3 papers
cs.CV2026
A Few Cases Are All You Need: An Empirical Study of Annotation-Efficient LoRA Fine-Tuning of MedSAM3
Sachin Dudda Nagaraju, Bendik Skarre Abrahamsen, Ashkan Moradi +1
Medical image segmentation is essential for clinical workflows such as treatment planning and disease assessment. While specialist tools like TotalSegmentator and MRSegmentator ach…
cs.CV2026
Federated Learning for Cross-Modality Medical Image Segmentation via Augmentation-Driven Generalization
Sachin Dudda Nagaraju, Ashkan Moradi, Bendik Skarre Abrahamsen +1
Artificial intelligence has emerged as a transformative tool in medical image analysis, yet developing robust and generalizable segmentation models remains difficult due to fragmen…
cs.CV2025
FedGIN: Federated Learning with Dynamic Global Intensity Non-linear Augmentation for Organ Segmentation using Multi-modal Images
Sachin Dudda Nagaraju, Ashkan Moradi, Bendik Skarre Abrahamsen +1
Medical image segmentation plays a crucial role in AI-assisted diagnostics, surgical planning, and treatment monitoring. Accurate and robust segmentation models are essential for e…