1 citations · 1 across the 2 of their papers we have counts for
4 papers
Evaluation of Anatomical Shape Priors in Deep Learning-Based Cardiac Multi-Compartment Segmentation
Michael Hudler, Franz Thaler, Martin Urschler
Whole-heart multi-compartment CT segmentation is clinically important, but standard CNNs do not explicitly enforce anatomical plausibility. Based on statistics derived from the tra…
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…
Flow Matching for Conditional MRI-CT and CBCT-CT Image Synthesis
Arnela Hadzic, Simon Johannes Joham, Martin Urschler
Generating synthetic CT (sCT) from MRI or CBCT plays a crucial role in enabling MRI-only and CBCT-based adaptive radiotherapy, improving treatment precision while reducing patient…
Restora-Flow: Mask-Guided Image Restoration with Flow Matching
Arnela Hadzic, Franz Thaler, Lea Bogensperger +2
Flow matching has emerged as a promising generative approach that addresses the lengthy sampling times associated with state-of-the-art diffusion models and enables a more flexible…