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Considering new regularization parameter-choice techniques for the tikhonov method to improve the accuracy of electrocardiographic imaging

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dc.contributor.author Chamorro Servent, Judit
dc.contributor.author Dubois, Rémi
dc.contributor.author Coudière, Yves
dc.date.accessioned 2023-01-17T09:10:08Z
dc.date.available 2023-01-17T09:10:08Z
dc.date.issued 2019
dc.identifier.citation Chamorro-Servent J, Dubois R, Coudière Y. Considering new regularization parameter-choice techniques for the tikhonov method to improve the accuracy of electrocardiographic imaging. Front Physiol. 2019 Mar 27;10:273. DOI: 10.3389/fphys.2019.00273
dc.identifier.issn 1664-042X
dc.identifier.uri http://hdl.handle.net/10230/55304
dc.description.abstract The electrocardiographic imaging (ECGI) inverse problem highly relies on adding constraints, a process called regularization, as the problem is ill-posed. When there are no prior information provided about the unknown epicardial potentials, the Tikhonov regularization method seems to be the most commonly used technique. In the Tikhonov approach the weight of the constraints is determined by the regularization parameter. However, the regularization parameter is problem and data dependent, meaning that different numerical models or different clinical data may require different regularization parameters. Then, we need to have as many regularization parameter-choice methods as techniques to validate them. In this work, we addressed this issue by showing that the Discrete Picard Condition (DPC) can guide a good regularization parameter choice for the two-norm Tikhonov method. We also studied the feasibility of two techniques: The U-curve method (not yet used in the cardiac field) and a novel automatic method, called ADPC due its basis on the DPC. Both techniques were tested with simulated and experimental data when using the method of fundamental solutions as a numerical model. Their efficacy was compared with the efficacy of two widely used techniques in the literature, the L-curve and the CRESO methods. These solutions showed the feasibility of the new techniques in the cardiac setting, an improvement of the morphology of the reconstructed epicardial potentials, and in most of the cases of their amplitude.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Frontiers
dc.relation.ispartof Frontiers in Physiology. 2019 Mar 27;10:273
dc.rights © 2019 Chamorro-Servent, Dubois and Coudière. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.title Considering new regularization parameter-choice techniques for the tikhonov method to improve the accuracy of electrocardiographic imaging
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.3389/fphys.2019.00273
dc.subject.keyword Inverse problem
dc.subject.keyword Tikhonov
dc.subject.keyword Regularization
dc.subject.keyword Electrocardiography
dc.subject.keyword MFS
dc.subject.keyword Ill-posed
dc.subject.keyword ECG
dc.subject.keyword Body surface
dc.subject.keyword Potentials
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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