1.4k citations · 2.8k across the 56 of their papers we have counts for
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Learning atrial fiber orientations and conductivity tensors from intracardiac maps using physics-informed neural networks
Thomas Grandits, Simone Pezzuto, Francisco Sahli Costabal +4
Electroanatomical maps are a key tool in the diagnosis and treatment of atrial fibrillation. Current approaches focus on the activation times recorded. However, more information ca…
GEASI: Geodesic-based Earliest Activation Sites Identification in cardiac models
Thomas Grandits, Alexander Effland, Thomas Pock +3
The identification of the initial ventricular activation sequence is a critical step for the correct personalization of patient-specific cardiac models. In healthy conditions, the…
Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction
Dominik Narnhofer, Alexander Effland, Erich Kobler +3
Recent deep learning approaches focus on improving quantitative scores of dedicated benchmarks, and therefore only reduce the observation-related (aleatoric) uncertainty. However,…
One-sided Frank-Wolfe algorithms for saddle problems
Vladimir Kolmogorov, Thomas Pock
We study a class of convex-concave saddle-point problems of the form where is a linear operator, is th…