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Abstract #0655

Accelerated high b-value diffusion-weighted MRI for higher-order diffusion analysis using a phase-constrained low-rank tensor model

Lianli Liu1, Adam Johansson2, James M. Balter2, Jeffrey A. Fessler1, and Yue Cao2

1Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, United States, 2Radiation Oncology, University of Michigan, Ann Arbor, MI, United States

DWI acquired with b-values greater than 1000 s/mm2 and higher-order diffusion analyses based on such DWI series have the potential to improve tumor differentiation, while the extended sampling of b-values makes the acquisition time inconveniently long. We propose an acceleration scheme that sparsely samples k-space and reconstructs images using a new low-rank tensor model which exploits both global and local low-rank structure. Under an acceleration factor of 8, parameter mapping results on one simulated and 7 patient datasets show improved accuracy over another low-rank tensor model that exploits global correlation only, and comparable accuracy to clinically used four-fold GRAPPA reconstruction.

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