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Massachusetts Institute of Technology experts combine deep learning and physics to fix motion-corrupted MRI scans

Compared to other imaging modalities like X-rays or CT scans, MRI scans provide high-quality soft tissue contrast. Unfortunately, MRI is highly sensitive to motion, with even the smallest of movements resulting in image artifacts. These artifacts put
United States Vanderbilt University Robert Frost Bruce Fischl Elfar Adalsteinsson Daniel Moyer

MIT researchers combine deep learning and physics to fix motion-corrupted MRI scans

MIT researchers develop an algorithm combining deep learning and physics for motion correction in MRI scans of the brain. Experts say this could help children, elderly, and people with psychiatric or neurological disorders who may have difficulty staying still during an MRI scanning session.
Vanderbilt University United States Polina Golland Daniel Moyer Adrian Dalca Steve Cauley
Source: mit.edu

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