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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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