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dc.contributor.authorCohen, Isaac
dc.contributor.authorCohen, Laurent D.
HAL ID: 738939
dc.contributor.authorAyache, Nicholas
dc.date.accessioned2014-12-18T08:42:06Z
dc.date.available2014-12-18T08:42:06Z
dc.date.issued1992
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/14472
dc.language.isoenen
dc.subject3-D imagesen
dc.subject.ddc519en
dc.titleUsing deformable surfaces to segment 3-D images and infer differential structuresen
dc.typeArticle accepté pour publication ou publié
dc.description.abstractenIn this paper, we use a 3-D deformable model, which evolves in 3-D images, under the action of internal forces (describing some elasticity properties of the surface), and external forces attracting the surface toward some detected edgels. Our formalism leads to the minimization of an energy which is expressed as a functional. We use a variational approach and a conforming finite element method to actually express the surface in a discrete basis of continuous functions. This leads to reduced computational complexity and better numerical stability. The power of the approach to segmenting 3-D images is demonstrated by a set of experimental results on various complex medical 3-D images. Another contribution of this approach is the possibility to infer easily the differential structure of the segmented surface. As we end up with an analytical description of class ∇∞ of the surface almost every-where, this allows us to compute, for instance, its first and second fundamental forms. From this, one can extract a curvature primal sketch of the surface, including some intrinsic features which can be used as landmarks for 3-D image interpretation.en
dc.relation.isversionofjnlnameCVGIP. Image Understanding
dc.relation.isversionofjnlvol56en
dc.relation.isversionofjnlissue2en
dc.relation.isversionofjnldate1992
dc.relation.isversionofjnlpages242-263en
dc.relation.isversionofdoihttp://dx.doi.org/10.1016/1049-9660(92)90041-Zen
dc.identifier.urlsitehttps://hal.inria.fr/inria-00075157en
dc.relation.isversionofjnlpublisherElsevieren
dc.subject.ddclabelProbabilités et mathématiques appliquéesen
dc.relation.forthcomingnonen
dc.relation.forthcomingprintnonen


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