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The source code of 'Diagnose Like A Pathologist: Weakly-Supervised Pathologist-Tree Network for Slide-Level Immunohistochemical Scoring' (AAAI 2021).

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PTree-Net

This repository is an official PyTorch implementation of the paper "Diagnose Like A Pathologist: Weakly-Supervised Pathologist-Tree Network for Slide-Level Immunohistochemical Scoring" [paper] from AAAI 2021.

Dependencies

  • Python 3.6
  • PyTorch >= 1.5.0
  • torch-geometric
  • numpy
  • sklearn
  • openslide

Quickstart

  • Train the PTree-Net with your HER2 WSI dataset:
python ./train.py 

Cite

If you find our work useful in your research or publication, please cite our work:

@inproceedings{chen2021diagnose,
  title={Diagnose Like A Pathologist: Weakly-Supervised Pathologist-Tree Network for Slide-Level Immunohistochemical Scoring},
  author={Chen, Zhen and Zhang, Jun and Che, Shuanlong and Huang, Junzhou and Han, Xiao and Yuan, Yixuan},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  year={2021}
}

Acknowledgements

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The source code of 'Diagnose Like A Pathologist: Weakly-Supervised Pathologist-Tree Network for Slide-Level Immunohistochemical Scoring' (AAAI 2021).

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