Update README.md

README.md

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----
-license: apache-2.0
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+# Gastric Cancer Tissue Segmentation Dataset  
+
+**License:** [Apache-2.0](https://opensource.org/licenses/Apache-2.0)  
+
+---
+
+## Overview  
+
+This dataset is designed for **tissue segmentation** in gastric cancer cases. It consists of **100 Regions of Interest (ROIs)** extracted from Whole Slide Images (WSIs) of 100 gastric cancer cases.  
+
+![Gastric Cancer Segmentation](https://cdn-uploads.huggingface.co/production/uploads/65f978b2119e70f4dbb7c6b1/zDW5HvtTGYS2xSUGQ5kAJ.png)
+
+### Tissue Types  
+Six tissue types are annotated:  
+1. **Tumor**  
+2. **Lymphoid stroma**  
+3. **Desmoplastic stroma**  
+4. **Smooth muscle**  
+5. **Necrosis**  
+6. **Others**  
+
+---
+
+## Data Source  
+
+The original WSIs are sourced from the **TCGA (The Cancer Genome Atlas)** database.  
+
+- **Mean size of ROIs**: 4655 × 5276 pixels  
+
+---
+
+## Annotation Process  
+
+- The annotated ROIs achieved a **78% one-time acceptance rate**.  
+- The remaining annotations were **accepted after one revision**.  
+- Pathologists performed minor corrections on **8.4% of all pixels** in total.  
+
+---
+
+## Data Organization  
+
+The dataset includes:  
+1. **ROIs (image patches)**:  
+   - Saved as `.png` files under the corresponding folders.  
+2. **Annotations**:  
+   - Each ROI's annotation is saved as a `.txt` file under the corresponding folders.  
+   - The annotation is a pixel-wise matrix with the following values:  
+     - **1**: Tumor  
+     - **2**: Lymphoid stroma  
+     - **3**: Desmoplastic stroma  
+     - **4**: Smooth muscle  
+     - **5**: Necrosis  
+     - **6**: Others  
+     - **-1**: Equal to 6 (others)  
+
+---
+
+## Usage and Restrictions  
+
+- This dataset is **for research purposes only**.  
+- **Commercial use is strictly prohibited**.  
+
+If you use this dataset in your research, you must cite the following publication:  
+
+```bibtex
+@article{gao2022unsupervised,
+  title={Unsupervised representation learning for tissue segmentation in histopathological images: From global to local contrast},
+  author={Gao, Zeyu and Jia, Chang and Li, Yang and Zhang, Xianli and Hong, Bangyang and Wu, Jialun and Gong, Tieliang and Wang, Chunbao and Meng, Deyu and Zheng, Yefeng and others},
+  journal={IEEE Transactions on Medical Imaging},
+  volume={41},
+  number={12},
+  pages={3611--3623},
+  year={2022},
+  publisher={IEEE}
+}
+```
+