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Facebook, NYU Collaborate to make MRI 10-times faster with AI

Facebook and NYU School of Medicine’s Department of Radiology today announced a new collaborative research project that will investigate the use of artificial intelligence (AI) to make magnetic resonance imaging (MRI) scans up to 10 times faster. Facebook said that if this effort is successful, it will make MRI technology available to more people, expanding access to this key diagnostic tool.

This project will initially focus on changing how MRI machines operate. Currently, scanners work by gathering raw numerical data in a series of sequential views and turning the data into cross-sectional images of internal body structures that doctors then use to evaluate a patient’s health. The larger the data set to be gathered, the longer the scan will take.

Facebook said that it may be possible to capture less data and therefore scan faster, while preserving or even enhancing the rich information content of magnetic resonance images, using AI. 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. This approach is similar to how humans process sensory information. When we experience the world, our brains often receive an incomplete picture — as in the case of obscured or dimly lit objects — that we need to turn into actionable information. Early work performed at NYU School of Medicine shows that artificial neural networks can accomplish a similar task, generating high-quality images from far less data than was previously thought to be necessary.

“We believe the fastMRI project will demonstrate how domain-specific experts from different fields and industries can work together to produce the kind of open research that will make a far-reaching and lasting positive impact in the world,” Facebook said.

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