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Abstract #0732

Spatiotemporal encoding for DWI of brain and prostate using subspace-constrained sampling and locally-low-rank regularized reconstruction

Martins Otikovs1, Ankit Basak1, and Lucio Frydman1
1Weizmann Institute of Science, Rehovot, Israel

The benefits of performing locally low-rank (LLR) reconstruction on subsampled diffusion weighted (DW) data employing spatiotemporal encoding (SPEN) methods, is investigated. SPEN allows for self-referenced correction of motion-induced phase errors in case of interleaved DW acquisitions, and allows to overcome distortions otherwise observed along EPI’s phase-encoded dimension. In combination with LLR regularization and with joint subsampling of b-weighted and interleaved images, additional improvements are demonstrated. The method is tested on phantoms, and improvements in in-vivo brain and prostate scans on volunteers are demonstrated.

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