Sumati Krishnan1, David Moratal2, Lei-Hou Hamilton3, Senthil Ramamurthy4, Marijn Eduard Brummer4
1Emory University, Atlanta, GA, United States; 22Universitat Politcnica de Valncia, Valencia, Spain; 3Georgia Institute of Technology, Atlanta, GA, United States; 4Emory University, Atlanta, GA, United States
A well-known reconstruction method, based on error energy reduction , is adapted to sparsely sampled dynamic cardiac MRI. Inherent temporally band-limited properties of known static regions in the FOV, are used to recover additional resolution from information embedded in the acquired k-t samples. The algorithm converges as the error due to residual dynamic content in the static region is minimized. Reconstructions equivalent to direct matrix-inversion  are achieved with significantly reduced computational costs, while convergence properties are related to the sampling patterns. The proposed iterative method has potential applications for a variety of non-Cartesian grids as well as sparse-sampling patterns.