Benchmarking Foundation and Large Language Models for Few-Shot Medical Image Segmentation
FAME is introduced, a unified benchmark for evaluating FS-MIS solutions, covering specialists, SAM-based methods, CLIP-based methods, and MLLM-based methods, and evaluates models under zero-shot and ten-shot settings with additional assessment of target-absence recognition and generalization under covariate and semanti...