research
∙
08/02/2023
Physics-informed neural networks for blood flow inverse problems
Physics-informed neural networks (PINNs) have emerged as a powerful tool...
share
research
∙
07/24/2023
Unsupervised reconstruction of accelerated cardiac cine MRI using Neural Fields
Cardiac cine MRI is the gold standard for cardiac functional assessment,...
research
∙
01/20/2023
Benchmarks for physics-informed data-driven hyperelasticity
Data-driven methods have changed the way we understand and model materia...
research
∙
11/22/2022
WarpPINN: Cine-MR image registration with physics-informed neural networks
Heart failure is typically diagnosed with a global function assessment, ...
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
∙
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
∙
05/09/2019