Update README.md

README.md

@@ -1,3 +1,47 @@
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-license: openmdw-1.0
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+---
+license: openmdw-1.0
+---
+
+# nnUNet_MSWAL
+
+nnU-Net models for **MSWAL** lesion segmentation.
+
+This repository contains nnU-Net models trained on the MSWAL dataset for 1000 and 4000 epochs.
+
+Available model directories:
+- `nnUNetTrainer__nnUNetResEncUNetLPlans__3d_fullres`
+- `nnUNetTrainer_4000epochs__nnUNetResEncUNetLPlans__3d_fullres`
+
+## Inference
+
+Place model in `nnUNet_results` directory; ensure nnU-Net environment variables are set; prediction can be run as follows:
+
+```bash
+nnUNetv2_predict \
+  -i INPUT_FOLDER \
+  -o OUTPUT_FOLDER \
+  -d 201 \
+  -c 3d_fullres \
+  -f 0 1 2 3 4 \
+  # use nnUNetTrainer_4000epochs for the 4000-epoch model
+  -tr nnUNetTrainer \
+  -p nnUNetResEncUNetLPlans
+```
+
+## Reference
+
+Please cite the original MSWAL work and refer to the official project resources.
+
+```bibtex
+@inproceedings{wu2025mswal,
+  title={Mswal: 3d multi-class segmentation of whole abdominal lesions dataset},
+  author={Wu, Zhaodong and Zhao, Qiaochu and Hu, Ming and Li, Yulong and Xue, Haochen and Jiang, Zhengyong and Stefanidis, Angelos and Wang, Qiufeng and Razzak, Imran and Ge, Zongyuan and others},
+  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
+  pages={378--388},
+  year={2025},
+  organization={Springer}
+}
+```
+
+Official MSWAL repository:
+https://github.com/haochen-MBZUAI/MSWAL-