DoDNet

This repo holds the pytorch implementation of DoDNet and TransDoDNet:

DoDNet: Learning to segment multi-organ and tumors from multiple partially labeled datasets (https://arxiv.org/pdf/2011.10217.pdf)
Learning from partially labeled data for multi-organ and tumor segmentation (https://arxiv.org/pdf/2211.06894.pdf)

Usage

1. MOTS Dataset Preparation

Before starting, MOTS should be re-built from the serveral medical organ and tumor segmentation datasets

Partial-label task	Data source
Liver	data
Kidney	data
Hepatic Vessel	data
Pancreas	data
Colon	data
Lung	data
Spleen	data

• Preprocessed data will be available soon.

2. Training/Testing/Evaluation

sh run_script.sh

3. Citation

If this code is helpful for your study, please cite:

@inproceedings{zhang2021dodnet,
  title={DoDNet: Learning to segment multi-organ and tumors from multiple partially labeled datasets},
  author={Zhang, Jianpeng and Xie, Yutong and Xia, Yong and Shen, Chunhua},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={},
  year={2021}
}
@article{xie2023learning,
  title={Learning from partially labeled data for multi-organ and tumor segmentation},
  author={Xie, Yutong and Zhang, Jianpeng and Xia, Yong and Shen, Chunhua},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2023}
}