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.