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
- GCN implementation with PyTorch Geometric.