Keywords: Motion Correction, Image ReconstructionCompressed sensing-based motion state-resolved image reconstruction (such as XD-GRASP) is computationally demanding, requiring iterative NUFFT operations. In addition, each individual echo is independently treated/reconstructed so that R2* relaxation rate with clinically significant information about tissue iron concentration may not be considered properly, causing unreliable R2* measurement. We propose a low-rank tensor-based 5D (3D space + 1D motion state + 1D echo) image reconstruction method that resolves motion states, accounts for consistency in echo evolution, and does not require iterative NUFFT operations. For in vivo human liver imaging, the proposed method showed superior image quality and R2* accuracy over existing methods.
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