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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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 |
work_keys_str_mv |
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1725695983789015040 |