Reducing Phase Encoding Steps in Undersampled MRI k-Space using Novel Deep Learning Algorithms
By Sauman Das
Acquiring MRI scans is a time-taking and uncomfortable process. Any patient movement during the acquisition time can result in low quality scans which cause inaccurate diagnoses and problems during surgical treatment. In this study, I plan to study different signal undersampling procedures for k-space acquisition and develop a generative deep learning model to interpolate missing details. If this algorithm works successfully, the MRI acquisition process can be made more efficient and help millions of patients across the world.
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