most citedSemantic-aware Random Convolution and Source Matching for Domain Generalization in Medical Image Segmentation

1 citations · 1 across the 1 of their papers we have counts for

collaborators

6 papers

cs.CV20261 cited

Semantic-aware Random Convolution and Source Matching for Domain Generalization in Medical Image Segmentation

Franz Thaler, Martin Urschler, Mateusz Kozinski +3

We tackle the challenging problem of single-source domain generalization (DG) for medical image segmentation, where we train a network on one domain (e.g., CT) and directly apply i…

physics.med-ph2025

Non-Intrusive Parametrized-Background Data-Weak Reconstruction of Cardiac Displacement Fields from Sparse MRI-like Observations

Francesco C. Mantegazza, Federica Caforio, Christoph Augustin +3

Personalized cardiac diagnostics require accurate reconstruction of myocardial displacement fields from sparse clinical imaging data, yet current methods often demand intrusive acc…

math.NA2025

AutoVARP -- a framework for automated reproducible inducibility testing in computational models of cardiac electrophysiology

Paolo Seghetti, Matthias Gsell, Anton Prassk +2

Simulations of Cardiac Electrophysiology are gaining momentum beyond basic mechanistic studies, as an approach for supporting clinical decision making. The potential for in silico…

math.NA2025

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…

q-bio.TO2025

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…

math.NA2025

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…