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Automatic branch detection of the arterial system from abdominal aortic segmentation

hal.structure.identifierModeling Enablers for Multi-PHysics and InteractionS [MEMPHIS]
dc.contributor.authorRIFFAUD, Sébastien
hal.structure.identifierModeling Enablers for Multi-PHysics and InteractionS [MEMPHIS]
dc.contributor.authorRAVON, Gwladys
hal.structure.identifierNurea
dc.contributor.authorALLARD, Thibault
hal.structure.identifierNurea
dc.contributor.authorBERNARD, Florian
hal.structure.identifierModeling Enablers for Multi-PHysics and InteractionS [MEMPHIS]
dc.contributor.authorIOLLO, Angelo
hal.structure.identifierCHU Bordeaux
dc.contributor.authorCARADU, Caroline
dc.date.accessioned2024-04-04T02:40:58Z
dc.date.available2024-04-04T02:40:58Z
dc.date.issued2022
dc.identifier.issn0140-0118
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/191108
dc.description.abstractEnWe present a new method to automatically identify the different arteries present in an abdominal aortic segmentation. In this approach, the arterial system is first represented by a vascular tree, extracted from the segmentation and containing the topologic and geometric features (branch position, branch direction, branch length, branch diameter) of the arterial system. Then, the branches of the vascular tree are matched with the main arteries origi- nating from the aorta: celiac artery, superior mesenteric artery, renal arteries and common iliac arteries. This match is determined by maximizing a similarity measure between the dif- ferent branches and corresponding arteries. We evaluate this method on 239 segmentations obtained from 102 different patients. The results demonstrate the accuracy of the proposed method, capable of delivering an error of less than 2.5% for the identification of the celiac and superior mesenteric arteries, 8.4% for the renal arteries, and 2.1% for the common iliac arteries.
dc.language.isoen
dc.publisherSpringer Verlag
dc.subject.enComputed tomography
dc.subject.enAbdominal aortic aneurysm
dc.subject.enAutomatic branch detection
dc.subject.enGraph matching method
dc.subject.enAortic root
dc.title.enAutomatic branch detection of the arterial system from abdominal aortic segmentation
dc.typeArticle de revue
dc.identifier.doi10.1007/s11517-022-02603-2
dc.subject.halSciences du Vivant [q-bio]/Médecine humaine et pathologie/Cardiologie et système cardiovasculaire
dc.subject.halInformatique [cs]/Imagerie médicale
dc.subject.halMathématiques [math]/Combinatoire [math.CO]
bordeaux.journalMedical and Biological Engineering and Computing
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-03520790
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-03520790v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Medical%20and%20Biological%20Engineering%20and%20Computing&rft.date=2022&rft.eissn=0140-0118&rft.issn=0140-0118&rft.au=RIFFAUD,%20S%C3%A9bastien&RAVON,%20Gwladys&ALLARD,%20Thibault&BERNARD,%20Florian&IOLLO,%20Angelo&rft.genre=article


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