Wei Lin1,
Feng Huang1, Hu Cheng2, Yu Li1, Arne Reykowski1
1Advanced Concepts Development, Invivo
Corporation, Philips Healthcare, Gainesville, FL, United States; 2Indiana
University, Bloomington, IN, United States
The
performance of GRAPPA-based parallel imaging methods can suffer when the size
of the auto-calibration signal (ACS) region becomes small. Based on an
analysis of condition number for GRAPPA calibration equation, an optimal
Tikhonov regularization factor is proposed to improve the quality of image
reconstruction. Alternatively, an optimal amount of noise can be added to the
ACS data to stabilize the system. The technique was applied to both GRAPPA
and GRAPPA operator for wider radial bands (GROWL), a self-calibrated radial
parallel imaging methods. Results show that minimal reconstruction errors are
always obtained with the proposed automatic regularization scheme.
Keywords