{"version":1,"kind":"Article","sha256":"","slug":"670","location":"","dependencies":[],"doi":"10.54294/q8zi79","frontmatter":{"title":"Carotid Lumen Segmentation Based on Tubular Anisotropy and Contours Without Edges","abstract":"We present a semi-automatic algorithm for Carotid lumen segmentation on CTA images.\nOur method is based on a variant of the minimal path method that models the vessel as a centerline and boundary. This is done by adding one dimension for the local radius around the centerline. The crucial step of our method is the definition of the local metrics to minimize. We have chosen to exploit the tubular structure of the vessels one wants to extract to built an anisotropic metric giving higher speed on the center of the vessels and also when the minimal path tangent is coherent with the vessel’s direction. Due to carotid stenosis or occlusions on the provided data, segmentation is refined using a region-based level sets.","license":"You are licensing your work to Kitware Inc. under the\nCreative Commons Attribution License Version 3.0.\n\nKitware Inc. agrees to the following:\n\nKitware is free\n * to copy, distribute, display, and perform the work\n * to make derivative works\n * to make commercial use of the work\n\nUnder the following conditions:\n\\\"by Attribution\\\" - Kitware must attribute the work in the manner specified by the author or licensor.\n\n * For any reuse or distribution, they must make clear to others the license terms of this work.\n * Any of these conditions can be waived if they get permission from the copyright holder.\n\nYour fair use and other rights are in no way affected by the above.\n\nThis is a human-readable summary of the Legal Code (the full license) available at\nhttp://creativecommons.org/licenses/by/3.0/legalcode","keywords":["Narrow band contours without edges","Minimal path","Anisotropy","Fast Marching"],"authors":[{"name":"Mille, Julien","affiliations":[]},{"name":"BENMANSOUR, Fethallah","email":"fethallah@gmail.com","affiliations":["CVLab, EPFL"],"corresponding":true},{"name":"Cohen, Laurent","affiliations":[]}],"date_submitted":"2009-07-20 17:25:53","external_publication_id":670,"revision_cids":["bafkreiaafvd6ipvirv452xh2iw3dnminat22wpcuu6s6dlnfqkigwmdsu4"]},"mdast":{"type":"root"},"downloads":[{"url":"https://ipfs.desci.com/ipfs/bafkreic3laznjxlmz4gjckf5oj73kluin4mns3u3melwch5ko3ez3zcykm","title":"root/insight-journal-metadata.json","filename":"insight-journal-metadata.json","extra":{"size_bytes":5092,"type":"file"}},{"url":"https://dweb.link/ipfs/bafybeihc34dwhmvoole4unjihbwt5wxlgkh57pyye4hlm53mr3hfans7mi","title":"root/article.pdf","filename":"article.pdf","extra":{"size_bytes":1805375,"type":"file"}}],"references":{"cite":{"order":["ref1","ref2","ref3","ref4","ref5","ref6","ref7"]},"data":{"ref1":{"label":"ref1","enumerator":"1","html":"Tubular anisotropy segmentation+In SSVM+2+25+2009+2+2+Fethallah Benmansour+Laurent D. Cohen"},"ref2":{"label":"ref2","enumerator":"2","url":"https://doi.org/10.1109/83.902291","html":"Active contours without edges+IEEE Transactions on Image Processing+10+2+266+277+2001+T. Chan+L. Vese"},"ref3":{"label":"ref3","enumerator":"3","url":"https://doi.org/10.1118/1.4802751","html":"Carotid lumen segmentation ans stenosis grading challenge+MICCAI'09 workshop, 3D Segmentation in the Clinic: A Grand Challenge - Carotid Bifurcation Lumen Segmentation and Stenosis Grading+2009+4+Reinhard Hameeteman+Zuluaga"},"ref4":{"label":"ref4","enumerator":"4","url":"https://doi.org/10.1007/978-3-540-88693-8_27","html":"Three dimensional curvilinear structure detection using optimally oriented flux+ECCV+2+2+382+2008+W. K. Max+Albert C. S. Law+Chung"},"ref5":{"label":"ref5","enumerator":"5","url":"https://doi.org/10.1109/tmi.2007.903696","html":"Vessels as 4-d curves: Global minimal 4-D paths to extract 3-D tubular surfaces and centerlines+Medical Imaging+26+9+1213+1223+2007+H. Li+A. Yezzi"},"ref6":{"label":"ref6","enumerator":"6","url":"https://doi.org/10.1016/j.cviu.2009.05.002","html":"Narrow band region-based active contours and surfaces for 2D and 3D segmentation+Computer Vision+113+9+946+965+2009+J. Mille"},"ref7":{"label":"ref7","enumerator":"7","url":"https://doi.org/10.1109/cvpr.2005.294","html":"Real-time tracking using level sets+In IEEE Computer Vision and Pattern Recognition (CVPR)+2+34+41+2005+Y. Shi+W. Karl"}}}}