27 citations · 29 across the 5 of their papers we have counts for
5 papers
WSSS4LUAD: Grand Challenge on Weakly-supervised Tissue Semantic Segmentation for Lung Adenocarcinoma
Chu Han, Xipeng Pan, Lixu Yan +40
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 pr…
A Standardized Pipeline for Colon Nuclei Identification and Counting Challenge
Jijun Cheng, Xipeng Pan, Feihu Hou +5
Nuclear segmentation and classification is an essential step for computational pathology. TIA lab from Warwick University organized a nuclear segmentation and classification challe…
RestainNet: a self-supervised digital re-stainer for stain normalization
Bingchao Zhao, Jiatai Lin, Changhong Liang +8
Color inconsistency is an inevitable challenge in computational pathology, which generally happens because of stain intensity variations or sections scanned by different scanners.…
PDBL: Improving Histopathological Tissue Classification with Plug-and-Play Pyramidal Deep-Broad Learning
Jiatai Lin, Guoqiang Han, Xipeng Pan +11
Histopathological tissue classification is a fundamental task in pathomics cancer research. Precisely differentiating different tissue types is a benefit for the downstream researc…
Multi-Layer Pseudo-Supervision for Histopathology Tissue Semantic Segmentation using Patch-level Classification Labels
Chu Han, Jiatai Lin, Jinhai Mai +15
Tissue-level semantic segmentation is a vital step in computational pathology. Fully-supervised models have already achieved outstanding performance with dense pixel-level annotati…