The Geometry of Transfer: Unlocking Medical Vision Manifolds for Training-Free Model Ranking

Researchers developed a new framework for selecting optimal medical AI foundation models without costly fine-tuning, achieving 31% better performance than existing methods. The topology-driven approach evaluates manifold tractability rather than statistical overlap to better assess model transferability for medical image segmentation tasks.