papers

Publications (13)

physics.flu-dyn2021

On the Incorporation of Obstacles in a Fluid Flow Problem Using a Navier-Stokes-Brinkman Penalization Approach

Jana Fuchsberger, Elias Karabelas, Philipp Aigner +4

Simulating the interaction of fluids with immersed moving solids is playing an important role for gaining a better quantitative understanding of how fluid dynamics is altered by th…

math.NA2023

Real-time whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations

Matteo Salvador, Marina Strocchi, Francesco Regazzoni +3

Cardiac digital twins provide a physics and physiology informed framework to deliver predictive and personalized medicine. However, high-fidelity multi-scale cardiac models remain…

cs.CV2026

The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography

Kaiyuan Yang, Fabio Musio, Yihui Ma +112

The paper introduces the TopCoW Challenge, a benchmark for automatically segmenting the Circle of Willis in CT and MR angiography using deep learning, and provides a new annotated…

#circle of willis segmentation#angiography#deep learning#benchmark challenge
cs.AI2025

Multi-Agent Reasoning for Cardiovascular Imaging Phenotype Analysis

Weitong Zhang, Mengyun Qiao, Chengqi Zang +4

Identifying associations between imaging phenotypes, disease risk factors, and clinical outcomes is essential for understanding disease mechanisms. However, traditional approaches…

eess.IV2025

ISLES'24: Final Infarct Prediction with Multimodal Imaging and Clinical Data. Where Do We Stand?

Ezequiel de la Rosa, Ruisheng Su, Mauricio Reyes +37

Accurate estimation of brain infarction (i.e., irreversibly damaged tissue) is critical for guiding treatment decisions in acute ischemic stroke. Reliable infarct prediction inform…

stat.ME2017

Probabilistic Models for Integration Error in the Assessment of Functional Cardiac Models

Chris. J. Oates, Steven Niederer, Angela Lee +2

This paper studies the numerical computation of integrals, representing estimates or predictions, over the output of a computational model with respect to a distribution $p(…