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 [1], 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 [2] 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.