OHBM 2019 - Deep Brain Synthesis Tutorial

Deep brain synthesis tutorial for the 2019 Organization for Human Brain Mapping Conference in Rome using 3D Conditional Improved Conditional Wasserstein Generative Adversarial Networks on the Neurovault Collection 1952 BrainPedia dataset.

Instructions

1. Clone the repository:

git clone https://github.com/BlissChapman/OHBMDeepBrainSynthesisTutorial

2. Install dependencies:

cd OHBMDeepBrainSynthesisTutorial
python3 -m pip install -r requirements.txt --user

3. Start a Jupyter notebook server:

jupyter notebook

4. Select Tutorial.ipynb and enjoy!

References

M. Arjovsky, S. Chintala, and L. Bottou. Wasserstein GANs. arXiv preprint arXiv:1701.07875, 2017.

J. Dubois and R. Adolphs. Building a science of individual differences from fMRI. Trends in cognitive sciences, 2016.

I. J. Goodfellow, J. A. Pouget, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio. Generative Adversarial Nets. In Advances in neural information processing systems, 2014.

KJ Gorgolewski, G. Varoquaux, G. Rivera, Y. Schwarz, SS Ghosh, C. Maumet, VV. Sochat, T. E Nichols, Russell A Poldrack, J-B. Poline, et al. Neurovault. org: a web-based repository for collecting and sharing unthresholded statistical maps of the human brain. Frontiers in neuroinformatics, 9, 2015.

I. Gulrajani, F. Ahmed,M. Arjovsky, V. Dumoulin, and A. Courville. Improved training of Wasserstein GANs. arXiv preprint arXiv:1704.00028, 2017.

M. Mirza and S. Osindero. Conditional Generative Adversarial Nets. arXiv preprint arXiv:1411.1784, 2014.

Contact Information

• Sanmi Koyejo - [email protected]
• Bliss Chapman - [email protected]