4.5 Article

Paradoxical effect of the signal-to-noise ratio of GRAPPA calibration lines: A quantitative study

Journal

MAGNETIC RESONANCE IN MEDICINE
Volume 74, Issue 1, Pages 231-239

Publisher

WILEY-BLACKWELL
DOI: 10.1002/mrm.25385

Keywords

GRAPPA; condition number; signal to noise ratio; real-time MRI

Funding

  1. National Heart, Lung, And Blood Institute [R01HL102450]
  2. Siemens Healthcare

Ask authors/readers for more resources

PurposeIntuitively, GRAPPA auto-calibration signal (ACS) lines with higher signal-to-noise ratio (SNR) may be expected to boost the accuracy of kernel estimation and increase the SNR of GRAPPA reconstructed images. Paradoxically, Sodickson and his colleagues pointed out that using ACS lines with high SNR may actually lead to lower SNR in the GRAPPA reconstructed images. A quantitative study of how the noise in the ACS lines affects the SNR of the GRAPPA reconstructed images is presented. MethodsIn a phantom, the singular values of the GRAPPA encoding matrix and the root-mean-square error of GRAPPA reconstruction were evaluated using multiple sets of ACS lines with variant SNR. In volunteers, ACS lines with high and low SNR were estimated, and the SNR of corresponding TGRAPPA reconstructed images was evaluated. ResultsWe show that the condition number of the GRAPPA kernel estimation equations is proportional to the SNR of the ACS lines. In dynamic image series reconstructed with TGRAPPA, high SNR ACS lines result in reduced SNR if appropriate regularization is not applied. ConclusionNoise has a similar effect to Tikhonov regularization. Without appropriate regularization, a GRAPPA kernel estimated from ACS lines with higher SNR amplifies random noise in the GRAPPA reconstruction. Magn Reson Med 74:231-239, 2015. (c) 2014 Wiley Periodicals, Inc.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available