Limits...
Accurate anisotropic fast marching for diffusion-based geodesic tractography.

Jbabdi S, Bellec P, Toro R, Daunizeau J, Pélégrini-Issac M, Benali H - Int J Biomed Imaging (2008)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Laboratoire d'Imagerie Fonctionnelle, INSERM, U678, 75013 Paris, France. saad@fmrib.ox.ac.uk

ABSTRACT
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.

No MeSH data available.


Localisation of the regions ofinterest on the cortex. 3D fronto-sagittal view.
© Copyright Policy - open-access
Related In: Results  -  Collection


getmorefigures.php?uid=PMC2235929&req=5

fig7: Localisation of the regions ofinterest on the cortex. 3D fronto-sagittal view.

Mentions: Five hundred and sixty-seven () regionscovering the whole cortex were manually selected in the DTI space. Each regionwas represented by a single voxel. The anatomical localization of these regionsis shown in Figure 7. We performed a front propagation from each region,which provided the distance functions . Then back propagation allowed us to construct the geodesicsconnecting the whole set of voxel pairs. We computed a heuristic connectivityindex consisting of the mean diffusivity along each geodesic, multiplied by themean FA along the pathways.


Accurate anisotropic fast marching for diffusion-based geodesic tractography.

Jbabdi S, Bellec P, Toro R, Daunizeau J, Pélégrini-Issac M, Benali H - Int J Biomed Imaging (2008)

Localisation of the regions ofinterest on the cortex. 3D fronto-sagittal view.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2235929&req=5

fig7: Localisation of the regions ofinterest on the cortex. 3D fronto-sagittal view.
Mentions: Five hundred and sixty-seven () regionscovering the whole cortex were manually selected in the DTI space. Each regionwas represented by a single voxel. The anatomical localization of these regionsis shown in Figure 7. We performed a front propagation from each region,which provided the distance functions . Then back propagation allowed us to construct the geodesicsconnecting the whole set of voxel pairs. We computed a heuristic connectivityindex consisting of the mean diffusivity along each geodesic, multiplied by themean FA along the pathways.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Laboratoire d'Imagerie Fonctionnelle, INSERM, U678, 75013 Paris, France. saad@fmrib.ox.ac.uk

ABSTRACT
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.

No MeSH data available.