:pig2: LNMNet

This is a PyTorch/GPU implementation of our Modern Pathology 2023 paper Predicting Lymph Node Metastasis from Primary Cervical Squamous Cell Carcinoma Based on Deep Learning in Histopathological Images.

<p align="center"> <img src="https://github.com/miccaiif/LNMNet/blob/main/work_flow.jpg" width="720"> </p>

For training

• Please refer to the training code for model training.

<p align="center"> <img src="https://github.com/miccaiif/LNMNet/blob/main/framework.jpg" width="720"> </p>

For inference

• Please refer to the testing code for model inference.

<p align="center"> <img src="https://github.com/miccaiif/LNMNet/blob/main/ROC_curve.jpg" width="720"> </p>

For attention-based visualization

• Please refer to the attention visualization for localization of key instances.

<p align="center"> <img src="https://github.com/miccaiif/LNMNet/blob/main/attention.png" width="720"> </p>

Citation

If this work is helpful to you, please cite it as:

@article{guo2023predicting,
  title={Predicting Lymph Node Metastasis from Primary Cervical Squamous Cell Carcinoma Based on Deep Learning in Histopathological Images},
  author={Guo, Qinhao and Qu, Linhao and Zhu, Jun and Li, Haiming and Wu, Yong and Wang, Simin and Yu, Min and Wu, Jiangchun and Wen, Hao and Ju, Xingzhu and others},
  journal={Modern Pathology},
  pages={100316},
  year={2023},
  publisher={Elsevier}
}

Contact Information

If you have any question, please email to me lhqu20@fudan.edu.cn.