Keywords: Sparse & Low-Rank Models, Sparse & Low-Rank ModelsLow-rank tensor modelling is promising for multi-dimensional MR imaging. In this work, we developed a new low-rank tensor reconstruction approach using alternating minimization of spatial and temporal bases from the whole k-t space data instead of from split subsets of data. The approach was evaluated for 2D motion-resolved myocardial T1/T2/T2*/fat-fraction mapping and could potentially be used for imporving reconstruction quality and/or further reducing scan time.
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