Unsupervised Source-Free Ranking of Biomedical Segmentation Models Under Distribution Shift

ArXi:2503.00450v3 Announce Type: replace Model reuse offers a solution to the challenges of segmentation in biomedical imaging, where high data annotation costs remain a major bottleneck for deep learning. However, although many pretrained models are released through challenges, model zoos, and repositories, selecting the most suitable model for a new dataset remains difficult due to the lack of reliable model ranking methods. We