The NYU School of Medicine’s department of radiology and Facebook recently announced a new collaborative research project focused on using artificial intelligence (AI) to make MRI scans up to 10 times faster. While some worry about AI’s impact in medical imaging, the potential for life-saving developments in medicine cannot be ignored.

Daniel Sodickson, MD, PhD, vice chair for research in radiology and director of the Center for Advanced Imaging Innovation and Research at NYU School of Medicine, is leading the collaboration. He spoke with Radiology Business about AI in medical imaging, while discussing a number of concepts that can be applied elsewhere.

Radiology Business: How did NYU end up teaming up with Facebook on this project?

Daniel Sodickson, MD, PhD: Here at NYU, we have been working on accelerating MRI by any means available. In 2016, we described some of the first uses of deep learning for image reconstruction from accelerated data acquisitions, and now that is an exploding area in MR research. There were three abstracts on that topic at the 2016 annual meeting of the International Society for Magnetic Resonance in Medicine—one of them was ours—and closer to 100 in 2018. So this is a fast-moving field very much in its “Wild West” phase and in need of real AI expertise combined with real physics and biology expertise.

A colleague at NYU connected us with the Facebook Artificial Intelligence Research (FAIR) group, and the challenge of reconstructing fast MR images from limited data really appealed to them, both because it raised fundamental questions for AI and because it addressed a problem with a significant impact. It became clear early on in our conversations with FAIR that this would be a really synergistic partnership.

Get the full interview with Radiology Business at the link below: