How New Machine Learning Techniques Could Improve MRI Scans
WNCG professor Jon Tamir aims to leverage machine learning techniques to make brain scans faster and more informative. He received an Amazon Machine Learning Research Award in 2020 from Amazon Web Services (AWS) to support the work.
A recent article on Amazon Science explored the details of Prof. Tamir's research on MRI scans.
Tamir and colleagues are working on machine learning algorithms that can learn from limited data to fill in the blanks, so to speak, on images. One tactic being explored by Tamir and others is to randomly collect about 25% of the possible data from a scan and train a neural network to reconstruct an entire image based on that under-sampled data. Another strategy is to use machine learning to optimize the sampling trajectory in the first place.
"Random sampling is a very convenient approach, but we could use machine learning to decide the best sampling trajectory and figure out which points are most important," he said.
Read the full article via Amazon Science.