data.bvec


3D grid file containing the sampling points used in diffusion data acquisition for file &#145;<span class="file">data.nii.gz</span>&#146;.


 data

Diffusion anisotropy has been used to characterize
white matter neuronal pathways in the human brain, and infer global
connectivity in the central nervous system. The package implements
algorithms to estimate and visualize the orientation of neuronal
pathways in model-free methods (q-space imaging methods).
For estimating fibre orientations two methods have been
implemented.  One method implements fibre orientation detection
through local maxima extraction. A second more robust method
is based on directional statistical clustering of ODF voxel data.
Fibre orientations in multiple fibre voxels are estimated using
a mixture of von Mises-Fisher (vMF) distributions. This statistical
estimation procedure is used to resolve crossing fibre
configurations.
Reconstruction of orientation distribution function (ODF)
profiles may be performed using the standard generalized
q-sampling imaging (GQI) approach, Garyfallidis' GQI (GQI2)
approach, or Aganj's variant of the Q-ball imaging (CSA-QBI)
approach. Procedures for the visualization of RGB-maps,
line-maps and glyph-maps of real diffusion magnetic resonance
imaging (dMRI) data-sets are included in the package.

Adelino da Silva

gdimap

Generalized Diffusion Magnetic Resonance Imaging

data.bvec function

&#145;<span class="file">data.bvec</span>&#146; is in ASCII format, specified as a sequence of values,
  as produced by the 'dcm2nii' tool, and compatible with the formats used
  in the 'DSI_Studio' and 'Dipy' toolboxes.

data.bvec: 3D b-table Vectors for Data Acquisition

Description

Arguments

Format

Details

References