UT Austin Researchers Demonstrate a Deep Learning Technique That Achieves High-Quality Image Reconstructions Based on MRI Datasets

During a magnetic resonance imaging (MRI) scan, time seems to stand still for many individuals. Those who have experienced one understand the difficulty of remaining immovably still inside a buzzing, banging scanner for periods ranging from a few minutes to more than an hour. IFML Senior Personnel Jon Tamir is working on ways to use machine learning to reduce exam duration times and extract more information from this necessary—but frequently unpleasant—imaging procedure. Read the full story on MarkTechPost