Accurate Anisotropic Fast Marching for Diffusion-Based Geodesic Tractography

Using geodesics for inferring white matter fibre tracts from diffusion-weighted MR data is an attractive method for at least two reasons: (i) the method optimises a global criterion, and hence is less sensitive to local perturbations such as noise or partial volume effects, and (ii) the method is fa...

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Main Authors: S. Jbabdi, P. Bellec, R. Toro, J. Daunizeau, M. Pélégrini-Issac, H. Benali
Format: Article
Language:English
Published: Hindawi Limited 2008-01-01
Series:International Journal of Biomedical Imaging
Online Access:http://dx.doi.org/10.1155/2008/320195
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spelling doaj-a85e432adfbf47cea7c9f5122eb27add2020-11-24T22:43:26ZengHindawi LimitedInternational Journal of Biomedical Imaging1687-41881687-41962008-01-01200810.1155/2008/320195320195Accurate Anisotropic Fast Marching for Diffusion-Based Geodesic TractographyS. Jbabdi0P. Bellec1R. Toro2J. Daunizeau3M. Pélégrini-Issac4H. Benali5Laboratoire d'Imagerie Fonctionnelle, INSERM, U678, Paris 75013, FranceLaboratoire d'Imagerie Fonctionnelle, INSERM, U678, Paris 75013, FranceBrain & Body Centre, The University of Nottingham, Nottingham NG7 2RD, UKLaboratoire d'Imagerie Fonctionnelle, INSERM, U678, Paris 75013, FranceLaboratoire d'Imagerie Fonctionnelle, INSERM, U678, Paris 75013, FranceLaboratoire d'Imagerie Fonctionnelle, INSERM, U678, Paris 75013, FranceUsing geodesics for inferring white matter fibre tracts from diffusion-weighted MR data is an attractive method for at least two reasons: (i) the method optimises a global criterion, and hence is less sensitive to local perturbations such as noise or partial volume effects, and (ii) the method is fast, allowing to infer on a large number of connexions in a reasonable computational time. Here, we propose an improved fast marching algorithm to infer on geodesic paths. Specifically, this procedure is designed to achieve accurate front propagation in an anisotropic elliptic medium, such as DTI data. We evaluate the numerical performance of this approach on simulated datasets, as well as its robustness to local perturbation induced by fiber crossing. On real data, we demonstrate the feasibility of extracting geodesics to connect an extended set of brain regions.http://dx.doi.org/10.1155/2008/320195
collection DOAJ
language English
format Article
sources DOAJ
author S. Jbabdi
P. Bellec
R. Toro
J. Daunizeau
M. Pélégrini-Issac
H. Benali
spellingShingle S. Jbabdi
P. Bellec
R. Toro
J. Daunizeau
M. Pélégrini-Issac
H. Benali
Accurate Anisotropic Fast Marching for Diffusion-Based Geodesic Tractography
International Journal of Biomedical Imaging
author_facet S. Jbabdi
P. Bellec
R. Toro
J. Daunizeau
M. Pélégrini-Issac
H. Benali
author_sort S. Jbabdi
title Accurate Anisotropic Fast Marching for Diffusion-Based Geodesic Tractography
title_short Accurate Anisotropic Fast Marching for Diffusion-Based Geodesic Tractography
title_full Accurate Anisotropic Fast Marching for Diffusion-Based Geodesic Tractography
title_fullStr Accurate Anisotropic Fast Marching for Diffusion-Based Geodesic Tractography
title_full_unstemmed Accurate Anisotropic Fast Marching for Diffusion-Based Geodesic Tractography
title_sort accurate anisotropic fast marching for diffusion-based geodesic tractography
publisher Hindawi Limited
series International Journal of Biomedical Imaging
issn 1687-4188
1687-4196
publishDate 2008-01-01
description Using geodesics for inferring white matter fibre tracts from diffusion-weighted MR data is an attractive method for at least two reasons: (i) the method optimises a global criterion, and hence is less sensitive to local perturbations such as noise or partial volume effects, and (ii) the method is fast, allowing to infer on a large number of connexions in a reasonable computational time. Here, we propose an improved fast marching algorithm to infer on geodesic paths. Specifically, this procedure is designed to achieve accurate front propagation in an anisotropic elliptic medium, such as DTI data. We evaluate the numerical performance of this approach on simulated datasets, as well as its robustness to local perturbation induced by fiber crossing. On real data, we demonstrate the feasibility of extracting geodesics to connect an extended set of brain regions.
url http://dx.doi.org/10.1155/2008/320195
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