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Sensitivity of the Electrocardiography Inverse Solution to the Torso Conductivity Uncertainties

hal.structure.identifierIHU-LIRYC
hal.structure.identifierModélisation et calculs pour l'électrophysiologie cardiaque [CARMEN]
dc.contributor.authorZEMZEMI, Nejib
hal.structure.identifierLaboratoire d'Etudes et Recherche en Mathématiques Appliquées [LERMA]
dc.contributor.authorABOULAICH, Rajae
hal.structure.identifierLaboratoire d'Etudes et Recherche en Mathématiques Appliquées [LERMA]
dc.contributor.authorFIKAL, Najib
hal.structure.identifierLaboratoire d'Etudes et Recherche en Mathématiques Appliquées [LERMA]
dc.contributor.authorEL GUARMAH, Emahdi
dc.contributor.editorHans van Assen; Peter Bovendeerd ; Tammo Delhaas
dc.date.accessioned2024-04-04T03:17:05Z
dc.date.available2024-04-04T03:17:05Z
dc.date.issued2015
dc.identifier.isbn978-3-319-20308-9
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/194277
dc.description.abstractEnElectrocardiography imaging (ECGI) is a new non invasive technology used for heart diagnosis. It allows to construct the electrical potential on the heart surface only from measurement on the body surface and some geometrical informations of the torso. The purpose of this work is twofold: First, we propose a new formulation to calculate the distribution of the electric potential on the heart, from measurements on the torso surface. Second, we study the influence of the errors and uncertainties on the conductivity parameters, on the ECGI solution. We use an optimal control formulation for the mathematical formulation of the problem with a stochastic diffusion equation as a constraint. The descretization is done using stochastic Galerkin method allowing to separate random and de-terministic variables. The optimal control problem is solved using a conjugate gradient method where the gradient of the cost function is computed with an ad-joint technique. The efficiency of this approach to solve the inverse problem and the usability to quantify the effect of conductivity uncertainties in the torso are demonstrated through a number of numerical simulations on a 2D geometrical model. Our results show that adding ±50% uncertainties in the fat conductivity does not alter the inverse solution, whereas adding ±50% uncertainties in the lung conductivity affects the reconstructed heart potential by almost 50%.
dc.language.isoen
dc.publisherSpringer
dc.source.titleFunctional Imaging and Modeling of the Heart
dc.subject.enInverse problem
dc.subject.enElectrocardiography Imaging
dc.subject.enStochastic Differential Equation
dc.title.enSensitivity of the Electrocardiography Inverse Solution to the Torso Conductivity Uncertainties
dc.typeChapitre d'ouvrage
dc.identifier.doi10.1007/978-3-319-20309-6_54
dc.subject.halInformatique [cs]/Modélisation et simulation
dc.subject.halMathématiques [math]/Optimisation et contrôle [math.OC]
dc.subject.halMathématiques [math]/Equations aux dérivées partielles [math.AP]
bordeaux.page475-483
bordeaux.volumeLecture Notes in Computer Science
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.issue9126
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.title.proceedingFunctional Imaging and Modeling of the Heart
hal.identifierhal-01222381
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01222381v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.btitle=Functional%20Imaging%20and%20Modeling%20of%20the%20Heart&rft.date=2015&rft.volume=Lecture%20Notes%20in%20Computer%20Science&rft.issue=9126&rft.spage=475-483&rft.epage=475-483&rft.au=ZEMZEMI,%20Nejib&ABOULAICH,%20Rajae&FIKAL,%20Najib&EL%20GUARMAH,%20Emahdi&rft.isbn=978-3-319-20308-9&rft.genre=unknown


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