5 papers
Learning geometry-dependent lead-field operators for forward ECG modeling
Arsenii Dokuchaev, Francesca Bonizzoni, Stefano Pagani +2
Modern forward electrocardiogram (ECG) computational models rely on an accurate representation of the torso domain. The lead-field method enables fast ECG simulations while preserv…
Shape-informed cardiac mechanics surrogates in data-scarce regimes via geometric encoding and generative augmentation
Davide Carrara, Marc Hirschvogel, Francesca Bonizzoni +3
High-fidelity computational models of cardiac mechanics provide mechanistic insight into the heart function but are computationally prohibitive for routine clinical use. Surrogate…
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…
NET4EXA: Pioneering the Future of Interconnects for Supercomputing and AI
Michele Martinelli, Roberto Ammendola, Andrea Biagioni +41
NET4EXA aims to develop a next-generation high-performance interconnect for HPC and AI systems, addressing the increasing demands of large-scale infrastructures, such as those requ…
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…