Illustrative White Matter Fiber Bundles

Illustrative White Matter Fiber Bundles

Diffusion Tensor Imaging (DTI) has made feasible the visualization of the fibrous structure of the brain white matter. In the last decades, several fiber-tracking methods have been developed to reconstruct the fiber tracts from DTI data. Usually these fiber tracts are shown individually based on some selection criteria like region of interest. However, if the white matter as a whole is being vi...

Registration, atlas estimation and variability analysis of white matter fiber bundles modeled as currents

This paper proposes a generic framework for the registration, the template estimation and the variability analysis of white matter fiber bundles extracted from diffusion images. This framework is based on the metric on currents for the comparison of fiber bundles. This metric measures anatomical differences between fiber bundles, seen as global homologous structures across subjects. It avoids t...

A Statistical Model of White Matter Fiber Bundles Based on Currents

The purpose of this paper is to measure the variability of a population of white matter fiber bundles without imposing unrealistic geometrical priors. In this respect, modeling fiber bundles as currents seems particularly relevant, as it gives a metric between bundles which relies neither on point nor on fiber correspondences and which is robust to fiber interruption. First, this metric is incl...

IMPROVED CHARACTERIZATION OF WHITE MATTER FIBER BUNDLES USING DIFFUSION MRI By

Characterization of white matter fiber bundles with T2* relaxometry and diffusion tensor imaging.

In this study, diffusion tensor imaging (DTI) and T(2)* multiechorelaxometry were combined in 30 healthy subjects at 3T, with the aim of characterizing the spatial distribution of relaxation rates in white matter (WM). Region of interest (ROI) analysis was performed in 23 different fiber tracts automatically defined in standard space. Spearman rank analysis was performed on regional values of T...