collaborators

6 papers

eess.IV2025

LA-CaRe-CNN: Cascading Refinement CNN for Left Atrial Scar Segmentation

Franz Thaler, Darko Stern, Gernot Plank +1

Atrial fibrillation (AF) represents the most prevalent type of cardiac arrhythmia for which treatment may require patients to undergo ablation therapy. In this surgery cardiac tiss…

cs.CV2025

Augmentation-based Domain Generalization and Joint Training from Multiple Source Domains for Whole Heart Segmentation

Franz Thaler, Darko Stern, Gernot Plank +1

As the leading cause of death worldwide, cardiovascular diseases motivate the development of more sophisticated methods to analyze the heart and its substructures from medical imag…

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…

cs.CV2024

Gaussian Process Emulators for Few-Shot Segmentation in Cardiac MRI

Bruno Viti, Franz Thaler, Kathrin Lisa Kapper +3

Segmentation of cardiac magnetic resonance images (MRI) is crucial for the analysis and assessment of cardiac function, helping to diagnose and treat various cardiovascular disease…

cs.CV2024

Synthetic Augmentation for Anatomical Landmark Localization using DDPMs

Arnela Hadzic, Lea Bogensperger, Simon Johannes Joham +1

Deep learning techniques for anatomical landmark localization (ALL) have shown great success, but their reliance on large annotated datasets remains a problem due to the tedious an…