Journal article
P. S. Özbay, A. Deistung, Xiang Feng, D. Nanz, J. Reichenbach, F. Schweser
NMR in biomedicine, 2017
NMR in biomedicine, 2017
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APA
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Özbay, P. S., Deistung, A., Feng, X., Nanz, D., Reichenbach, J., & Schweser, F. (2017). A comprehensive numerical analysis of background phase correction with V‐SHARP. NMR in Biomedicine.
Chicago/Turabian
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Özbay, P. S., A. Deistung, Xiang Feng, D. Nanz, J. Reichenbach, and F. Schweser. “A Comprehensive Numerical Analysis of Background Phase Correction with V‐SHARP.” NMR in biomedicine (2017).
MLA
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Özbay, P. S., et al. “A Comprehensive Numerical Analysis of Background Phase Correction with V‐SHARP.” NMR in Biomedicine, 2017.
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@article{p2017a,
title = {A comprehensive numerical analysis of background phase correction with V‐SHARP},
year = {2017},
journal = {NMR in biomedicine},
author = {Özbay, P. S. and Deistung, A. and Feng, Xiang and Nanz, D. and Reichenbach, J. and Schweser, F.}
}
Abstract
Sophisticated harmonic artifact reduction for phase data (SHARP) is a method to remove background field contributions in MRI phase images, which is an essential processing step for quantitative susceptibility mapping (QSM). To perform SHARP, a spherical kernel radius and a regularization parameter need to be defined. In this study, we carried out an extensive analysis of the effect of these two parameters on the corrected phase images and on the reconstructed susceptibility maps. As a result of the dependence of the parameters on acquisition and processing characteristics, we propose a new SHARP scheme with generalized parameters. The new SHARP scheme uses a high‐pass filtering approach to define the regularization parameter. We employed the variable‐kernel SHARP (V‐SHARP) approach, using different maximum radii (Rm) between 1 and 15 mm and varying regularization parameters (f) in a numerical brain model. The local root‐mean‐square error (RMSE) between the ground‐truth, background‐corrected field map and the results from SHARP decreased towards the center of the brain. RMSE of susceptibility maps calculated with a spatial domain algorithm was smallest for Rm between 6 and 10 mm and f between 0 and 0.01 mm−1, and for maps calculated with a Fourier domain algorithm for Rm between 10 and 15 mm and f between 0 and 0.0091 mm−1. We demonstrated and confirmed the new parameter scheme in vivo. The novel regularization scheme allows the use of the same regularization parameter irrespective of other imaging parameters, such as image resolution. Copyright © 2016 John Wiley & Sons, Ltd.
