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Evaluation of Field Map and Nonlinear Registration Methods for Correction of Susceptibility Artifacts in Diffusion MRI

Correction of echo planar imaging (EPI)-induced distortions (called “unwarping”) improves anatomical fidelity for diffusion magnetic resonance imaging (MRI) and functional imaging investigations. Commonly used unwarping methods require the acquisition of supplementary images during the scanning sess...

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Autores principales: Wang, Sijia, Peterson, Daniel J., Gatenby, J. C., Li, Wenbin, Grabowski, Thomas J., Madhyastha, Tara M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5318394/
https://www.ncbi.nlm.nih.gov/pubmed/28270762
http://dx.doi.org/10.3389/fninf.2017.00017
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author Wang, Sijia
Peterson, Daniel J.
Gatenby, J. C.
Li, Wenbin
Grabowski, Thomas J.
Madhyastha, Tara M.
author_facet Wang, Sijia
Peterson, Daniel J.
Gatenby, J. C.
Li, Wenbin
Grabowski, Thomas J.
Madhyastha, Tara M.
author_sort Wang, Sijia
collection PubMed
description Correction of echo planar imaging (EPI)-induced distortions (called “unwarping”) improves anatomical fidelity for diffusion magnetic resonance imaging (MRI) and functional imaging investigations. Commonly used unwarping methods require the acquisition of supplementary images during the scanning session. Alternatively, distortions can be corrected by nonlinear registration to a non-EPI acquired structural image. In this study, we compared reliability using two methods of unwarping: (1) nonlinear registration to a structural image using symmetric normalization (SyN) implemented in Advanced Normalization Tools (ANTs); and (2) unwarping using an acquired field map. We performed this comparison in two different test-retest data sets acquired at differing sites (N = 39 and N = 32). In both data sets, nonlinear registration provided higher test-retest reliability of the output fractional anisotropy (FA) maps than field map-based unwarping, even when accounting for the effect of interpolation on the smoothness of the images. In general, field map-based unwarping was preferable if and only if the field maps were acquired optimally.
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spelling pubmed-53183942017-03-07 Evaluation of Field Map and Nonlinear Registration Methods for Correction of Susceptibility Artifacts in Diffusion MRI Wang, Sijia Peterson, Daniel J. Gatenby, J. C. Li, Wenbin Grabowski, Thomas J. Madhyastha, Tara M. Front Neuroinform Neuroscience Correction of echo planar imaging (EPI)-induced distortions (called “unwarping”) improves anatomical fidelity for diffusion magnetic resonance imaging (MRI) and functional imaging investigations. Commonly used unwarping methods require the acquisition of supplementary images during the scanning session. Alternatively, distortions can be corrected by nonlinear registration to a non-EPI acquired structural image. In this study, we compared reliability using two methods of unwarping: (1) nonlinear registration to a structural image using symmetric normalization (SyN) implemented in Advanced Normalization Tools (ANTs); and (2) unwarping using an acquired field map. We performed this comparison in two different test-retest data sets acquired at differing sites (N = 39 and N = 32). In both data sets, nonlinear registration provided higher test-retest reliability of the output fractional anisotropy (FA) maps than field map-based unwarping, even when accounting for the effect of interpolation on the smoothness of the images. In general, field map-based unwarping was preferable if and only if the field maps were acquired optimally. Frontiers Media S.A. 2017-02-21 /pmc/articles/PMC5318394/ /pubmed/28270762 http://dx.doi.org/10.3389/fninf.2017.00017 Text en Copyright © 2017 Wang, Peterson, Gatenby, Li, Grabowski and Madhyastha. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution and reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Wang, Sijia
Peterson, Daniel J.
Gatenby, J. C.
Li, Wenbin
Grabowski, Thomas J.
Madhyastha, Tara M.
Evaluation of Field Map and Nonlinear Registration Methods for Correction of Susceptibility Artifacts in Diffusion MRI
title Evaluation of Field Map and Nonlinear Registration Methods for Correction of Susceptibility Artifacts in Diffusion MRI
title_full Evaluation of Field Map and Nonlinear Registration Methods for Correction of Susceptibility Artifacts in Diffusion MRI
title_fullStr Evaluation of Field Map and Nonlinear Registration Methods for Correction of Susceptibility Artifacts in Diffusion MRI
title_full_unstemmed Evaluation of Field Map and Nonlinear Registration Methods for Correction of Susceptibility Artifacts in Diffusion MRI
title_short Evaluation of Field Map and Nonlinear Registration Methods for Correction of Susceptibility Artifacts in Diffusion MRI
title_sort evaluation of field map and nonlinear registration methods for correction of susceptibility artifacts in diffusion mri
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5318394/
https://www.ncbi.nlm.nih.gov/pubmed/28270762
http://dx.doi.org/10.3389/fninf.2017.00017
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