CRS-Bench: A Reference-Relative Reliability Benchmark for Medical Image Encoders
Pretrained image encoders are central to medical image classification, where expert annotation is costly and task-specific cohorts are often limited. As the model space expands from general-purpose to broad-medical and specialty-specific encoders, selecting the representation becomes a substantive modeling decision. Clean-test discrimination alone is insufficient for this purpose: encoders with similar AUROC can differ in calibration, label efficiency, and stability under acquisition perturbations or distribution shift. We introduce CRS-Bench, a controlled benchmark for multi-objective medical encoder selection. CRS-Bench evaluates 15 pretrained encoder families across dermatology, ophtha...
| Authors | Xingtao Lin, Hangqi Ren, Caiwan Sun et al. |
|---|---|
| Primary category | eess.IV |
| Published | 22 August 2026 |
| Last updated at source | 22 August 2026 |
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