Accelerated Multiparameter Mapping Using Low-Rank Tensors
Anthony G. Christodoulou 1 and Zhi-Pei Liang 1
Beckman Institute and Department of
Electrical and Computer Engineering, University of
Illinois at Urbana-Champaign, Urbana, IL, United States
This work describes a novel method for highly
accelerated multiparameter mapping exploiting the
low-rank tensor structure induced by partial
separability of the desired multivariate image function.
We demonstrate the proposed tensor-based data
acquisition and reconstruction method for highly
accelerated multiparameter mapping and demonstrate this
method for accelerated FLASH-based
, and T
heart infiltrated by superparamagnetic iron oxide
(SPIO)-labeled macrophages, which produced excellent
reconstruction results from very sparsely sampled data.
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