Facebook, NYU Pin Hope of Faster MRIs on Artificial Intelligence

This could be important because now it can take an hour or more to produce a good MRI scan.

The radiology department at New York University School of Medicine in New York City has joined forces with Facebook to launch fastMRI, a collaborative research project applying artificial intelligence to MRI scans.

To realize those benefits, NYU is exploring using technology to reconstruct data generated during fast MRI scans.

"We have some great physicists here and even some hot-stuff mathematicians, but Facebook and FAIR have some of the leading AI scientists in the world", Dan Sodickson, director of the Center of Advanced Imaging Innovation and Research at NYU, told TechCrunch. They use the data to build cross-sectional images of... More data means more time in the MRI machine. These tests can take up to an hour, during which time the patient must stay completely still so as not to distort the image. Rather, the hope is to advance an important machine learning technique, and to help attract AI researchers keen to work on meaningful stuff.

Facebook noted "a few missing or incorrectly modeled pixels" could cause the AI scan to miss a possible ailment, but the streamlined process "can quite literally save lives" by making scans more accessible and cutting costs. "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", Facebook wrote in the blog post. The project will use image data from 10,000 clinical cases with roughly 3 million MRIs of the knee, brain and liver. In April, CNBC reported that Facebook asked several major US hospitals to share anonymized data for a new research project. In disclosing the collaboration, Facebook stressed that all the images are de-identified and none of its data will be used in the project.

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Facebook started talking to NYU about the project a year ago because its AI team wanted to work on something with real-world benefits even as it performs basic research, said Larry Zitnick of the company's Artificial Intelligence Research group.

The catch is that neural networks have to bridge gaps without hurting accuracy.

As the project progresses, researchers say Facebook will share the AI models, baselines and evaluation metrics with the broader research community, while the NYU School of Medicine will open-source the image dataset. NYU Langone Health, which counts the NYU School of Medicine as a department, has been working on imaging and AI.

Additionally, there are MRI shortages in many rural areas and in other countries with limited access, resulting in long scheduling backlogs. NYU is also an IBM partner.

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