60 citations · 66 across the 12 of their papers we have counts for
12 papers
The MYOSAIQ Challenge: Myocardial Segmentation with Automated Infarct Quantification
Olivier Bernard, William A. Romero R., Cyprien Bouton +24
Late gadolinium enhancement (LGE) cardiac magnetic resonance (MR) imaging is the modality of choice to assess myocardial infarction (MI) lesions. Nowadays MI volume quantification…
cAPM: Continual AI-Assisted Pace-Mapping with Active Learning
Dylan O'Hara, Pradeep Bajracharya, Casey Meisenzahl +7
Ventricular tachycardia is a life-threatening rhythm disorder and a major cause of sudden cardiac death. Pace-mapping is a clinical procedure for identifying the intervention targe…
Explainable Deep Learning-based Classification of Wolff-Parkinson-White Electrocardiographic Signals
Alice Ragonesi, Stefania Fresca, Karli Gillette +3
Wolff-Parkinson-White (WPW) syndrome is a cardiac electrophysiology (EP) disorder caused by the presence of an accessory pathway (AP) that bypasses the atrioventricular node, faste…
Computational Modeling of Selective Capture Mechanisms in Conduction System Pacing
Mohammadreza Kariman, Matthias A. F. Gsell, Edward J. Vigmond +3
CSP is gaining clinical significance owing to its ability to restore a physiological activation sequence in the ventricles. While His bundle pacing (HBP) producing the most physiol…
An efficient end-to-end computational framework for the generation of ECG calibrated volumetric models of human atrial electrophysiology
Elena Zappon, Luca Azzolin, Matthias A. F. Gsell +12
Computational models of atrial electrophysiology (EP) are increasingly utilized for applications such as the development of advanced mapping systems, personalized clinical therapy…
Integrating anatomy and electrophysiology in the healthy human heart: Insights from biventricular statistical shape analysis using universal coordinates
Lore Van Santvliet, Elena Zappon, Matthias A. F. Gsell +9
A cardiac digital twin is a virtual replica of a patient-specific heart, mimicking its anatomy and physiology. A crucial step of building a cardiac digital twin is anatomical twinn…
Accurate and Efficient Cardiac Digital Twin from surface ECGs: Insights into Identifiability of Ventricular Conduction System
Thomas Grandits, Karli Gillette, Gernot Plank +1
Digital twins for cardiac electrophysiology are an enabling technology for precision cardiology. Current forward models are advanced enough to simulate the cardiac electric activit…
Multi-Source and Multi-Sequence Myocardial Pathology Segmentation Using a Cascading Refinement CNN
Franz Thaler, Darko Stern, Gernot Plank +1
Myocardial infarction (MI) is one of the most prevalent cardiovascular diseases and consequently, a major cause for mortality and morbidity worldwide. Accurate assessment of myocar…
Quantifying variabilities in cardiac digital twin models of the electrocardiogram
Elena Zappon, Matthias A. F. Gsell, Karli Gillette +1
Cardiac digital twins (CDTs) of human cardiac electrophysiology (EP) are digital replicas of patient hearts that match like-for-like clinical observations. The electrocardiogram (E…
pyCEPS: A cross-platform Electroanatomic Mapping Data to Computational Model Conversion Platform for the Calibration of Digital Twin Models of Cardiac Electrophysiology
Robert Arnold, Anton J. Prassl, Aurel Neic +7
Background and Objective: Data from electro-anatomical mapping (EAM) systems are playing an increasingly important role in computational modeling studies for the patient-specific c…
CaRe-CNN: Cascading Refinement CNN for Myocardial Infarct Segmentation with Microvascular Obstructions
Franz Thaler, Matthias A. F. Gsell, Gernot Plank +1
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)…
Physics-informed Neural Network Estimation of Material Properties in Soft Tissue Nonlinear Biomechanical Models
Federica Caforio, Francesco Regazzoni, Stefano Pagani +5
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 in…