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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…
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…
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…
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…