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Fast Constrained Surface Extraction by Minimal Paths

dc.contributor.authorArdon, Roberto
dc.contributor.authorCohen, Laurent D.
HAL ID: 738939
dc.date.accessioned2011-07-27T15:31:49Z
dc.date.available2011-07-27T15:31:49Z
dc.date.issued2006
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/6823
dc.descriptionLa version de travail s'intitule " Minimal Paths and Surface Segmentation"en
dc.language.isoenen
dc.subjectactive surfacesen
dc.subjectactive contoursen
dc.subjectminimal pathsen
dc.subjectlevel set methoden
dc.subjectobject extractionen
dc.subject.ddc519en
dc.titleFast Constrained Surface Extraction by Minimal Pathsen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenIn this paper we consider a new approach for single object segmentation in 3D images. Our method improves the classical geodesic active surface model. It greatly simplifies the model initialization and naturally avoids local minima by incorporating user extra information into the segmentation process. The initialization procedure is reduced to introducing 3D curves into the image. These curves are supposed to belong to the surface to extract and thus, also constitute user given information. Hence, our model finds a surface that has these curves as boundary conditions and that minimizes the integral of a potential function that corresponds to the image features. Our goal is achieved by using globally minimal paths. We approximate the surface to extract by a discrete network of paths. Furthermore, an interpolation method is used to build a mesh or an implicit representation based on the information retrieved from the network of paths. Our paper describes a fast construction obtained by exploiting the Fast Marching algorithm and a fast analytical interpolation method. Moreover, a Level set method can be used to refine the segmentation when higher accuracy is required. The algorithm has been successfully applied to 3D medical images and synthetic images.en
dc.relation.isversionofjnlnameInternational Journal of Computer Vision
dc.relation.isversionofjnlvol69en
dc.relation.isversionofjnlissue1en
dc.relation.isversionofjnldate2006
dc.relation.isversionofjnlpages127-136en
dc.relation.isversionofdoihttp://dx.doi.org/10.1007/s11263-006-6850-zen
dc.description.sponsorshipprivateouien
dc.relation.isversionofjnlpublisherSpringeren
dc.subject.ddclabelProbabilités et mathématiques appliquéesen


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