@article {567, title = {Impact of MR Acquisition Parameters on DTI Scalar Indexes: A Tractography Based Approach}, journal = {PLoS ONE}, volume = {10}, year = {2015}, pages = {e0137905}, doi = {10.1371/journal.pone.0137905}, url = {http://dx.doi.org/10.1371\%2Fjournal.pone.0137905}, author = {Gonzalo Barrio-Arranz and Rodrigo de Luis-Garc{\'\i}a and Antonio Trist{\'a}n-Vega and Marcos Mart{\'\i}n-Fern{\'a}ndez and Santiago Aja-Fern{\'a}ndez} } @article {532, title = {Improving GRAPPA reconstruction by frequency discrimination in the ACS lines}, journal = {International Journal of Computer Assisted Radiology and Surgery}, volume = {10}, year = {2015}, month = {2015}, pages = {1699-1710}, chapter = {1699}, abstract = {
Purpose
GRAPPA is a well-known parallel imaging method that recovers the MR magnitude image from aliasing by using a weighted interpolation of the data in k-space. To estimate the optimal reconstruction weights, GRAPPA uses a band along the center of the k-space where the signal is sampled at the Nyquist rate, the so-called autocalibrated (ACS) lines. However, while the subsampled lines usually belong to the medium- to high-frequency areas of the spectrum, the ACS lines include the low-frequency areas around the DC component. The use for estimation and reconstruction of areas of the k-space with very different features may negatively affect the final reconstruction quality. We propose a simple, yet powerful method to eliminate reconstruction artifacts, based on the discrimination of the low-frequency spectrum.
Methods
The proposal to improve the estimation of the weights lays on a proper selection of the coefficients within the ACS lines, which advises discarding those points around the DC component. A simple approach is the elimination of a square window in the center of the k-space, although more developed approaches can be used.
Results
The method is tested using real multiple-coil MRI acquisitions. We empirically show this approach achieves great enhancement rates, while keeping the same complexity of the original GRAPPA and reducing the g-factor. The reconstruction is even more accurate when combined with other reconstruction methods. Improvement rates of 35\ \% are achieved for 32 ACS and acceleration rate of 3.
Conclusions
The method proposed highly improves the accuracy of the GRAPPA coefficients and therefore the final image reconstruction. The method is fully compatible with the original GRAPPA formulation and with other optimization methods proposed in literature, and it can be easily implemented into the commercial scanning software.
}, doi = {10.1007/s11548-015-1172-7}, author = {Santiago Aja-Fern{\'a}ndez and Daniel Garc{\'\i}a-Mart{\'\i}n and Antonio Trist{\'a}n-Vega and Gonzalo Vegas-S{\'a}nchez-Ferrero} } @article {aja2012influence, title = {Influence of noise correlation in multiple-coil statistical models with sum of squares reconstruction}, journal = {Magnetic Resonance in Medicine}, volume = {67}, number = {2}, year = {2012}, pages = {580{\textendash}585}, publisher = {Wiley Subscription Services, Inc., A Wiley Company}, author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega} }