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Abstract #1262

Sparsity-based superresolution MR imaging using dual dictionaries

Jean-Christophe Brisset 1 , Riccardo Otazo 1 , and Yulin Ge 1

1 Department of Radiology, New York University School of Medicine, New York, NY, United States

Clinical imaging is always longing for increased image resolution to obtain superior details of biological structural changes at micro levels. SuperResolution is the process of reconstructing a High Resolution image from a Low Resolution image and has been predominantly used in digital photography and picture enhancement. Superresolution techniques have been proposed previously for MRI but with limited success due to scan time and SNR challenges. In this study, we propose to bring this idea to brain MRI for supersolved subvoxel microstructural diffraction. Coupled-sparsity superresolution may be very useful for identifying microstructures that are not well visualized with current MRI techniques.

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