Lesion Detection in CT with Frozen Self-Distilled Features: SALT, a Spatially Adaptive Label-Guided Temperature

The paper introduces SALT, a spatially adaptive self-distillation method for CT lesion detection. During pretraining, weak box-derived labels identify a compact region on the encoder’s patch grid. Inside that region, SALT sharpens the teacher temperature and increases the masked-patch loss weight, while leaving the masking policy, centering statistics, architecture, and schedule unchanged. At downstream use, the encoder is frozen and operates without labels or conditioning; only a lightweight multi-depth CenterNet-style 3D detection head is trained. The study proposes evaluations across four CT cohorts, lesion-size strata, box quality, and a detector-free follow-up re-identification probe.