Yingyu Chen

Counterintuitively, the most *unreliable* samples in medical imaging datasets—those with fluctuating confidence and frequent forgetting during training—are the *most* informative for building accurate decision boundaries.

By explicitly modeling the manifold structure induced by different CT scanning protocols, this work achieves superior generalization in unsupervised NICT enhancement, overcoming limitations of methods that assume homogeneous noise.