Finite element-based space-time total variation-type regularization of the inverse problem in electrocardiographic imaging
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arXiv
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| Autores principales: | , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866918182822871040 |
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| author | Haas, Manuel Grandits, Thomas Pinetz, Thomas Beiert, Thomas Pezzuto, Simone Effland, Alexander |
| author_facet | Haas, Manuel Grandits, Thomas Pinetz, Thomas Beiert, Thomas Pezzuto, Simone Effland, Alexander |
| contents | Reconstructing cardiac electrical activity from body surface electric potential measurements results in the severely ill-posed inverse problem in electrocardiography. Many different regularization approaches have been proposed to improve numerical results and provide unique results. This work presents a novel approach for reconstructing the epicardial potential from body surface potential maps based on a space-time total variation-type regularization using finite elements, where a first-order primal-dual algorithm solves the underlying convex optimization problem. In several numerical experiments, the superior performance of this method and the benefit of space-time regularization for the reconstruction of epicardial potential on two-dimensional torso data and a three-dimensional rabbit heart compared to state-of-the-art methods are demonstrated. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_11573 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Finite element-based space-time total variation-type regularization of the inverse problem in electrocardiographic imaging Haas, Manuel Grandits, Thomas Pinetz, Thomas Beiert, Thomas Pezzuto, Simone Effland, Alexander Numerical Analysis Computer Vision and Pattern Recognition Reconstructing cardiac electrical activity from body surface electric potential measurements results in the severely ill-posed inverse problem in electrocardiography. Many different regularization approaches have been proposed to improve numerical results and provide unique results. This work presents a novel approach for reconstructing the epicardial potential from body surface potential maps based on a space-time total variation-type regularization using finite elements, where a first-order primal-dual algorithm solves the underlying convex optimization problem. In several numerical experiments, the superior performance of this method and the benefit of space-time regularization for the reconstruction of epicardial potential on two-dimensional torso data and a three-dimensional rabbit heart compared to state-of-the-art methods are demonstrated. |
| title | Finite element-based space-time total variation-type regularization of the inverse problem in electrocardiographic imaging |
| topic | Numerical Analysis Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2408.11573 |