This project is for medical image synthesis with generative adversarial networks (GAN), such as, synthesize CT from MRI, 7T from 3T, high does PET from low dose PET.
Currently, we have uploaded a 2D/3D GAN in this repository (2D is in the root folder, and 3D version is in the folder of '3dversion'). Detailed information can be found in our paper:
Medical Image Synthesis with Context-Aware Generative Adversarial Networks
If it is helpful for you, please cite our paper:
@inproceedings{nie2017medical, title={Medical image synthesis with context-aware generative adversarial networks}, author={Nie, Dong and Trullo, Roger and Lian, Jun and Petitjean, Caroline and Ruan, Su and Wang, Qian and Shen, Dinggang}, booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention}, pages={417--425}, year={2017}, organization={Springer} }
The main entrance for the code is main.py
I suppose you have installed:
tensorflow (>=0.12.1)
simpleITK
numpy
Steps to run the code (since the code is implemented as early as 2016, part of the codes are deprecated, you can refer to our pytorch version for new implementations):
BTW, you can download a real medical image synthesis dataset for reconstructing standard-dose PET from low-dose PET via this link: https://www.aapm.org/GrandChallenge/LowDoseCT/
Also, there are some MRI synthesis datasets available: http://brain-development.org/ixi-dataset/
medSynthesis is released under the MIT License (refer to the LICENSE file for details).