Abstract #0744
MRI Reconstruction by Learning the Dictionary of Spatialfrequency-Bands Correlation: A novel algorithm integratable with PI and CS to further push acceleration
Enhao Gong 1 and John M Pauly 1
1
Electrical Engineering, Stanford University,
Stanford, CA, United States
Parallel Imaging (PI) and Compressed Sensing (CS) enable
MR acceleration by exploiting channel-correlation and
sparsity. However, the acceleration capability is
limited by channel-encoding, increased noise and blurred
details. In this work, a novel algorithm is proposed to
further improve the undersampled MRI reconstruction by
exploiting the correlation between image details in
different bands of spatial-frequencies. Dictionaries of
image patches in different spatial-frequency bands were
learned from database and undersampled MR images were
reconstructed by solving as a sparse representation of
the dictionary. The proposed algorithm demonstrated
great advantages and were integrated with PI-CS to
further push acceleration.
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