, Glioma, MESH: Contrast Media, medicine, Animals, Radiology, Nuclear Medicine and imaging, MESH: Animals, Rats, Wistar, Neovascularization, Pathologic, Brain Neoplasms, business.industry, Blood flow, MESH: Rats, Wistar, medicine.disease, MESH: Sensitivity and Specificity, MESH: Male, Iopamidol, Rats, 3. Good health, Radiographic Image Enhancement, Disease Models, Animal, Dynamic contrast, Blood Volume Fraction, Permeability (electromagnetism), MESH: Radiographic Image Enhancement, MESH: Brain Neoplasms, MESH: Synchrotrons, MESH: Disease Models, Animal, Tomography, X-Ray Computed, business, Nuclear medicine, MESH: Tomography, X-Ray Computed, MESH: Neovascularization, Pathologic, Perfusion, Synchrotrons, 030217 neurology & neurosurgery
Abstract: International audience; PURPOSE: To depict and analyze in vivo the tumor zone organization of C6 gliomas depicted on quantitative parametric maps obtained with dynamic contrast material-enhanced synchrotron radiation computed tomography (CT) in a tightly controlled data-processing protocol. MATERIALS AND METHODS: Animal use was compliant with official French guidelines and was assessed by the local Internal Evaluation Committee for Animal Welfare and Rights. Fifteen Wistar rats with orthotopically implanted gliomas were studied at monochromatic synchrotron radiation CT after receiving a bolus injection of contrast material. The iodine concentration maps were analyzed by using a compartmental model selected from among a package of models. Choice of model and assessment of the relevance of the model were guided by quality criteria. Tissue blood flow (F(T)), tissue blood volume fraction (V(T)), permeability-surface area product (PS), artery-to-tissue delay (D(A-T)), and vascular mean transit time (MTT) maps were obtained. Parametric map findings were compared with histologic findings. Local regions of interest were selected in the contralateral hemisphere and in several tumor structures to characterize the tumor microvasculature. Differences in parameter values between regions were assessed with the Wilcoxon method. RESULTS: Whole-tumor parameters were expressed as means +/- standard errors of the mean: Mean F(T), V(T), PS, and D(A-T) values and MTT were 61.4 mL/min/100 mL +/- 15.3, 2.4% +/- 0.4, 0.37 mL/min/100 mL +/- 0.11, 0.24 second +/- 0.06; and 3.9 seconds +/- 0.83, respectively. MTT and mean PS were significantly lower (P < .01) in the normal contralateral tissue: 1.10 seconds +/- 0.06 and < or = 10(-5) mL/min/100 mL, respectively. Tumor regions were characterized by significantly different (P < .05) F(T) and V(T) pairs: 108 mL/min/100 mL and 3.66%, respectively, at the periphery; 45.9 mL/min/100 mL and 1.91%, respectively, in the intermediate zone; 5.1 mL/min/100 mL and 0.42%, respectively, in the center; and 210 mL/min/100 mL and 6.82%, respectively, in the maximal value region. CONCLUSION: Fine mapping of the glioma microcirculation is feasible with dynamic contrast-enhanced synchrotron radiation CT performed with well-controlled analytic protocols. Supplemental material: http://radiology.rsnajnls.org/cgi/content/full/2501071929/DC1.
Published: 2009

11. Compensation of some time dependent deformations in tomography

Author: Pierre Grangeat, Sébastien Roux, Laurent Desbat, Gestes Medico-chirurgicaux Assistés par Ordinateur (TIMC-IMAG-GMCAO), Techniques de l'Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications, Grenoble - UMR 5525 (TIMC-IMAG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), GMCAO, Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information (CEA-LETI), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information (CEA-LETI), ANR-05-BLAN-0349,TORIID,Tomographie et Reconstruction 3D conique pour l'Imagerie Interventionnelle Dynamique.(2005), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF), and VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information (CEA-LETI)
Subjects: Time Factors, MESH: Motion, Physics::Medical Physics, MESH: Algorithms, 02 engineering and technology, MESH: Imaging, Three-Dimensional, Sensitivity and Specificity, Imaging phantom, 030218 nuclear medicine & medical imaging, Compensation (engineering), Motion, 03 medical and health sciences, Imaging, Three-Dimensional, 0302 clinical medicine, Optics, 0202 electrical engineering, electronic engineering, information engineering, MESH: Radiographic Image Interpretation, Computer-Assisted, Electrical and Electronic Engineering, Computer Science::Databases, Mathematics, Motion compensation, Radiological and Ultrasound Technology, Deformation (mechanics), Radon transform, business.industry, Mathematical analysis, MESH: Time Factors, Reproducibility of Results, MESH: Sensitivity and Specificity, Computer Science Applications, Radiographic Image Enhancement, MESH: Reproducibility of Results, MESH: Artifacts, MESH: Radiographic Image Enhancement, Radiographic Image Interpretation, Computer-Assisted, 020201 artificial intelligence & image processing, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Tomography, Affine transformation, Artifacts, Tomography, X-Ray Computed, business, MESH: Tomography, X-Ray Computed, Algorithms, Software, Beam (structure)
Abstract: This work concerns 2D + t dynamic tomography. We show that a much larger class of deformations than the affine transforms can be compensated analytically within filtered back projection algorithms in 2D parallel beam and fan beam dynamic tomography. We present numerical experiments on the Shepp and Logan phantom showing that nonaffine deformations can be compensated. A generalization to 3D cone beam tomography is proposed.
Published: 2007

12. Accuracy of 16-detector multislice spiral computed tomography in the initial evaluation of dilated cardiomyopathy

Author: Martine Gilard, Ulric Vinsonneau, Grégoire Le Gal, Jacques Boschat, Pierre-Yves Pennec, Jean-Jacques Blanc, Jean-Christophe Cornily, Jacques Mansourati, Département de Cardiologie (CHRU - Cardio), Centre Hospitalier Régional Universitaire de Brest (CHRU Brest), Service d'Hémodynamique, Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-Hôpital de la Cavale Blanche - CHRU Brest (CHU - BREST ), Optimisation des régulations physiologiques (ORPHY (EA 4324)), Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO)-Université de Brest (UBO)-Université de Brest (UBO)-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest), Centre d'Investigation Clinique (CIC - Brest), Université de Brest (UBO)-Institut National de la Santé et de la Recherche Médicale (INSERM), Département de Cardiologie (HIA - Cardio), and Hôpital d'Instruction des armées
Subjects: Male, MESH: Equipment Failure Analysis, Pilot Projects, 030204 cardiovascular system & hematology, Coronary Angiography, 030218 nuclear medicine & medical imaging, Coronary artery disease, 0302 clinical medicine, MESH: Middle Aged, medicine.diagnostic_test, Dilated cardiomyopathy, General Medicine, Equipment Design, Middle Aged, Spiral computed tomography, MESH: Reproducibility of Results, Radiographic Image Enhancement, 030220 oncology & carcinogenesis, End-diastolic volume, Radiographic Image Interpretation, Computer-Assisted, Female, Radiology, Agatston score, MESH: Transducers, Cardiomyopathy, Dilated, medicine.medical_specialty, Transducers, Sensitivity and Specificity, 03 medical and health sciences, medicine, MESH: Radiographic Image Interpretation, Computer-Assisted, Humans, Multislice, Radiology, Nuclear Medicine and imaging, cardiovascular diseases, MESH: Cardiomyopathy, Dilated, MESH: Humans, business.industry, Reproducibility of Results, medicine.disease, MESH: Pilot Projects, MESH: Coronary Angiography, MESH: Sensitivity and Specificity, MESH: Male, Equipment Failure Analysis, Heart failure, MESH: Radiographic Image Enhancement, Angiography, MESH: Tomography, Spiral Computed, business, MESH: Female, Tomography, Spiral Computed, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, MESH: Equipment Design
Abstract: International audience; BACKGROUND: Multislice Computed Tomography (MSCT) recently proved its accuracy in the detection of coronary artery disease (CAD). It can also give information about left ventricular function and venous network anatomy. We here sought to validate a MSCT-based strategy in the initial evaluation of patients with dilated cardiomyopathy (DCM). METHODS: 36 patients with DCM underwent cardiac MSCT before conventional coronary angiography with ventriculography. We analysed arterial calcium score (Agatston score equivalent: ASE), coronary stenosis, left ventricular parameters and venous network. RESULTS: The sensitivity of a MSCT-based strategy in detecting significant CAD was 100% and the specificity 80%. The positive and negative predictive values were respectively 67% and 100%. For ASE or =1000, MSCT enabled conventional angiography to be avoided in only 2/9 patients (22.2%). The ventricle was assessable in 83.4% (30 patients) on MSCT. Correlation coefficient Rs with ventriculography were 0.78 (p1.000, conventional coronary angiography is mandatory due to MSCT's poor interest in such cases; when ASE
Published: 2006

13. Ray casting with 'on-the-fly' region growing: 3-D navigation into cardiac MSCT volume

Author: Jean-Louis, Coatrieux, Kristell, Rioual, Cemil, Göksu, Edurne, Unanua, Pascal, Haigron, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Senhadji, Lotfi, Université de Rennes 1 (UR1), and Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Subjects: MESH: Preoperative Care, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, MESH: Algorithms, Planing, MESH: Imaging, Three-Dimensional, Sensitivity and Specificity, Article, User-Computer Interface, Imaging, Three-Dimensional, Medical Imaging, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Artificial Intelligence, Preoperative Care, MESH: Radiographic Image Interpretation, Computer-Assisted, Humans, MESH: Artificial Intelligence, MESH: Sensit, [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing, [SDV.IB] Life Sciences [q-bio]/Bioengineering, MESH: Humans, Cardiovascular Surgical Procedures, Reproducibility of Results, Heart, MESH: Cardiovascular Surgical Procedures, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Radiographic Image Enhancement, Cardiac Resynchronization, MESH: Heart, MESH: Reproducibility of Results, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, Surgery, Computer-Assisted, MESH: Radiographic Image Enhancement, Radiographic Image Interpretation, Computer-Assisted, CRT, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Tomography, Spiral Computed, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Algorithms, Image Guided Intervention
Abstract: International audience; This paper describes an extended ray casting scheme for three-dimensional (3-D) navigation into the heart cavities for preoperative planning using multislice X-ray computed tomography data. The key benefit is that artifacts due to contrast inhomogeneities can be eliminated during volume traversal, thus improving the visual perception of the endocardial wall.
Published: 2006

14. Multi-slice computer tomography of left ventricular function with automated analysis software in comparison with conventional ventriculography

Author: Grégoire Le Gal, Jacques Mansourati, Michel Nonent, Jean-Christophe Cornily, Ulric Vinsonneau, Pierre-Yves Pennec, Jacques Boschat, Martine Gilard, Service d'Hémodynamique, Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-Hôpital de la Cavale Blanche - CHRU Brest (CHU - BREST ), Optimisation des régulations physiologiques (ORPHY (EA 4324)), Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO)-Université de Brest (UBO)-Université de Brest (UBO)-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest), Service de Cardiologie (BREST - Cardio), Centre Hospitalier Régional Universitaire de Brest (CHRU Brest), Service de Cardiologie (HIA - Cardio), HIA - BREST, Centre d'Investigation Clinique (CIC - Brest), Université de Brest (UBO)-Institut National de la Santé et de la Recherche Médicale (INSERM), Groupe d'Etude de la Thrombose de Bretagne Occidentale (GETBO), Université de Brest (UBO)-Institut Brestois Santé Agro Matière (IBSAM), Université de Brest (UBO)-Université de Brest (UBO), and Département de radiologie [Brest] (DR - Brest)
Subjects: Male, MESH: Diagnostic Techniques, Cardiovascular, Diagnostic Techniques, Cardiovascular, Contrast Media, Computed tomography, Coronary Artery Disease, 030204 cardiovascular system & hematology, MESH: Ventricular Function, Left, Ventricular Function, Left, 030218 nuclear medicine & medical imaging, Coronary artery disease, 0302 clinical medicine, Medicine, MESH: Coronary Artery Disease, Diagnosis, Computer-Assisted, MESH: Middle Aged, Ejection fraction, medicine.diagnostic_test, Ventricular function, Cineradiography, Multi slice, General Medicine, Middle Aged, 3. Good health, Radiographic Image Enhancement, Female, Tomography, Radiology, medicine.medical_specialty, Tomography Scanners, X-Ray Computed, Heart Ventricles, MESH: Software, 03 medical and health sciences, MESH: Contrast Media, Analysis software, Humans, Radiology, Nuclear Medicine and imaging, MESH: Tomography Scanners, X-Ray Computed, MESH: Humans, business.industry, MESH: Diagnosis, Computer-Assisted, medicine.disease, Standard technique, MESH: Male, MESH: Cineradiography, MESH: Radiographic Image Enhancement, Feasibility Studies, MESH: Heart Ventricles, MESH: Feasibility Studies, business, Nuclear medicine, MESH: Female, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Software
Abstract: International audience; PURPOSE: To evaluate the accuracy of left ventricular volumetric and functional parameters from multi-slice computed tomography using automated analysis software, and to correlate results with those of invasive left ventriculography. MATERIALS AND METHODS: In 145 consecutive patients (mean age, 61 years+/-12) known or suspected to have coronary artery disease, a 16-channel multi-slice computed tomography (Philips Mx8000 IDT 16) was performed using a standard technique. Using short-axis secondary multi-slice computed tomography reformations, we determined end-diastolic and end-systolic left ventricular volumes and ejection fraction with a commercially available analysis software capable of automated contour detection. Conventional left ventriculography was performed according to standard techniques within the following 24 h. Bland-Altman analysis was performed to calculate the limits of agreement and systematic errors between multi-slice computed tomography and conventional left ventriculography. RESULTS: As determined by computer tomography, mean end-systolic (53+/-29 mL) left ventricular volumes had an acceptable correlation with conventional ventriculography (67+/-50 mL; r=0.74; p
Published: 2005

15. Quantitative analysis of synchrotron radiation intravenous angiographic images

Author: Hélène Elleaume, Bernard Bertrand, Anna Sarnelli, Christian Nemoz, François Estève, Alberto Bravin, Dipartimento di Fisica, Università degli Studi di Ferrara (UniFE), European Synchrotron Radiation Facility (ESRF), Rayonnement Synchrotron et Recherche Medicale (RSRM), Université Joseph Fourier - Grenoble 1 (UJF)-European Synchrotron Radiation Facility (ESRF)-Institut National de la Santé et de la Recherche Médicale (INSERM), Biomedical Beamline (ID17), Clinique de cardiologie, CHU Grenoble-Hôpital Michallon, Collaboration, Sarnelli, A, Nemoz, C, Elleaume, N, Esteve, F, Bertrand, B, Bravin, A, Serduc, Raphael, Università degli Studi di Ferrara = University of Ferrara (UniFE), and European Synchrotron Radiation Facility (ESRF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut National de la Santé et de la Recherche Médicale (INSERM)
Subjects: Male, MESH: Subtraction Technique, Synchrotron radiation, Information Storage and Retrieval, Coronary Angiography, 030218 nuclear medicine & medical imaging, 0302 clinical medicine, Restenosis, MESH: Coronary Restenosis, MESH: Middle Aged, Radiological and Ultrasound Technology, Subtraction, Graft Occlusion, Vascular, Middle Aged, Radiographic Image Enhancement, MESH: Reproducibility of Results, medicine.anatomical_structure, 030220 oncology & carcinogenesis, MESH: Synchrotrons, Radiographic Image Interpretation, Computer-Assisted, Radiology, Deconvolution, Algorithms, medicine.medical_specialty, MESH: Graft Occlusion, Vascular, FIS/07 - FISICA APPLICATA (A BENI CULTURALI, AMBIENTALI, BIOLOGIA E MEDICINA), Image processing, MESH: Algorithms, Sensitivity and Specificity, Coronary Restenosis, 03 medical and health sciences, medicine, MESH: Radiographic Image Interpretation, Computer-Assisted, Humans, Radiology, Nuclear Medicine and imaging, Quantitative analysis, synchrotron radiation, intravenous angiography, MESH: Humans, business.industry, Reproducibility of Results, MESH: Information Storage and Retrieval, medicine.disease, MESH: Coronary Angiography, MESH: Sensitivity and Specificity, MESH: Male, Coronary arteries, Beamline, Subtraction Technique, MESH: Radiographic Image Enhancement, Nuclear medicine, business, Quantitative analysis (chemistry), Synchrotrons
Abstract: International audience; A medical research protocol on clinical intravenous coronary angiography has been completed at the European Synchrotron Radiation Facility (ESRF) biomedical beamline. The aim was to investigate the accuracy of intravenous coronary angiography based on the K-edge digital subtraction technique for the detection of in-stent restenosis. For each patient, diagnosis has been performed on the synchrotron radiation images and monitored with the conventional selective coronary angiography method taken as the golden standard. In this paper, the methods of image processing and the results of the quantitative analysis are described. Image processing includes beam harmonic contamination correction, spatial deconvolution and the extraction of a 'contrast' and a 'tissue' image from each couple of radiograms simultaneously acquired at energies bracketing the K-edge of iodine. Quantitative analysis includes the estimation of the vessel diameter, the calculation of the absolute iodine concentration profiles along the coronary arteries and the stenosis degree measurement.
Published: 2005

16. Depth-map-based scene analysis for active navigation in virtual angioscopy

Author: Oscar Acosta, Pascal Haigron, Marc-Emmanuel Bellemare, K. Rioual, C. Goksu, C. Kulik, A. Lucas, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire des Sciences de l'Information et des Systèmes (LSIS), Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Université de Toulon (UTLN)-Aix Marseille Université (AMU), Service de chirurgie thoracique cardiaque et vasculaire [Rennes] = Thoracic and Cardiovascular Surgery [Rennes], CHU Pontchaillou [Rennes], Dillenseger, Jean-Louis, Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Centre National de la Recherche Scientifique (CNRS)
Subjects: Visual perception, Computer science, 030204 cardiovascular system & hematology, 030218 nuclear medicine & medical imaging, Pattern Recognition, Automated, User-Computer Interface, 0302 clinical medicine, Computer graphics (images), automatic path planning, MESH: Pattern Recognition, Automated, Computer vision, Active vision, MESH: Angiography, MESH: User-Co, Radiological and Ultrasound Technology, virtual angioscopy, Process (computing), Angiography, Angioscopy, Computer Science Applications, MESH: Reproducibility of Results, Radiographic Image Enhancement, Surgery, Computer-Assisted, Radiographic Image Interpretation, Computer-Assisted, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Algorithms, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, MESH: Algorithms, Virtual reality, Sensitivity and Specificity, Article, 03 medical and health sciences, Depth map, MESH: Angioscopy, MESH: Radiographic Image Interpretation, Computer-Assisted, Humans, Electrical and Electronic Engineering, active virtual sensor, [SDV.IB] Life Sciences [q-bio]/Bioengineering, MESH: Humans, business.industry, Reproducibility of Results, Mobile robot navigation, MESH: Sensitivity and Specificity, Virtual image, MESH: Radiographic Image Enhancement, Ray casting, MESH: Surgery, Computer-Assisted, Artificial intelligence, business, Software
Abstract: This paper presents a new approach dealing with virtual exploratory navigation inside vascular structures. It is based on the notion of active vision in which only visual perception drives the motion of the virtual angioscope. The proposed fly-through approach does not require a premodeling of the volume dataset or an interactive control of the virtual sensor during the fly-through. Active navigation combines the on-line computation of the scene view and its analysis, to automatically define the three-dimensional sensor path. The navigation environment and the camera-like model are first sketched. The basic stages of the active navigation framework are then described: the virtual image computation (based on ray casting), the scene analysis process (using depth map), the navigation strategy, and the virtual path estimation. Experimental results obtained from phantom model and patient computed tomography data are finally reported.
Published: 2004

17. Exact reconstruction in 2D dynamic CT: compensation of time-dependent affine deformations

Author: Sébastien Roux, Laurent Desbat, Anne Koenig, Pierre Grangeat, Techniques de l'Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications, Grenoble - UMR 5525 (TIMC-IMAG), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF), Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information (CEA-LETI), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Collaboration TIMC-IMAG, CEA-LETI, Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), and Desbat, Laurent
Subjects: Time Factors, MESH: Subtraction Technique, Information Storage and Retrieval, 02 engineering and technology, MESH: Movement, MESH: Signal Processing, Computer-Assisted, 030218 nuclear medicine & medical imaging, Compensation (engineering), Reduction (complexity), 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, Computer vision, MESH: Numerical Analysis, Computer-Assisted, Mathematics, Radiological and Ultrasound Technology, Phantoms, Imaging, Respiration, Signal Processing, Computer-Assisted, [MATH.MATH-NA] Mathematics [math]/Numerical Analysis [math.NA], MESH: Reproducibility of Results, Radiographic Image Enhancement, MESH: Artifacts, Radiographic Image Interpretation, Computer-Assisted, 020201 artificial intelligence & image processing, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Radiography, Thoracic, MESH: Tomography, X-Ray Computed, Artifacts, [MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA], Algorithms, Movement, Motion (geometry), MESH: Algorithms, Deformation (meteorology), Sensitivity and Specificity, 03 medical and health sciences, analytic methods, MESH: Radiographic Image Interpretation, Computer-Assisted, Humans, Radiology, Nuclear Medicine and imaging, [SDV.IB] Life Sciences [q-bio]/Bioengineering, MESH: Respiration, Motion compensation, MESH: Humans, business.industry, deformations, Work (physics), MESH: Time Factors, MESH: Information Storage and Retrieval, Reproducibility of Results, Numerical Analysis, Computer-Assisted, MESH: Radiography, Thoracic, Object (computer science), MESH: Sensitivity and Specificity, MESH: Phantoms, Imaging, dynamic tomography, MESH: Radiographic Image Enhancement, Subtraction Technique, Artificial intelligence, Affine transformation, business, Tomography, X-Ray Computed
Abstract: International audience; This work is dedicated to the reduction of reconstruction artefacts due to motion occurring during the acquisition of computerized tomographic projections. This problem has to be solved when imaging moving organs such as the lungs or the heart. The proposed method belongs to the class of motion compensation algorithms, where the model of motion is included in the reconstruction formula. We address two fundamental questions. First what conditions on the deformation are required for the reconstruction of the object from projections acquired sequentially during the deformation, and second how do we reconstruct the object from those projections. Here we answer these questions in the particular case of 2D general time-dependent affine deformations, assuming the motion parameters are known. We treat the problem of admissibility conditions on the deformation in the parallel-beam and fan-beam cases. Then we propose exact reconstruction methods based on rebinning or sequential FBP formulae for each of these geometries and present reconstructed images obtained with the fan-beam algorithm on simulated data.
Published: 2004

18. Sampling conditions of 3D parallel and fan-beam x-ray CT with application to helical tomography

Author: Pierre Grangeat, Sébastien Roux, Laurent Desbat, Anne Koenig, Desbat, Laurent, Gestes Medico-chirurgicaux Assistés par Ordinateur (TIMC-IMAG-GMCAO), Techniques de l'Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications, Grenoble - UMR 5525 (TIMC-IMAG), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF), GMCAO, VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information (CEA-LETI), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information (CEA-LETI), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), and Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information (CEA-LETI)
Subjects: MESH: Subtraction Technique, Information Storage and Retrieval, MESH: Signal Processing, Computer-Assisted, 01 natural sciences, 030218 nuclear medicine & medical imaging, 0302 clinical medicine, MESH: Numerical Analysis, Computer-Assisted, Mathematics, Signal processing, Radiological and Ultrasound Technology, Phantoms, Imaging, Detector, Sampling (statistics), Signal Processing, Computer-Assisted, [MATH.MATH-NA] Mathematics [math]/Numerical Analysis [math.NA], 010101 applied mathematics, Radiographic Image Enhancement, MESH: Reproducibility of Results, Line (geometry), symbols, Radiographic Image Interpretation, Computer-Assisted, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Tomography, Algorithm, Algorithms, [MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA], MESH: Algorithms, MESH: Imaging, Three-Dimensional, Sensitivity and Specificity, 03 medical and health sciences, symbols.namesake, Optics, Imaging, Three-Dimensional, MESH: Radiographic Image Interpretation, Computer-Assisted, Radiology, Nuclear Medicine and imaging, 0101 mathematics, MESH: Sample Size, [SDV.IB] Life Sciences [q-bio]/Bioengineering, business.industry, Numerical analysis, Reproducibility of Results, MESH: Information Storage and Retrieval, Numerical Analysis, Computer-Assisted, MESH: Sensitivity and Specificity, Fourier transform, MESH: Phantoms, Imaging, Sample Size, Subtraction Technique, MESH: Radiographic Image Enhancement, MESH: Tomography, Spiral Computed, business, Tomography, Spiral Computed, Beam (structure)
Abstract: We give the sampling conditions of the 3D fan-beam x-ray transform (3DFBXRT). The motivation of this work lies in the fact that helical tomography with a single detector line is simply a sampling of this transform under the helical constraint. We give a precise description of the geometry of the essential support of the 3DFBXRT Fourier transform and show how to derive efficient sampling schemes. We then give efficient sampling schemes in parallel helical tomography. We present numerical experiments showing that efficient sampling on hexagonal interlaced schemes yields better reconstructions than the standard schemes in both parallel helical tomography (using QDO) and 3DFBXRT. We discuss the practical drawbacks and advantages of these efficient schemes and the possible extension to fan-beam helical CT.
Published: 2004

19. Multichannel algorithm for fast 3D reconstruction

Author: Pierre Grangeat, Thomas Rodet, Laurent Desbat, Desbat, Laurent, Laboratoire des signaux et systèmes (L2S), Université Paris-Sud - Paris 11 (UP11)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Commissariat à l'énergie atomique et aux énergies alternatives - Laboratoire d'Electronique et de Technologie de l'Information (CEA-LETI), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Gestes Medico-chirurgicaux Assistés par Ordinateur (TIMC-IMAG-GMCAO), Techniques de l'Ingénierie Médicale et de la Complexité - Informatique, Mathématiques et Applications, Grenoble - UMR 5525 (TIMC-IMAG), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF), and Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Divide and conquer algorithms, Quality Control, Computation, MESH: Tomography, Emission-Computed, MESH: Quality Control, MESH: Algorithms, Iterative reconstruction, MESH: Signal Processing, Computer-Assisted, Sensitivity and Specificity, MESH: Fluoroscopy, Image (mathematics), MESH: Brain, Medical imaging, Radiology, Nuclear Medicine and imaging, Computer vision, Mathematics, [SDV.IB] Life Sciences [q-bio]/Bioengineering, Decimation, Radiological and Ultrasound Technology, Fourier Analysis, business.industry, Phantoms, Imaging, 3D reconstruction, Brain, Signal Processing, Computer-Assisted, [MATH.MATH-NA] Mathematics [math]/Numerical Analysis [math.NA], Grid, Image Enhancement, MESH: Sensitivity and Specificity, Radiographic Image Enhancement, MESH: Phantoms, Imaging, MESH: Radiographic Image Enhancement, Fluoroscopy, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Artificial intelligence, MESH: Image Enhancement, business, Algorithm, MESH: Fourier Analysis, [MATH.MATH-NA]Mathematics [math]/Numerical Analysis [math.NA], Algorithms, Tomography, Emission-Computed
Abstract: Some recent medical imaging applications such as functional imaging (PET and SPECT) or interventional imaging (CT fluoroscopy) involve increasing amounts of data. In order to reduce the image reconstruction time, we develop a new fast 3D reconstruction algorithm based on a divide and conquer approach. The proposed multichannel algorithm performs an indirect frequential subband decomposition of the image f to be reconstructed (f = sigma fj) through the filtering of the projections Rf. The subband images fj are reconstructed on a downsampled grid without information suppression. In order to reduce the computation time, we do not backproject the null filtered projections and we downsample the number of projections according to the Shannon conditions associated with the subband image. Our algorithm is based on filtering and backprojection operators. Using the same algorithms for these basic operators, our approach is three and a half times faster than a classical FBP algorithm for a 2D image 512 x 512 and six times faster for a 3D image 32 x 512 x 512.
Published: 2002

20. Fast detection and characterization of vessels in very large 3-D data sets using geometrical moments

Author: Jean-Louis Coatrieux, Christine Toumoulin, Jean-Louis Dillenseger, C. Boldak, Y. Rolland, Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Dillenseger, Jean-Louis
Subjects: MESH: Models, Cardiovascular, Adaptive control, Computer science, 02 engineering and technology, 030218 nuclear medicine & medical imaging, 0302 clinical medicine, Ischemia, Popliteal Artery, Computer vision, medicine.diagnostic_test, Orientation (computer vision), Models, Cardiovascular, MESH: Popliteal Artery, MESH: Leg, Femoral Artery, Radiographic Image Enhancement, MESH: Artifacts, Data Display, cardiovascular system, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Artifacts, MESH: Tomography, X-Ray Computed, Algorithms, MESH: Femoral Artery, 0206 medical engineering, Biomedical Engineering, Image processing, MESH: Algorithms, Method of moments (statistics), Article, Edge detection, 03 medical and health sciences, Position (vector), medicine, Humans, MESH: Thrombosis, [SDV.IB] Life Sciences [q-bio]/Bioengineering, Leg, MESH: Humans, business.industry, Thrombosis, Image segmentation, 020601 biomedical engineering, MESH: Radiographic Image Enhancement, Angiography, Artificial intelligence, MESH: Ischemia, Tomography, X-Ray Computed, business, MESH: Data Display
Abstract: International audience; An improved and very fast algorithm dealing with the extraction of vessels in three-dimensional imaging is described. The approach is based on geometrical moments and a local cylindrical approximation. A robust estimation of vessel and background intensity levels, position, orientation, and diameter of the vessels with adaptive control of key parameters, is provided during vessel tracking. Experimental results are presented for lower limb arteries in multidetector computed tomography scanner.
Published: 2001

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20 results on '"MESH: Radiographic Image Enhancement"'

1. High-resolution CT by diffraction-enhanced x-ray imaging: mapping of breast tissue samples and comparison with their histo-pathology

2. Iodixanol in multidetector-row computed tomography angiography (MDCTA): diagnostic accuracy for abdominal aorta and abdominal aortic major-branch diseases using four-, eight- and 16-detector-row CT scanners

3. Cerebral Venous Thrombosis and Multidetector CT Angiography: Tips and Tricks

4. Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge

5. Similarity enhancement for automatic segmentation of cardiac structures in computed tomography volumes

6. Construction of patient specific atlases from locally most similar anatomical pieces

7. An improved 3D shape context based non-rigid registration method and its application to small animal skeletons registration

8. Quantification of inflammation within rabbit atherosclerotic plaques using the macrophage-specific CT contrast agent N1177: a comparison with 18F-FDG PET/CT and histology

9. Motion compensated tomography reconstruction of coronary arteries in rotational angiography

10. Mapping the zonal organization of tumor perfusion and permeability in a rat glioma model by using dynamic contrast-enhanced synchrotron radiation CT

11. Compensation of some time dependent deformations in tomography

12. Accuracy of 16-detector multislice spiral computed tomography in the initial evaluation of dilated cardiomyopathy

13. Ray casting with 'on-the-fly' region growing: 3-D navigation into cardiac MSCT volume

14. Multi-slice computer tomography of left ventricular function with automated analysis software in comparison with conventional ventriculography

15. Quantitative analysis of synchrotron radiation intravenous angiographic images

16. Depth-map-based scene analysis for active navigation in virtual angioscopy

17. Exact reconstruction in 2D dynamic CT: compensation of time-dependent affine deformations

18. Sampling conditions of 3D parallel and fan-beam x-ray CT with application to helical tomography

19. Multichannel algorithm for fast 3D reconstruction

20. Fast detection and characterization of vessels in very large 3-D data sets using geometrical moments

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