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Spatially-Varying Metric Learning for Diffeomorphic Image Registration: A Variational Framework

hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorVialard, François-Xavier
hal.structure.identifierInstitut de Mathématiques de Toulouse UMR5219 [IMT]
dc.contributor.authorRisser, Laurent
HAL ID: 17551
dc.date.accessioned2021-11-03T10:34:28Z
dc.date.available2021-11-03T10:34:28Z
dc.date.issued2014
dc.identifier.urihttps://basepub.dauphine.psl.eu/handle/123456789/22158
dc.language.isoenen
dc.subjectImage Registrationen
dc.subjectDimensionality Reduction Methoden
dc.subjectGrid Step Sizeen
dc.subjectSimple Gradient Descenten
dc.subjectTarget Overlapen
dc.subject.ddc510en
dc.titleSpatially-Varying Metric Learning for Diffeomorphic Image Registration: A Variational Frameworken
dc.typeCommunication / Conférence
dc.description.abstractenThis paper introduces a variational strategy to learn spatially-varying metrics on large groups of images, in the Large Deformation Diffeomorphic Metric Mapping (LDDMM) framework. Spatially-varying metrics we learn not only favor local deformations but also correlated deformations in different image regions and in different directions. In addition, metric parameters can be efficiently estimated using a gradient descent method. We first describe the general strategy and then show how to use it on 3D medical images with reasonable computational ressources. Our method is assessed on the 3D brain images of the LPBA40 dataset. Results are compared with ANTS-SyN and LDDMM with spatially-homogeneous metrics.en
dc.identifier.citationpages227-234en
dc.relation.ispartoftitleInternational Conference on Medical Image Computing and Computer-Assisted Intervention: MICCAI 2014en
dc.relation.ispartofpublnameSpringeren
dc.relation.ispartofpublcityBerlin Heidelbergen
dc.relation.ispartofdate2014
dc.relation.ispartofpages826en
dc.relation.ispartofurl10.1007/978-3-319-10404-1en
dc.subject.ddclabelMathématiquesen
dc.relation.ispartofisbn978-3-319-10403-4en
dc.relation.conftitleMedical Image Computing and Computer-Assisted Intervention – MICCAI 2014 17th International Conferenceen
dc.relation.confdate2014-09
dc.relation.confcityBostonen
dc.relation.confcountryUnited Statesen
dc.relation.forthcomingnonen
dc.identifier.doi10.1007/978-3-319-10404-1_29en
dc.description.ssrncandidatenon
dc.description.halcandidatenonen
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewednonen
dc.date.updated2021-11-03T10:29:23Z
hal.author.functionaut
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