zwq1230 / deepflash Goto Github PK

*********** DeepFLASH **********
This repository contains source code and data of a predictive diffeomorphic image registration (https://arxiv.org/abs/2004.02097).

```
@inproceedings{wang2020deepflash,
  title={DeepFLASH: An Efficient Network for Learning-based Medical Image Registration},
  author={Wang, Jian and Zhang, Miaomiao},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={4444--4452},
  year={2020}
}
```
********** Disclaimer **********
This software is published for academic and non-commercial use only.

********** DeepFLASH **********
The implementation includes network training, testing and for 2D and 3D medical images. We request you to cite our research paper if you use it:

DeepFLASH: An Efficient Network for Learning-basedMedical Image Registration.
Jian Wang, Miaomiao Zhang. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.


********** Setup **********
* [PyTorch 3.4](http://pytorch.org/)
* [PyCA](https://bitbucket.org/scicompanat/pyca) (optional)
* [FLASH] (https://bitbucket.org/FlashC/flashc/src/master/)
* [CUDA 9.0](https://developer.nvidia.com/cuda-downloads)
* [Anaconda 4.3.1](https://anaconda.org)

********** Preprocessing **********
The optimal registration solutions for our network training is generated by FLASH.
You may run the MATLAB preprocess scripts provided in "/DeepFLASH/preprocess/processmhd.m" to generated training data for our network. 

Preprocessed data are included in directory "/DeepFLASH/data/Rnet/" and  "/DeepFLASH/data/Inet" separately. 

**********Usage **********
Below is a simple *quickstart* guide on how to use DeepFLASH for predictive registration network training. 

cd DeepFLASH/
sh runDeepFLASH.sh 

We take the frequencies from of training data directly in this network. Details can be checked by, 

python3 DeepFLASH_test.py -h 

 --im_src_realpart IM_SRC_REALPART
                        root directory of real parts of source images
  --im_tar_realpart IM_TAR_REALPART
                        root directory of real parts of target images
  --im_vel_realX IM_VEL_REALX
                        root directory of real parts of velocity fields (X
                        direction)
  --im_vel_realY IM_VEL_REALY
                        root directory of real parts of velocity fields (Y
                        direction)
  --im_vel_realZ IM_VEL_REALZ
                        root directory of real parts of velocity fields (Z
                        direction)
  --im_src_imaginarypart IM_SRC_IMAGINARYPART
                        root directory of imaginary parts of source images
  --im_tar_imaginarypart IM_TAR_IMAGINARYPART
                        root directory of imaginary parts of target images
  --im_vel_imagX IM_VEL_IMAGX
                        root directory of imaginary parts of source images (X
                        direction)
  --im_vel_imagY IM_VEL_IMAGY
                        root directory of imaginary parts of velocity fields
                        (Y direction)
  --im_vel_imagZ IM_VEL_IMAGZ
                        root directory of imaginary parts of velocity fields
                        (Z direction)