Exploring possible choices of the Tikhonov regularization parameter for the method of fundamental solutions in electrocardiography
The inverse problem of electrocardiographic imaging (ECGI), i. e. computing epicardial potentials from the body surface measured potentials, is a challenging problem. In this setting, Tikhonov regularization is commonly employed, weighted by a regularization parameter. This parameter has an importan...
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Published in | 2017 Computing in Cardiology (CinC) pp. 1 - 4 |
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Main Authors | , , |
Format | Conference Proceeding |
Language | English |
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01.09.2017
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Abstract | The inverse problem of electrocardiographic imaging (ECGI), i. e. computing epicardial potentials from the body surface measured potentials, is a challenging problem. In this setting, Tikhonov regularization is commonly employed, weighted by a regularization parameter. This parameter has an important influence on the solution. In this work, we show the feasibility of two methods to choose the regularization parameter when using the method of fundamental solution, or MFS (a homogeneous meshless scheme based). These methods are i) a novel automatic technique based on the Discrete Picard condition (DPC), which we named ADPC and ii) the U-curve method introduced in other fields for cases where the well-known L-curve method fails or over-regularize the solution. We calculated the Tikhonov solution with the ADPC and U-curve methods for experimental data from the free distributed Experimental Data and Geometric Analysis Repository (EDGAR), and we compared them to the solution obtained with CRESO and L-curve procedures that are the two extensively used techniques in the ECGI. |
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AbstractList | The inverse problem of electrocardiographic imaging (ECGI), i. e. computing epicardial potentials from the body surface measured potentials, is a challenging problem. In this setting, Tikhonov regularization is commonly employed, weighted by a regularization parameter. This parameter has an important influence on the solution. In this work, we show the feasibility of two methods to choose the regularization parameter when using the method of fundamental solution, or MFS (a homogeneous meshless scheme based). These methods are i) a novel automatic technique based on the Discrete Picard condition (DPC), which we named ADPC and ii) the U-curve method introduced in other fields for cases where the well-known L-curve method fails or over-regularize the solution. We calculated the Tikhonov solution with the ADPC and U-curve methods for experimental data from the free distributed Experimental Data and Geometric Analysis Repository (EDGAR), and we compared them to the solution obtained with CRESO and L-curve procedures that are the two extensively used techniques in the ECGI. |
Author | Chamorro-Servent, J. Dubois, R. Coudiere, Y. |
Author_xml | – sequence: 1 givenname: J. surname: Chamorro-Servent fullname: Chamorro-Servent, J. organization: IHU-Liryc, Electrophysiology and Heart Modeling Institute, foundation Bordeaux Université, F-33600 Pessac-Bordeaux, France – sequence: 2 givenname: R. surname: Dubois fullname: Dubois, R. organization: CARMEN Research Team, INRIA, Bordeaux, France – sequence: 3 givenname: Y. surname: Coudiere fullname: Coudiere, Y. organization: IHU-Liryc, Electrophysiology and Heart Modeling Institute, foundation Bordeaux Université, F-33600 Pessac-Bordeaux, France |
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Snippet | The inverse problem of electrocardiographic imaging (ECGI), i. e. computing epicardial potentials from the body surface measured potentials, is a challenging... |
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SubjectTerms | Boundary conditions Distributed databases Electric potential Electrodes Heart Imaging Inverse problems |
Title | Exploring possible choices of the Tikhonov regularization parameter for the method of fundamental solutions in electrocardiography |
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