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Abstract #0076

Dynamic Imaging Using Sparse Sampling with Rank & Group Sparsity Constraints

Anthony G. Christodoulou1, 2, S. Derin Babacan2, Zhi-Pei Liang1, 2

1Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, Urbana, IL, United States; 2Beckman Institute of Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, United States

This work highlights a novel dynamic imaging method which jointly uses partial separability (PS), sparsity, and group sparsity constraints to enable sparse sampling in (k,t)-space. The specific formulation of the group sparsity spatially varies the effective model order of the PS constraint as a form of controlling the balance between the PS and sparsity constraints.

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Keywords

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