17 citations · 26 across the 14 of their papers we have counts for
8 papers · 1 filter
Zero-Shot Brain MRI Inpainting with 2.5D Unconditional Flow Priors
Arnela Hadzic, Franz Thaler, Simon Johannes Joham +1
Generative inpainting of brain MRI volumes is essential for synthesizing healthy tissue in pathological regions, improving the accuracy and reliability of automated downstream brai…
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…
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…
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…
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…
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)…
Biomedical image analysis competitions: The state of current participation practice
Matthias Eisenmann, Annika Reinke, Vivienn Weru +352
The number of international benchmarking competitions is steadily increasing in various fields of machine learning (ML) research and practice. So far, however, little is known abou…
Modeling Annotation Uncertainty with Gaussian Heatmaps in Landmark Localization
Franz Thaler, Christian Payer, Martin Urschler +1
In landmark localization, due to ambiguities in defining their exact position, landmark annotations may suffer from large observer variabilities, which result in uncertain annotati…