{"version":1,"kind":"Article","sha256":"","slug":"675","location":"","dependencies":[],"doi":"10.54294/2nwedz","frontmatter":{"title":"Carotid arteries segmentation in CT images with use of a right generalized cylinder model","abstract":"The arterial lumen is modeled by a spatially continuous right generalized cylinder with piece-wise constant parameters. The method is the identifies the parameters of each cylinder piece from a series of planar contours extracted along an approximate axis of the artery. This curve is defined by a minimal path between the artery end-points. The contours are extracted by use of a 2D Fast Marching algorithm. The identification of the axial parameters is based on a geometrical analogy with piece-wise helical curves, while the identification of the surface parameters uses the Fourier series decomposition of the contours. Thus identified parameters are used as observations in a Kalman optimal estimation scheme that manages the spatial consistency from each piece to another. The method was was evaluated on 15 training and 31 testing datasets from the MICCAI 3D Segmentation in the Clinic Grand Challenge: Carotid Bifurcation Lumen Segmentation and Stenosis Grading (http://cls2009.bigr.nl/).","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":["geometric modeling","blood vessels","generalized cylinders","image segmentation"],"authors":[{"name":"Flórez Valencia, Leonardo","email":"florez-l@javeriana.edu.co","affiliations":["Pontificia Universidad Javeriana"],"corresponding":true},{"name":"Azencot, Jacques","affiliations":[]},{"name":"Orkisz, Maciej","email":"maciejorkisz@gmail.com","affiliations":[]}],"date_submitted":"2009-08-01 16:37:26","external_publication_id":675,"revision_cids":["bafkreicypwo6eyhhey75glgltl43wldcjye57ptsb3ybz6mss7vgvccpju"]},"mdast":{"type":"root"},"downloads":[{"url":"https://ipfs.desci.com/ipfs/bafkreid23srr6t7vj4vpy5ipyxlnjn5wxc6eue4qffwmnnmh55widfctlm","title":"root/insight-journal-metadata.json","filename":"insight-journal-metadata.json","extra":{"size_bytes":6730,"type":"file"}},{"url":"https://dweb.link/ipfs/bafkreib5t7mutxa44odzxr7uqg4geyv4rm2uxyzbovezkyd3cxjvxyxu74","title":"root/article.pdf","filename":"article.pdf","extra":{"size_bytes":286650,"type":"file"}}],"references":{"cite":{"order":["ref1","ref2","ref3","ref4","ref5","ref6","ref7","ref8","ref9","ref10"]},"data":{"ref1":{"label":"ref1","enumerator":"1","url":"https://doi.org/10.1016/s1524-0703(03)00073-0","html":"Deterministic and stochastic state model of right generalized cylinder (RGCsm): application in computer phantoms synthesis+Graph. Models+65+6+323+350+2003+J. Azencot+M. Orkisz"},"ref2":{"label":"ref2","enumerator":"2","url":"https://doi.org/10.1109/iembs.2007.4352409","html":"Fast marching contours for the segmentation of vessel lumen in CTA cross-sections+In Conf. Proc. IEEE Eng. Med. Biol. Soc.+3+794+2007+3+M. Baltaxe Milwer+I.E. Magnin+M. Orkisz"},"ref3":{"label":"ref3","enumerator":"3","url":"https://doi.org/10.1109/icip.2006.312770","html":"Segmentation and Quantification of Blood Vessels in 3D Images using a Right Generalized Cylinder State Model+In Proc. IEEE Int. Conf. Image Process.+2441+2444+2006+L. Flo+J. Azencot+F. Vincent+M. Orkisz+and I.E. Magnin"},"ref4":{"label":"ref4","enumerator":"4","url":"https://doi.org/10.1007/1-4020-4179-9_52","html":"Fast 3D pre-segmentation of arteries in computed tomography angiograms+In Int. Conf. Comput. Vision & Graphics+87+88+2004+L. Flo´rez Valencia+F. Vincent+M. Orkisz"},"ref5":{"label":"ref5","enumerator":"5","url":"https://doi.org/10.1118/1.4802751","html":"Segmentation in the Clinic: Carotid Lumen Segmentation+2009+nl. 4+K. Hameeteman+M. Zuluaga+L. Joskowicz+M. Freiman+T. van Walsum. 3D"},"ref6":{"label":"ref6","enumerator":"6","url":"https://doi.org/10.1115/1.3662552","html":"A New Approach to Linear Filtering and Prediction Problems+82+35+45+1960+R.E. Kalman+Engineering ASME-J. Basic"},"ref7":{"label":"ref7","enumerator":"7","url":"https://doi.org/10.1016/0734-189x(85)90093-3","html":"Threshold selection based on a simple image statistic+Comput. Vision Graphics Image Process+30+2+125+147+1985+Josef Kittler+J. Fglein"},"ref8":{"label":"ref8","enumerator":"8","url":"https://doi.org/10.1109/tpami.2003.1177156","html":"A linear time algorithm for computing exact euclidean distance transforms of binary images in arbitrary dimensions+IEEE Trans. Pattern Anal. Mach+25+2+265+270+2003+R. Calvin+Maurer+Qi Rensheng+Vijay Raghavan"},"ref9":{"label":"ref9","enumerator":"9","url":"https://doi.org/10.1073/pnas.93.4.1591","html":"A Fast Marching Level Set Method for Monotonically Advancing Fronts+In Proc. Nat. Acad. Sci.,+93+1591+1595+1996+J.A. Sethian"},"ref10":{"label":"ref10","enumerator":"10","url":"https://doi.org/10.1002/mrm.10164","html":"3D MRA coronary axis determination using a minimum cost path approach+47+6+1169+1175+2002+O. Wink+W.J. Niessen+A.F. Frangi+B. Verdonck+M.A. Viergever"}}}}