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A Geodesic Voting Shape Prior to Constrain the Level Set Evolution for the Segmentation of Tubular Trees

dc.contributor.authorRouchdy, Youssef
dc.contributor.authorCohen, Laurent D.
HAL ID: 738939
dc.date.accessioned2012-01-09T10:54:30Z
dc.date.available2012-01-09T10:54:30Z
dc.date.issued2012
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/7836
dc.language.isoenen
dc.subjectGeodesic pathsen
dc.subject.ddc519en
dc.titleA Geodesic Voting Shape Prior to Constrain the Level Set Evolution for the Segmentation of Tubular Treesen
dc.typeCommunication / Conférence
dc.description.abstractenThis paper presents a geodesic voting method to segment tree structures, such as retinal or cardiac blood vessels. Many authors have used minimal cost paths, or similarly geodesics relative to a weight potential P, to find a vessel between two end points. Our goal focuses on the use of a set of such geodesic paths for finding a tubular tree structures, using minimal interaction. This work adapts the geodesic voting method that we have introduced for the segmentation of thin tree structures to the segmentation of tubular trees. The original approach of geodesic voting consists in computing geodesics from a set of end points scattered in the image to a given source point. The target structure corresponds to image points with a high geodesic density. Since the potential takes low values on the tree structure, geodesics will locate preferably on this structure and thus the geodesic density should be high. Geodesic voting method gives a good approximation of the localization of the tree branches, but it does not allow to extract the tubular aspect of the tree. Here, we use the geodesic voting method to build a shape prior to constrain the level set evolution in order to segment the boundary of the tubular structure. We show results of the segmentation with this approach on 2D angiogram images and 3D simulated data.en
dc.identifier.citationpages362-373en
dc.relation.ispartoftitleScale Space and Variational Methods in Computer Vision Third International Conference, SSVM 2011, Ein-Gedi, Israel, May 29 – June 2, 2011, Revised Selected Papersen
dc.relation.ispartofeditorBruckstein, Alfred M.
dc.relation.ispartofeditorTer Haar Romeny, Bart M.
dc.relation.ispartofeditorBronstein, Alexander M.
dc.relation.ispartofeditorBronstein, Michael M.
dc.relation.ispartofpublnameSpringeren
dc.relation.ispartofpublcityBerlinen
dc.relation.ispartofdate2012
dc.relation.ispartofpages798en
dc.relation.ispartofurlhttp://dx.doi.org/10.1007/978-3-642-24785-9en
dc.description.sponsorshipprivateouien
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.relation.ispartofisbn978-3-642-24784-2en
dc.relation.conftitleThird International Conference on Scale Space and Variational Methods in Computer Vision (SSVM 2011)en
dc.relation.confdate2011-05
dc.relation.confcityEin-Gedien
dc.relation.confcountryIsraëlen


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