Code for TMI 2020 "Hi-Net: Hybrid-fusion Network for Multi-modal MR Image Synthesis"

Usage

1. The original implementation of Hi-Net is Pytorch. The code has been tested in Mac and Linux.

2. To run the code, you should first install dependencies:

   pip install fire

3. Setup all parameters in config.py

4. Put your data into ./data (Some samples from BraTs2018 have been stored out in this file)

5. Train

   CUDA_VISIBLE_DEVICES=0,1 python main.py train --batch_size=128 --task_id=2 --gpu_id=[0,1]

   (you can set your parameters when runing the code)

If you use this code, please cite the following papers:

[1] Tao Zhou, Huazhu Fu, Geng Chen, Jianbing Shen, Ling Shao. "Hi-Net: Hybrid-fusion Network for Multi-modal MR Image Synthesis". IEEE Transactions on Medical Imaging (IEEE TMI), 2020. (Offical version)(arXiv version)

Datsets: you can download multi-modal medical datastes from:

[1] BraTs 2018: [HERE]

[2] BraTs 2019: [HERE]

[3] ISLES2015: [HERE]