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dc.contributor.authorBouix, Sylvain
dc.contributor.authorSiddiqi, Kaleem
dc.contributor.authorTannenbaum, Allen R.
dc.date.accessioned2009-11-30T21:27:38Z
dc.date.available2009-11-30T21:27:38Z
dc.date.issued2003-06
dc.identifier.citationSylvain Bouix, Kaleem Siddiqi, Allen Tannenbaum, "Flux driven fly-throughs," Proceedings of the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003, I-449-454.en
dc.identifier.isbn0-7695-1900-8
dc.identifier.issn1063-6919
dc.identifier.urihttp://hdl.handle.net/1853/31240
dc.description©2003 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.en
dc.descriptionDOI: 10.1109/CVPR.2003.1211388
dc.descriptionPresented at the 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 18-20 June, 2003, Madison, Wisconsin.
dc.description.abstractWe present a fast, robust and automatic method for computing central paths through tubular structures for application to virtual endoscopy. The key idea is to utilize a medial surface algorithm, which exploits properties of the average outward flux of the gradient vector field of a Euclidean distance function the boundary of the structure of interest. The algorithm is modified to yield a collection of 3D curves, each of which is locally centered. The approach requires no user interaction, and is virtually parameter free and has low computational complexity. We illustrate the approach on segmented colon and vessel data.en
dc.language.isoen_USen
dc.publisherGeorgia Institute of Technologyen
dc.subjectBlood-vesselsen
dc.subjectEndoscopesen
dc.subjectImage segmentationen
dc.subjectMedical image processingen
dc.subjectVirtual realityen
dc.titleFlux driven fly-throughsen
dc.typeProceedingsen
dc.contributor.corporatenameGeorgia Institute of Technology. Dept. of Biomedical Engineering
dc.contributor.corporatenameEmory University. Dept. of Biomedical Engineering
dc.contributor.corporatenameMcGill University. School of Computer Science
dc.publisher.originalInstitute of Electrical and Electronics Engineers


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