Joint-phase Attention Network for Breast Cancer Segmentation in DCE-MRI

by Rian Huang, Zeyan Xu, Yu Xie, Hong Wu, Zixian Li, Yanfen Cui, Yingwen Huo, Chu Han, Xiaotang Yang*, Zaiyi Liu*, Yi Wang*

Introduction

This repository is for our ESWA 2023 paper 'Joint-phase Attention Network for Breast Cancer Segmentation in DCE-MRI'.

Installation

This repository is based on PyTorch 1.7.1.

Usage

1. Clone the repository:

   git clone https://github.com/ryandok/JPA.git
   cd JPA

2. Preprocess data including CropZeroZone, Resample, Normalization on C1, C0, BreastPred of the input. Reference: nnUNet

3. Internal structure of data folders:

   ${data}
      [RawData]
          [DCE-C0]
              - DCE-C0_0000000.nii.gz
              - DCE-C0_0000001.nii.gz
              ...
          [DCE-C1]
              - DCE-C1_0000000.nii.gz
              - DCE-C1_0000001.nii.gz
              ...
          [TumorMask]
              - TumorMask_0000000.nii.gz
              - TumorMask_0000001.nii.gz
              ...
      
      [Processed]
          [DCE-C0]
              - DCE-C0_0000000.nii.gz
              - DCE-C0_0000001.nii.gz
              ...
          [DCE-C1]
              - DCE-C1_0000000.nii.gz
              - DCE-C1_0000001.nii.gz
              ...
          [BreastPred]
              - BreastPred_0000000.nii.gz
              - BreastPred_0000001.nii.gz
              ...
          [TumorMask]
              - TumorMask_0000000.nii.gz
              - TumorMask_0000001.nii.gz
              ...
          
   

4. Train the model:

   cd code
   python train_JPAnet_3channels_C1&C0&Breast.py --gpu 0 --data_root_path YOUR_PROCESSED_DATA --img1_prefix=DCE-C1 --img2_prefix=DCE-C0 --img3_prefix=BreastPred --label_prefix=TumorMask

5. Test the model:

   modified 
   'utils.image_processing_breastSeg.ImageProcessingBreastSeg' and
   'utils.image_processing_tumorSeg.ImageProcessingTumorSegOriginRegion'
   according to your preprocess methods.
   

   cd code
   python test_TumorSeg_OriginRes_onBreastPred.py --gpu 0 --data_root_path YOUR_RAW_DATA --img1_prefix=DCE-C1 --img2_prefix=DCE-C0  --label_prefix=TumorMask --backbone=JPAnet_C1&C0&Breast --exp_name=YOUR_EXP_NAME

Citation

If JPA is useful for your research, please consider citing:

@article{huang2023joint,
    title={Joint-phase attention network for breast cancer segmentation in DCE-MRI},
    author={Huang, Rian and Xu, Zeyan and Xie, Yu and Wu, Hong and Li, Zixian and Cui, Yanfen and Huo, Yingwen and Han, Chu and Yang, Xiaotang and Liu, Zaiyi and others},
    journal={Expert Systems with Applications},
    pages={119962},
    year={2023},
    publisher={Elsevier}}