Abstract #2890
Undersampled simultaneous multi-slice readout-segmented EPI diffusion acquisition with a patch-based low rank constraint
Ganesh Adluru 1 , Bradley D. Bolster Jr 2 , Robert Frost 3 , Lorie Richards 4 , and Edward V.R. DiBella 1
1
Radiology, University of Utah, Salt Lake
City, Utah, United States,
2
Siemens
Healthcare, Salt Lake City, Utah, United States,
3
FMRIB
Centre, Nuffield Department of Clinical Neurosciences,
University of Oxford, Oxford, United Kingdom,
4
Occupational
Therapy, University of Utah, Salt Lake City, Utah,
United States
Readout-Segmented EPI (RS-EPI) acquisition is a
promising approach for high quality diffusion imaging.
With its short echo spacing times compared to the
standard single shot EPI sequence, RS-EPI has less
blurring and distortions and allows high spatial
resolution acquisitions. However with long diffusion
preparation time for each segment, scan time increase is
almost proportional to the number of segments making the
RS-EPI technique less practical especially for diffusion
acquisitions with a large number of diffusion
directions. Here we present a framework to speed up
RS-EPI by combining simultaneous multi-slice
acquisitions with constrained reconstructions for
k-space undersampling. We use a patch-based low rank
reconstruction to remove undersampling artifacts.
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