The project will apply the deep learning and AI training expertise of Facebook's FAIR initiative to an imaging data set of 10,000 clinical cases collected exclusively by NYU that comprise approximately three million MR images of the knee, brain and liver.

“Our goals are to open-source this project to allow the wider research community to build on our developments in the interest of advancing the state of the art in medical imaging as quickly as possible,” Lui said. “Longer-term, we hope one day that because of this project, MR will be able to replace X-ray or CT for certain applications, also leading to decreased radiation exposure to patients. However, we hope to apply these techniques to other imaging modalities such as CT, enabling ultra-low-dose scans and decreasing patient exposure to radiation.”


Facebook will share AI models, baselines and evaluation metrics as research progresses. NYU School of Medicine will open-source the image data set.

The project is fully HIPAA-compliant and approved under NYU Langone’s Institutional Review Board, which oversees all human subject research at the medical center. It is filed under strict human data protection regulations.

No Facebook data will be used in the research.

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