59 citations · 217 across the 22 of their papers we have counts for
4 papers · 1 filter
WarpPINN: Cine-MR image registration with physics-informed neural networks
Pablo Arratia López, Hernán Mella, Sergio Uribe +2
Heart failure is typically diagnosed with a global function assessment, such as ejection fraction. However, these metrics have low discriminate power, failing to distinguish differ…
-PINNs: physics-informed neural networks on complex geometries
Francisco Sahli Costabal, Simone Pezzuto, Paris Perdikaris
Physics-informed neural networks (PINNs) have demonstrated promise in solving forward and inverse problems involving partial differential equations. Despite recent progress on expa…
Learning cardiac activation maps from 12-lead ECG with multi-fidelity Bayesian optimization on manifolds
Simone Pezzuto, Paris Perdikaris, Francisco Sahli Costabal
We propose a method for identifying an ectopic activation in the heart non-invasively. Ectopic activity in the heart can trigger deadly arrhythmias. The localization of the ectopic…
Physics-informed neural networks to learn cardiac fiber orientation from multiple electroanatomical maps
Carlos Ruiz Herrera, Thomas Grandits, Gernot Plank +3
We propose FiberNet, a method to estimate \emph{in-vivo} the cardiac fiber architecture of the human atria from multiple catheter recordings of the electrical activation. Cardiac f…