Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-aware Contrastive Distillation. (arXiv:2206.02307v1 [cs.CV])

Contrastive learning has shown great promise over annotation scarcity
problems in the context of medical image segmentation. Existing approaches
typically assume a balanced class distribution for both labeled and unlabeled
medical images. However, medical image data in reality is commonly imbalanced
(i.e., multi-class label imbalance), which naturally yields blurry contours and
usually incorrectly labels rare objects. Moreover, it remains unclear whether
all negative samples are equally negative. In this work, we present ACTION, an
Anatomical-aware ConTrastive dIstillatiON framework, for semi-supervised …

arxiv bootstrapping cv distillation image medical segmentation semi-supervised