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A practical algorithm to build geometric models of cardiac muscle structure

hal.structure.identifierIHU-LIRYC
hal.structure.identifierModélisation et calculs pour l'électrophysiologie cardiaque [CARMEN]
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorPOTSE, Mark
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierInstitut Polytechnique de Bordeaux [Bordeaux INP]
hal.structure.identifierService Expérimentation et Développement [Bordeaux] [SED]
dc.contributor.authorCIRROTTOLA, Luca
hal.structure.identifierService Expérimentation et Développement [Bordeaux] [SED]
dc.contributor.authorFROEHLY, Algiane
dc.date.accessioned2024-04-04T02:36:09Z
dc.date.available2024-04-04T02:36:09Z
dc.date.conference2022-06-05
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/190703
dc.description.abstractEnCardiac muscle tissue has a unique, network-like structure. Three-dimensional models of this structure are needed for simulations of cardiac electrophysiology and mechanics. We developed an algorithm to produce such models artificially, using an implicit surface expressed on a tailored unstructured multi-domain mesh to define the cell membranes. The algorithm first creates a random network of cell centers, observing angle and distance criteria inferred from real tissue. The space around the network edges is assigned to the cellular domains based on the nearest half-edge. The network is then immersed in a regular tetrahedral mesh which is refined to fit the domain boundaries and to offer sufficient density around the cell membrane. The refinements are alternated with basic mesh improvement operations to maintain an acceptable mesh quality. On the refined mesh a level-set function is expressed that defines the cell membrane. The remeshing code Mmg3d is then used to discretize the level set while retaining the domains, and to improve the quality of the final mesh. A serial implementation of the algorithm was able to produce meshes of a few hundreds of cardiac cells in 15 minutes, but we are still facing difficulties in the remesher, likely resulting from the unusual complexity of these meshes. It was still possible, however, to correctly mesh a small network of cells that was designed to be replicated by successive mirroring. This allowed us to build models of upto 1 cm 3 of tissue (11 million cells and 370 billion tetrahedra) that now serve in performance tests of a large-scale simulation code.
dc.language.isoen
dc.subject.enBiological systems
dc.subject.enCardiac modeling
dc.subject.enMesh adaptation
dc.subject.enLevel-set Methods
dc.title.enA practical algorithm to build geometric models of cardiac muscle structure
dc.typeCommunication dans un congrès
dc.subject.halInformatique [cs]
dc.subject.halSciences du Vivant [q-bio]/Médecine humaine et pathologie/Cardiologie et système cardiovasculaire
dc.description.sponsorshipEuropeNumerical modeling of cardiac electrophysiology at the cellular scale
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.conference.titleECCOMAS 2022 - The 8th European Congress on Computational Methods in Applied Sciences and Engineering
bordeaux.countryNO
bordeaux.conference.cityOslo
bordeaux.peerReviewedoui
hal.identifierhal-03936963
hal.version1
hal.invitednon
hal.proceedingsnon
hal.conference.end2022-06-09
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-03936963v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.au=POTSE,%20Mark&CIRROTTOLA,%20Luca&FROEHLY,%20Algiane&rft.genre=unknown


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