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hal.structure.identifierLaboratoire Jacques-Louis Lions [LJLL (UMR_7598)]
dc.contributor.authorGalarce, Felipe
hal.structure.identifierLaboratoire Jacques-Louis Lions [LJLL (UMR_7598)]
dc.contributor.authorLombardi, Damiano
HAL ID: 10254
hal.structure.identifierCEntre de REcherches en MAthématiques de la DEcision [CEREMADE]
dc.contributor.authorMula, Olga
HAL ID: 1531
ORCID: 0000-0002-3017-6598
dc.date.accessioned2021-10-26T12:51:30Z
dc.date.available2021-10-26T12:51:30Z
dc.date.issued2021
dc.identifier.urihttps://basepub.dauphine.psl.eu/handle/123456789/22105
dc.language.isoenen
dc.subjectModel Reductionen
dc.subjectShape Variabilityen
dc.subject.ddc621.3en
dc.titleState Estimation with Model Reduction and Shape Variability. Application to biomedical problemsen
dc.typeDocument de travail / Working paper
dc.description.abstractenWe develop a mathematical and numerical framework to solve state estimation problems for applications that present variations in the shape of the spatial domain. This situation arises typically in a biomedical context where inverse problems are posed on certain organs or portions of the body which inevitably involve morphological variations. If one wants to provide fast reconstruction methods, the algorithms must take into account the geometric variability. We develop and analyze a method which allows to take this variability into account without needing any a priori knowledge on a parametrization of the geometrical variations. For this, we rely on morphometric techniques involving Multidimensional Scaling, and couple them with reconstruction algorithms that make use of reduced model spaces pre-computed on a database of geometries. We prove the potential of the method on a synthetic test problem inspired from the reconstruction of blood flows and quantities of medical interest with Doppler ultrasound imaging.en
dc.identifier.citationpages26en
dc.relation.ispartofseriestitleCahier de recherche du CEREMADEen
dc.identifier.urlsitehttps://hal.inria.fr/hal-03264205en
dc.subject.ddclabelTraitement du signalen
dc.identifier.citationdate2021
dc.description.ssrncandidatenon
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dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.date.updated2021-10-26T12:47:14Z
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