The goal of this research partnership is to see if using AI can make MRI scans up to 10 times faster. MRIs work by gathering data and turning it into cross-sectional images of internal body structures, like organs and blood vessels. But as the area that needs to be scanned gets larger, so does the scan time. That’s where AI might be able to help. The NYU and FAIR researchers want to speed up scans by collecting less raw data and having trained neural networks fill in the gaps. “The key is to train artificial neural networks to recognize the underlying structure of the images in order to fill in views omitted from the accelerated scan,” said researchers in a blog postabout the work.

The project will use around 10,000 clinical cases and 3 million MRI images that have been stripped of all patient information. The team plans to make the work open-source, making its AI models, baselines, evaluation metrics and image data sets available to other researchers.