Search Results for author: Simone Pezzuto

Found 9 papers, 3 papers with code

Digital twinning of cardiac electrophysiology models from the surface ECG: a geodesic backpropagation approach

no code implementations16 Aug 2023 Thomas Grandits, Jan Verhülsdonk, Gundolf Haase, Alexander Effland, Simone Pezzuto

The eikonal equation has become an indispensable tool for modeling cardiac electrical activation accurately and efficiently.

$Δ$-PINNs: physics-informed neural networks on complex geometries

1 code implementation8 Sep 2022 Francisco Sahli Costabal, Simone Pezzuto, Paris Perdikaris

We approximate the eigenfunctions as well as the operators involved in the partial differential equations with finite elements.

Physics-informed neural networks to learn cardiac fiber orientation from multiple electroanatomical maps

1 code implementation28 Jan 2022 Carlos Ruiz Herrera, Thomas Grandits, Gernot Plank, Paris Perdikaris, Francisco Sahli Costabal, Simone Pezzuto

The inverse problem amounts to identifying the conduction velocity tensor of a cardiac propagation model from a set of sparse activation maps.

Smoothness and continuity of cost functionals for ECG mismatch computation

no code implementations12 Jan 2022 Thomas Grandits, Simone Pezzuto, Gernot Plank

The field of cardiac electrophysiology tries to abstract, describe and finally model the electrical characteristics of a heartbeat.

Descriptive

Learning atrial fiber orientations and conductivity tensors from intracardiac maps using physics-informed neural networks

no code implementations22 Feb 2021 Thomas Grandits, Simone Pezzuto, Francisco Sahli Costabal, Paris Perdikaris, Thomas Pock, Gernot Plank, Rolf Krause

In this work, we employ a recently developed approach, called physics informed neural networks, to learn the fiber orientations from electroanatomical maps, taking into account the physics of the electrical wave propagation.

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