Awesome
Synthetic Medical Images from Dual Generative Adversarial Networks
Code is split into two stages: a segmentation-mask-generating DCGAN, and an image-to-image translator using pix2pix.
Paper: https://arxiv.org/abs/1709.01872
SynthMed (Repository for GAN-produced synthetic medical images): https://synthmed.github.io/
Pipeline
Prerequisites
- Python 2 and 3
- numpy
- TensorFlow 1.0+
- Keras
- Preprocessed dataset
Acknowledgements
Stage-I GAN based on: https://github.com/carpedm20/DCGAN-tensorflow <br></br> Stage-II GAN based on: https://github.com/ray0809/pix2pix
Authors: John Guibas, Tejpal Virdi, Peter Li