Weakly Supervised Medical Image Segmentation With Soft Labels and Noise Robust Loss

no code implementations • 16 Sep 2022 • Banafshe Felfeliyan, Abhilash Hareendranathan, Gregor Kuntze, Stephanie Wichuk, Nils D. Forkert, Jacob L. Jaremko, Janet L. Ronsky

The aim of this paper was to develop and evaluate a method to generate probabilistic labels based on multi-rater annotations and anatomical knowledge of the lesion features in MRI and a method to train segmentation models using probabilistic labels using normalized active-passive loss as a "noise-tolerant loss" function.

Image Segmentation Medical Diagnosis +3