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Erschienen in: International Journal of Computer Assisted Radiology and Surgery 10/2015

01.10.2015 | Original Article

Improving GRAPPA reconstruction by frequency discrimination in the ACS lines

verfasst von: Santiago Aja-Fernández, Daniel García Martín, Antonio Tristán-Vega, Gonzalo Vegas-Sánchez-Ferrero

Erschienen in: International Journal of Computer Assisted Radiology and Surgery | Ausgabe 10/2015

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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.

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Metadaten
Titel
Improving GRAPPA reconstruction by frequency discrimination in the ACS lines
verfasst von
Santiago Aja-Fernández
Daniel García Martín
Antonio Tristán-Vega
Gonzalo Vegas-Sánchez-Ferrero
Publikationsdatum
01.10.2015
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Computer Assisted Radiology and Surgery / Ausgabe 10/2015
Print ISSN: 1861-6410
Elektronische ISSN: 1861-6429
DOI
https://doi.org/10.1007/s11548-015-1172-7

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