Use the Mask Before You Trust It: FreNet Reconfigures Visual Priors for Lesion Segmentation
TL;DR for operators An upstream lesion mask can be informative without being reliable enough to use as the final answer. The paper behind FreNet asks a more operationally useful question: can that imperfect mask control how the downstream model represents the image? Its answer is a two-stage design. Before normal feature extraction, the mask helps reweight the input at pixel level. During encoding, the system reorganizes intermediate features by frequency and then restores spatial alignment with a refined version of the prior. In the reported ablations, this distinction matters: on ETIS, the PVT baseline achieves 75.0 Dice, and adding SAM guidance alone also produces 75.0; the full configuration reaches 82.0. ...