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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

CITP Seminar: Building Language Technologies for Analyzing Online Activism

While recent advances in natural language processing (NLP) have greatly enhanced our ability to analyze online text, distilling broad social-oriented research questions into tasks concrete enough for NLP models remains challenging. In this work, we develop state-of-the-art NLP models grounded in frameworks from social theory in order to analyze two social media movements: online media coverage of the #MeToo movement in 2017-2018 and tweets about #BlackLivesMatter protests in 2020. In the first p...
Yulia Tsvtekov University Of Washington Princeton University Language Technologies Institute At Carnegie Mellon University Language Technologies Institute Carnegie Mellon University

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