Abstract #0104

Accelerated Multiparameter Mapping Using Low-Rank Tensors

Anthony G. Christodoulou ¹ and Zhi-Pei Liang ¹

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 lower case Greek rho

, T ₁ , and T ₂ ^* mapping of an ex vivo rat heart infiltrated by superparamagnetic iron oxide (SPIO)-labeled macrophages, which produced excellent reconstruction results from very sparsely sampled data.

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