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E. Chaikof, J. Blankensteijn, P. Harris, G. White, C. Zarins, V. Bernhard, J. Matsumura, J. May, F. Veith, M. Fillinger, R. Rutherford, K. Kent (2002)
Reporting standards for endovascular aortic aneurysm repair.Journal of vascular surgery, 35 5
JJ Wever, JD Blankensteijn, WP Mali, BC Eikelboom (2000)
Maximal aneurysm diameter follow-up is inadequate after endovascular abdominal aortic aneurysm repair.European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery, 20 2
(2012)
Fast AAA thrombus segmentation from CTA images for endovascular repair follow-up
G. Kossioris, Y. Papaharilaou, Christos Zohios (2008)
Detection of Lumen, Thrombus and Outer Wall Boundaries of an Abdominal Aortic Aneurysm From 2D Medical Images Using Level Set Methods
N. Sakalihasan, R. Limet, O. Defawe (2005)
Abdominal aortic aneurysmThe Lancet, 365
J. Sethian (1999)
Fast Marching MethodsSIAM Rev., 41
Marleen Bruijne, B. Ginneken, M. Viergever, W. Niessen (2003)
Adapting Active Shape Models for 3D Segmentation of Tubular Structures in Medical ImagesInformation processing in medical imaging : proceedings of the ... conference, 18
S. Olabarriaga, J. Rouet, M. Fradkin, M. Breeuwer, W. Niessen (2005)
Segmentation of thrombus in abdominal aortic aneurysms from CTA with nonparametric statistical grey level appearance modelingIEEE Transactions on Medical Imaging, 24
Sergio Martinez-Muñoz, Daniel Fernández, J. Galiana-Merino (2016)
Automatic Abdominal Aortic Aneurysm segmentation in MR imagesExpert Syst. Appl., 54
I. Macía, M. Graña, Josu Maiora, C. Paloc, M. Blas (2011)
Detection of type II endoleaks in abdominal aortic aneurysms after endovascular repairComputers in biology and medicine, 41 10
Christos Zohios, G. Kossioris, Y. Papaharilaou (2012)
Geometrical methods for level set based abdominal aortic aneurysm thrombus and outer wall 2D image segmentationComputer methods and programs in biomedicine, 107 2
M. Ebadian-Dehkordi, A. Jouannic, S. Qanadli (2015)
Automatic detection , segmentation and quantification of of Abdominal Aortic Aneurysm using Computed Tomography Angiography
Bipul Das, Y. Mallya, S. Suryanarayanan, R. Malladi (2006)
Aortic Thrombus Segmentation using Narrow Band Active Contour Model2006 International Conference of the IEEE Engineering in Medicine and Biology Society
A. Kaladji, A. Lucas, G. Kervio, P. Haigron, A. Cardon (2010)
Sizing for endovascular aneurysm repair: clinical evaluation of a new automated three-dimensional software.Annals of vascular surgery, 24 7
M. Freiman, S. Esses, Leo Joskowicz, J. Sosna (2010)
AN iterative model-constrained graph-cut algorithm for Abdominal Aortic Aneurysm thrombus segmentation2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro
S. Demirci, Guy Lejeune, Nassir Navab (2009)
Hybrid deformable model for aneurysm segmentation2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro
M. Kass, A. Witkin, Demetri Terzopoulos (2004)
Snakes: Active contour modelsInternational Journal of Computer Vision, 1
Kyungmoo Lee, Yin Yin, A. Wahle, M. Olszewski, M. Sonka (2008)
3-D segmentation and quantitative analysis of inner and outer walls of thrombotic abdominal aortic aneurysms, 6916
T. Walker, S. Kalva, Kalpana Yeddula, S. Wicky, Sanjoy Kundu, P. Drescher, B. d’Othée, S. Rose, J. Cardella (2010)
Clinical practice guidelines for endovascular abdominal aortic aneurysm repair: written by the Standards of Practice Committee for the Society of Interventional Radiology and endorsed by the Cardiovascular and Interventional Radiological Society of Europe and the Canadian Interventional Radiology AsJournal of vascular and interventional radiology : JVIR, 21 11
Feng Zhuge, G. Rubin, Shaohua Sun, S. Napel (2006)
An abdominal aortic aneurysm segmentation method: level set with region and statistical information.Medical physics, 33 5
M. Subašić, S. Lončarić, E. Sorantin (2005)
Model-based quantitative AAA image analysis using a priori knowledgeComputer methods and programs in biomedicine, 80 2
M. Subašić, Sven Loncaric, Erich Sorantin (2003)
Region-based deformable model for aortic wall segmentation3rd International Symposium on Image and Signal Processing and Analysis, 2003. ISPA 2003. Proceedings of the, 2
B. Rodríguez-Vila, J. Tarjuelo-Gutierrez, Patricia Sánchez-González, P. Verbrugghe, I. Fourneau, G. Maleux, P. Herijgers, E. Gómez (2015)
Automated Delineation of Vessel Wall and Thrombus Boundaries of Abdominal Aortic Aneurysms Using Multispectral MR ImagesComputational and Mathematical Methods in Medicine, 2015
Josu Maiora, M. Graña (2012)
Abdominal CTA image analisys through active learning and decision random forests: Aplication to AAA segmentationThe 2012 International Joint Conference on Neural Networks (IJCNN)
S. Shiffman, G. Rubin, S. Napel (1996)
Semiautomated editing of computed tomography sections for visualization of vasculature, 2707
M. Subašić, Sven Loncaric, Erich Sorantin (2001)
3D image analysis of abdominal aortic aneurysm, 4322
Marleen Bruijne, B. Ginneken, M. Viergever, W. Niessen (2004)
Interactive segmentation of abdominal aortic aneurysms in CTA imagesMedical image analysis, 8 2
Josu Maiora, G. Papakostas, V. Kaburlasos, M. Graña (2014)
A proposal of Texture Features for interactive CTA Segmentation by Active LearningStudies in health technology and informatics, 207
EL Chaikof, JD Blankensteijn, PL Harris, GH White, CK Zarins, VM Bernhard, JS Matsumura, J May, FJ Veith, MF Fillinger, RB Rutherford, KC Kent (2002)
Ad hoc committee for standardized reporting practices in vascular surgery of the society for vascular surgery/American association for vascular surgery: reporting standards for endovascular aortic aneurysm repairJ Vasc Surg, 35
Kyungmoo Lee, Ryan Johnson, Yin Yin, A. Wahle, M. Olszewski, T. Scholz, M. Sonka (2010)
Three-dimensional thrombus segmentation in abdominal aortic aneurysms using graph search based on a triangular meshComputers in biology and medicine, 40 3
S. Loncaric, M. Subašić, E. Sorantin (2000)
3-D deformable model for aortic aneurysm segmentation from CT imagesProceedings of the 22nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (Cat. No.00CH37143), 1
Int J CARS (2017) 12:1501–1510 DOI 10.1007/s11548-017-1591-8 ORIGINAL ARTICLE 1 1 2 2 Florent Lalys · Vincent Yan · Adrien Kaladji · Antoine Lucas · Simon Esneault Received: 11 January 2017 / Accepted: 18 April 2017 / Published online: 28 April 2017 © CARS 2017 Abstract of precision. Comparison with the level-set algorithm also Purpose Abdominal aortic aneurysm (AAA) is a localized, demonstrated the superiority of the 3D deformable model. permanent and irreversible enlargement of the artery, with the Average processing time was 8.2 ± 3.5s. formation of thrombus into the inner wall of the aneurysm. Conclusion We presented a near-automatic and generic A precise patient-specific segmentation of the thrombus is thrombus segmentation algorithm applicable to a large vari- useful for both the pre-operative planning to estimate the ability of patient and imaging conditions. When integrated rupture risk, and for post-operative assessment to monitor in an endovascular planning system, our segmentation algo- the disease evolution. This paper presents a generic approach rithm shows its compatibility with clinical routine and could for 3D segmentation of thrombus from patients suffering be used for pre-operative planning and post-operative assess- from AAA using computed tomography angiography (CTA) ment of endovascular procedures. scans. Methods
International Journal of Computer Assisted Radiology and Surgery – Springer Journals
Published: Apr 28, 2017
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