3 papers
eess.IV2026
Uncertainty Quantification for Cardiac Shape Reconstruction with Deep Signed Distance Functions via MCMC methods
Jan Verhülsdonk, Thomas Grandits, Francisco Sahli Costabal +3
Atlas-based approaches allow high-quality, patient-specific shape reconstructions of cardiac anatomy from sparse and/or noisy data such as point clouds. However, these methods are…
math.NA2026
Learned Finite Element-based Regularization of the Inverse Problem in Electrocardiographic Imaging
Manuel Haas, Thomas Grandits, Thomas Pinetz +3
Electrocardiographic imaging (ECGI) seeks to reconstruct cardiac electrical activity from body-surface potentials noninvasively. However, the associated inverse problem is severely…
math.NA2025
Finite element-based space-time total variation-type regularization of the inverse problem in electrocardiographic imaging
Manuel Haas, Thomas Grandits, Thomas Pinetz +3
Reconstructing cardiac electrical activity from body surface electric potential measurements results in the severely ill-posed inverse problem in electrocardiography. Many differen…