research
∙
08/16/2023
Digital twinning of cardiac electrophysiology models from the surface ECG: a geodesic backpropagation approach
The eikonal equation has become an indispensable tool for modeling cardi...
share
research
∙
09/08/2022
Δ-PINNs: physics-informed neural networks on complex geometries
Physics-informed neural networks (PINNs) have demonstrated promise in so...
research
∙
03/11/2022
Learning cardiac activation maps from 12-lead ECG with multi-fidelity Bayesian optimization on manifolds
We propose a method for identifying an ectopic activation in the heart n...
research
∙
01/28/2022
Physics-informed neural networks to learn cardiac fiber orientation from multiple electroanatomical maps
We propose FiberNet, a method to estimate in-vivo the cardiac fiber arch...
research
∙
01/12/2022
Smoothness and continuity of cost functionals for ECG mismatch computation
The field of cardiac electrophysiology tries to abstract, describe and f...
research
∙
02/22/2021
Learning atrial fiber orientations and conductivity tensors from intracardiac maps using physics-informed neural networks
Electroanatomical maps are a key tool in the diagnosis and treatment of ...
research
∙
02/19/2021
GEASI: Geodesic-based Earliest Activation Sites Identification in cardiac models
The personalization of cardiac models is the cornerstone of patient-spec...
research
∙
02/19/2021
Fast and Accurate Uncertainty Quantification for the ECG with Random Electrodes Location
The standard electrocardiogram (ECG) is a point-wise evaluation of the b...
research
∙
10/30/2020
