Diagnosis of recurrence of nasopharyngeal carcinoma

Introduction

This repository is for our paper 'MRI-based deep learning model for surveillance and contour of local recurrence for nasopharyngeal carcinoma patients from national to community hospitals'.

Usage

Training:

Detection and classification

Run python main_ddp.py

Segmentation

Run python main_seg.py

Inference:

Detection and classification

Run python inference_cls.py

Segmentation

Run python inference_seg.py

Result

Result of classification (AUC)

Network	SYSUCC test A set	SYSUCC test B set	SYSUCC test C set	SYSUCC test D set	Guangzhou test set	Zhongshan test set	Zhuhai test set
det+cls	0.91	0.90	0.94	0.86	0.89	0.88	0.86

Comparative Experiment of segmentation (DSC)

Network	Val set	Test1 set	SYSUCC set	External set
3D UNet	0.584	0.522	0.539	0.336
3D VNet	0.621	0.627	0.625	0.441
2.5D VNet	0.632	0.664	0.640	0.445

Citation

If you use xxx in your research, please cite the paper:

@inproceedings{xxx,
  title={MRI-based deep learning model for surveillance and contour of local recurrence for nasopharyngeal carcinoma patients from national to community hospitals},
  author={xxx},
  journal={xxx},
  year={2022}
}