WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma. (arXiv:2204.06455v1 [eess.IV])

Lung cancer is the leading cause of cancer death worldwide, and
adenocarcinoma (LUAD) is the most common subtype. Exploiting the potential
value of the histopathology images can promote precision medicine in oncology.
Tissue segmentation is the basic upstream task of histopathology image
analysis. Existing deep learning models have achieved superior segmentation
performance but require sufficient pixel-level annotations, which is
time-consuming and expensive. To enrich the label resources of LUAD and to
alleviate the annotation efforts, we organize this challenge WSSS4LUAD …

arxiv challenge segmentation semantic