3 papers
cs.CV2026
Super-Generalist: Towards Comprehensive and Accurate Medical Image Understanding via Generalist-Specialist Synergy
Shaoteng Zhang, Weiwei Cao, Wanxing Chang +9
Medical images require comprehensive and accurate interpretation to support the diagnosis of diverse clincial conditions. Recent vision-language generalist models offer broad task…
cs.CV2026
Attention-Based Prototype Calibration for Multi-Rater Few-Shot Medical Image Segmentation
Truong Vu, Minh Khoi Ho, Yutong Xie
Few-shot medical image segmentation methods typically assume a single ground-truth annotation, overlooking systematic variability across expert raters commonly observed in clinical…
cs.CV2025
Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang +50
How can we test AI performance? This question seems trivial, but it isn't. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified…