Please use this identifier to cite or link to this item: https://doi.org/10.1007/11566465_7
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dc.titleMRA image segmentation with capillary active contour
dc.contributor.authorYan, P.
dc.contributor.authorKassim, A.A.
dc.date.accessioned2014-06-19T03:19:00Z
dc.date.available2014-06-19T03:19:00Z
dc.date.issued2005
dc.identifier.citationYan, P.,Kassim, A.A. (2005). MRA image segmentation with capillary active contour. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 3749 LNCS : 51-58. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/11566465_7" target="_blank">https://doi.org/10.1007/11566465_7</a>
dc.identifier.isbn3540293272
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/71026
dc.description.abstractPrecise segmentation of three-dimensional (3D) magnetic resonance angiography (MRA) image can be a very useful computer aided diagnosis (CAD) tool in clinical routines. Our objective is to develop a specific segmentation scheme for accurately extracting vasculature from MRA images. Our proposed algorithm, called the capillary active contour (CAC), models capillary action where liquid can climb along the boundaries of thin tubes. The CAC, which is implemented based on level sets, is able to segment thin vessels and has been applied for verification on synthetic volumetric images and real 3D MRA images. Compared with other state-of-the-art MRA segmentation algorithms, our experiments show that the introduced capillary force can facilitate more accurate segmentation of blood vessels. © Springer-Verlag Berlin Heidelberg 2005.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/11566465_7
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1007/11566465_7
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume3749 LNCS
dc.description.page51-58
dc.identifier.isiutNOT_IN_WOS
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