Meeting Banner
Abstract #3352

A Quantitative Study of Sodicksons Paradox

Yu Ding1, Hui Xue2, Ti-chiun Chang3, Christoph Guetter3, Orlando Simonetti1

1Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University, Columbus, OH, United States; 2siemens corporate research; 3Siemens Corporate Research

GRAPPA reconstructs the missing k-space by applying a convolution kernel which is estimated from ACS lines using linear regression. Intuitively, ACS lines with higher SNR should boost the accuracy of the kernel estimation, and increase the SNR of GRAPPA reconstruction. Paradoxically, Sodickson and his colleagues pointed out that the higher SNR in ACS lines may lead to lower SNR in GRAPPA reconstruction. We study quantitative about how the noise in the ACS lines affects the SNR of the GRAPPA reconstruction, and proposes a simple solution to improve the SNR of TGRAPPA.