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CERES: A new cerebellum lobule segmentation method

hal.structure.identifierITACA
dc.contributor.authorROMERO, Jose
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorCOUPÉ, Pierrick
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierInstitut Polytechnique de Bordeaux [Bordeaux INP]
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorGIRAUD, Rémi
hal.structure.identifierInstitut Polytechnique de Bordeaux [Bordeaux INP]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorTA, Vinh-Thong
hal.structure.identifierMontreal Neurological Institute and Hospital
dc.contributor.authorFONOV, Vladimir
hal.structure.identifierDouglas Mental Health University Institute
dc.contributor.authorPARK, Min Tae
hal.structure.identifierDouglas Mental Health University Institute
dc.contributor.authorCHAKRAVARTY, Mallar
dc.contributor.authorVOINESKOS, Aristotle
hal.structure.identifierITACA
dc.contributor.authorMANJÓN, Jose
dc.date.accessioned2024-04-04T03:12:59Z
dc.date.available2024-04-04T03:12:59Z
dc.date.issued2016
dc.identifier.issn1053-8119
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/193914
dc.description.abstractEnThe human cerebellum is involved in language, motor tasks and cognitive processes such as attention or emotional processing. Therefore, an automatic and accurate segmentation method is highly desirable to measure and understand the cerebellum role in normal and pathological brain development. In this work, we propose a patch-­‐based multi-­‐atlas segmentation tool called CERES (CEREbellum Segmentation) that is able to automatically parcellate the cerebellum lobules. The proposed method works with standard resolution magnetic resonance T1-­‐weighted images and uses the Optimized PatchMatch algorithm to speed up the patch matching process. The proposed method was compared with related recent state-­‐of-­‐the-­‐art methods showing competitive results in both accuracy (average DICE of 0.7729) and execution time (around 5 minutes).
dc.description.sponsorshipTranslational Research and Advanced Imaging Laboratory - ANR-10-LABX-0057
dc.language.isoen
dc.publisherElsevier
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/
dc.subject.enMRI
dc.subject.encerebellum lobule segmentation
dc.subject.ennon-­‐local multi-­‐atlas patch-­‐based label fusion
dc.subject.enoptimized patchmatch
dc.title.enCERES: A new cerebellum lobule segmentation method
dc.typeArticle de revue
dc.identifier.doi10.1016/j.neuroimage.2016.11.003
dc.subject.halInformatique [cs]/Imagerie médicale
bordeaux.journalNeuroImage
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-01398748
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01398748v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=NeuroImage&rft.date=2016&rft.eissn=1053-8119&rft.issn=1053-8119&rft.au=ROMERO,%20Jose&COUP%C3%89,%20Pierrick&GIRAUD,%20R%C3%A9mi&TA,%20Vinh-Thong&FONOV,%20Vladimir&rft.genre=article


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