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Microstructure Imaging of Crossing (MIX) White Matter Fibers from diffusion MRI
Diffusion MRI (dMRI) reveals microstructural features of the brain white matter by quantifying the anisotropic diffusion of water molecules within axonal bundles. Yet, identifying features such as axonal orientation dispersion, density, diameter, etc., in complex white matter fiber configurations (e...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5159854/ https://www.ncbi.nlm.nih.gov/pubmed/27982056 http://dx.doi.org/10.1038/srep38927 |
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author | Farooq, Hamza Xu, Junqian Nam, Jung Who Keefe, Daniel F. Yacoub, Essa Georgiou, Tryphon Lenglet, Christophe |
author_facet | Farooq, Hamza Xu, Junqian Nam, Jung Who Keefe, Daniel F. Yacoub, Essa Georgiou, Tryphon Lenglet, Christophe |
author_sort | Farooq, Hamza |
collection | PubMed |
description | Diffusion MRI (dMRI) reveals microstructural features of the brain white matter by quantifying the anisotropic diffusion of water molecules within axonal bundles. Yet, identifying features such as axonal orientation dispersion, density, diameter, etc., in complex white matter fiber configurations (e.g. crossings) has proved challenging. Besides optimized data acquisition and advanced biophysical models, computational procedures to fit such models to the data are critical. However, these procedures have been largely overlooked by the dMRI microstructure community and new, more versatile, approaches are needed to solve complex biophysical model fitting problems. Existing methods are limited to models assuming single fiber orientation, relevant to limited brain areas like the corpus callosum, or multiple orientations but without the ability to extract detailed microstructural features. Here, we introduce a new and versatile optimization technique (MIX), which enables microstructure imaging of crossing white matter fibers. We provide a MATLAB implementation of MIX, and demonstrate its applicability to general microstructure models in fiber crossings using synthetic as well as ex-vivo and in-vivo brain data. |
format | Online Article Text |
id | pubmed-5159854 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-51598542016-12-21 Microstructure Imaging of Crossing (MIX) White Matter Fibers from diffusion MRI Farooq, Hamza Xu, Junqian Nam, Jung Who Keefe, Daniel F. Yacoub, Essa Georgiou, Tryphon Lenglet, Christophe Sci Rep Article Diffusion MRI (dMRI) reveals microstructural features of the brain white matter by quantifying the anisotropic diffusion of water molecules within axonal bundles. Yet, identifying features such as axonal orientation dispersion, density, diameter, etc., in complex white matter fiber configurations (e.g. crossings) has proved challenging. Besides optimized data acquisition and advanced biophysical models, computational procedures to fit such models to the data are critical. However, these procedures have been largely overlooked by the dMRI microstructure community and new, more versatile, approaches are needed to solve complex biophysical model fitting problems. Existing methods are limited to models assuming single fiber orientation, relevant to limited brain areas like the corpus callosum, or multiple orientations but without the ability to extract detailed microstructural features. Here, we introduce a new and versatile optimization technique (MIX), which enables microstructure imaging of crossing white matter fibers. We provide a MATLAB implementation of MIX, and demonstrate its applicability to general microstructure models in fiber crossings using synthetic as well as ex-vivo and in-vivo brain data. Nature Publishing Group 2016-12-16 /pmc/articles/PMC5159854/ /pubmed/27982056 http://dx.doi.org/10.1038/srep38927 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Farooq, Hamza Xu, Junqian Nam, Jung Who Keefe, Daniel F. Yacoub, Essa Georgiou, Tryphon Lenglet, Christophe Microstructure Imaging of Crossing (MIX) White Matter Fibers from diffusion MRI |
title | Microstructure Imaging of Crossing (MIX) White Matter Fibers from diffusion MRI |
title_full | Microstructure Imaging of Crossing (MIX) White Matter Fibers from diffusion MRI |
title_fullStr | Microstructure Imaging of Crossing (MIX) White Matter Fibers from diffusion MRI |
title_full_unstemmed | Microstructure Imaging of Crossing (MIX) White Matter Fibers from diffusion MRI |
title_short | Microstructure Imaging of Crossing (MIX) White Matter Fibers from diffusion MRI |
title_sort | microstructure imaging of crossing (mix) white matter fibers from diffusion mri |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5159854/ https://www.ncbi.nlm.nih.gov/pubmed/27982056 http://dx.doi.org/10.1038/srep38927 |
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