Semi-Supervised Pixel Contrastive Learning Framework for Tissue Segmentation in Histopathological Image (JBHI 2023)

Gastric Cancer Semantic Segmentation (GCSS) dataset

• Download link:
  • Baidu Cloud: https://pan.baidu.com/s/1EEmuDCQez1odggab3lElFQ; Extraction code: GCSS
  • Zenodo: https://zenodo.org/record/8176354
• Annotation: The annotation of each ROI is a pixel matrix. {1,2,3,4,5} represent tumor, lymphoid stroma, desmoplastic stroma, smooth muscle, and necrosis. {-1, 0, 6} represent others.
• Data statistics: 100 ROIs cropped from the 100 gastric cancer cases of the TCGA-STAD project.

Citation

If you find our work helpful for your research, please consider citing:

@ARTICLE{SSPCL,
  author={Shi, Jiangbo and Gong, Tieliang and Wang, Chunbao and Li, Chen},
  journal={IEEE Journal of Biomedical and Health Informatics}, 
  title={Semi-Supervised Pixel Contrastive Learning Framework for Tissue Segmentation in Histopathological Image}, 
  year={2023},
  volume={27},
  number={1},
  pages={97-108},
  doi={10.1109/JBHI.2022.3216293}}