This looks interesting:
An AI system can produce magnetic resonance imaging (MRI) scans with only a quarter of the data normally required, which could speed up the scanning process.
MRIs are created by placing a person inside a machine that scans the body and are often used to image brain development or muscle and tissue injuries. The speedy AI-based system, called FastMRI, was developed by researchers at Facebook AI and NYU Langone. It was trained on thousands of images gathered from 242 people.
The team then used the new system to create MRI scans of 108 people’s knees using 75 per cent less data taken during the scan to generate the finished image. The AI reconstruction uses less actual data, resulting in less time in an MRI machine. It manages this by filling in the “gaps” based on the images it was trained on.
The team then gave the 108 FastMRI scans to six radiologists, five of whom couldn’t distinguish them from MRI scans obtained using the traditional method. [NewScientist, paywall]
I get to spend another 45 minutes in an MRI machine in order to check how a cyst on my pituitary gland is changing, if at all, after pandemic vaccines are developed and approved, so something like this is interesting, if too late to reduce in my particular case.
But I do worry that the data of interest will reside in the gaps filled in by the machine learning algorithm. They don’t really address that possibility in this relatively short article.
