A nonlinear regularization strategy for GRAPPA calibration.
A regularization strategy is described for generalized autocalibrating partially parallel acquisition (GRAPPA) that allows successful calibration using a small number of autocalibration signals (ACS). The approach requires certain nonlinear relationships between the GRAPPA coefficients to be satisfied, which increases the redundancy so that fewer ACS need to be acquired.
Bydder
Mark
M
Department of Radiology, University of California San Diego, San Diego, CA 92103-8226, USA. mbydder@ucsd.edu
Jung
Youngkyoo
Y
D001931:Brain Mapping / Q000379:methods*; D002138:Calibration; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*