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hal.structure.identifier
dc.contributor.authorChen, Da*
hal.structure.identifier
dc.contributor.authorCohen, Laurent D.
HAL ID: 738939
*
hal.structure.identifier
dc.contributor.authorMirebeau, Jean-Marie
HAL ID: 5588
*
dc.date.accessioned2017-11-02T12:46:18Z
dc.date.available2017-11-02T12:46:18Z
dc.date.issued2014
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/16895
dc.language.isoenen
dc.subjectGeodesic methods
dc.subjectVessel extraction
dc.subjectAnisotropic Fast Marching
dc.subjectMinimal Paths
dc.subjectKeypoints
dc.subject.ddc515en
dc.titleVessel Extraction Using Anisotropic Minimal Paths and Path Score
dc.typeCommunication / Conférence
dc.description.abstractenGeodesic methods have been widely applied to image analysis [1]. They are particularly efficient to extract a tubular structure, such as a blood vessel, given its two endpoints in a 2D or 3D medical image [2]. We address here a more difficult problem: the extraction of a full vessel tree structure given a single initial root, by growing a collection of keypoints, connected by geodesic minimal paths as in [3]. Keypoints are iteratively added, using selection criteria which compare geodesic distances with the standard euclidean curve length and a path score. A weakness of existing approaches is that the geodesic length and the euclidean path length are locally proportional, due to the use of an isotropic geodesic potential P(x). In contrast, we use an anisotropic geodesic potential P(x, v), and develop new criteria for selecting keypoints and stopping the tree growth. Experimental results demonstrate that our method can extract vessel structures at a finer scale, with increased accuracy.
dc.relation.ispartoftitle2014 IEEE International Conference on Image Processing (ICIP 2014)
dc.relation.ispartoftitleIEEE International Conference on Image Processing (ICIP 2014)
dc.relation.ispartofpublnameIEEE
dc.relation.ispartofpublcityPiscataway, NJ
dc.relation.ispartofdate2014
dc.subject.ddclabelAnalyseen
dc.relation.ispartofisbn978-1-4799-5751-4
dc.relation.confcountryFRANCE
dc.relation.forthcomingnonen
dc.identifier.doi10.1109/ICIP.2014.7025314
dc.description.ssrncandidatenon
dc.description.halcandidatenon
dc.description.readershiprecherche
dc.description.audienceInternational
dc.date.updated2017-11-28T10:44:05Z
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