no code implementations • 18 Dec 2023 • Franz Thaler, Matthias A. F. Gsell, Gernot Plank, Martin Urschler
Late gadolinium enhanced (LGE) magnetic resonance (MR) imaging is widely established to assess the viability of myocardial tissue of patients after acute myocardial infarction (MI).
no code implementations • 15 Dec 2023 • Federica Caforio, Francesco Regazzoni, Stefano Pagani, Elias Karabelas, Christoph Augustin, Gundolf Haase, Gernot Plank, Alfio Quarteroni
The development of biophysical models for clinical applications is rapidly advancing in the research community, thanks to their predictive nature and their ability to assist the interpretation of clinical data.
3 code implementations • 29 Nov 2022 • Karli Gillette, Matthias A. F. Gsell, Claudia Nagel, Jule Bender, Bejamin Winkler, Steven E. Williams, Markus Bär, Tobias Schäffter, Olaf Dössel, Gernot Plank, Axel Loewe
Mechanistic cardiac electrophysiology models allow for personalized simulations of the electrical activity in the heart and the ensuing electrocardiogram (ECG) on the body surface.
1 code implementation • 28 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.
no code implementations • 12 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.
no code implementations • 22 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.
no code implementations • 12 Jan 2021 • Laura Marx, Justyna A. Niestrawska, Matthias A. F. Gsell, Federica Caforio, Gernot Plank, Christoph M. Augustin
Image-based computational models of the heart represent a powerful tool to shed new light on the mechanisms underlying physiological and pathological conditions in cardiac function and to improve diagnosis and therapy planning.
no code implementations • 16 Sep 2020 • Christoph M. Augustin, Matthias A. F. Gsell, Elias Karabelas, Erik Willemen, Frits W. Prinzen, Joost Lumens, Edward J. Vigmond, Gernot Plank
Computer models of cardiac electro-mechanics (EM) show promise as an effective means for quantitative analysis of clinical data and, potentially, for predicting therapeutic responses. realize such advanced applications methodological key challenges must be addressed.