Abstract #3649

Wang J, Zhuo Y, Luo J, Zhang B

GRAPPA is known as its high robustness and low residual artifact, but the fitting process may introduce additional uncertainty to the weighting coefficients. We present here a general method to calculate SNR degradation due to non-ideal weighting coefficients and use equivalent weighting coefficients for GRAPPA to analyze its noise behavior. The result shows that although the SNR degradation for GRAPPA is mathematically the reciprocal value of SENSE g-factor, it depends not only on the coil geometry but also on the image contrast. It is also observed that the GRAPPA algorithm has the ability to sacrifice SNR to achieve lowest artifact power and to optimize SNR when artifact power is low.