Sparsity-based superresolution MR imaging using dual dictionaries
Jean-Christophe Brisset 1 , Riccardo Otazo 1 , and Yulin Ge 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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