SegEVOLution: Towards Multimodal Medical Image Segmentation with Context-Prior Learning
Published in GitHub, 2024
Co-authored a project to evaluate the transferability of SegVol, a 3D SAM-based segmentation foundation model, across different medical imaging modalities (CT and MRI). We extended SegVol’s capabilities through LoRA fine-tuning and context-priors (Gao et al., 2023), improving segmentation scores with both approaches.
Recommended citation: Z. Fülöp, S. Mihailov, M. Krastev, M. Hamar, D.A. Toapanta, S. Achlatis. (2025). SegEVOLution: Towards Multimodal Medical Image Segmentation with Context-Prior Learning.