gdimap-package

The package implements algorithms to estimate and visualize the orientation of neuronal pathways in model-free methods (q-space imaging methods).
For fibre orientation estimation based on mixtures of von Mises-Fischer (vMF) distributions see <code><a href="/link/gqi.odfvmflines?package=gdimap&version=0.0-3" rd-options="" data-mini-rdoc="gdimap::gqi.odfvmflines">gqi.odfvmflines</a></code>, and <code><a href="/link/gqi.odfvmf?package=gdimap&version=0.0-3" rd-options="" data-mini-rdoc="gdimap::gqi.odfvmf">gqi.odfvmf</a></code>.
For fibre orientation estimation based on local peak detection procedures see <code><a href="/link/gqi.odfpeaklines?package=gdimap&version=0.0-3" rd-options="" data-mini-rdoc="gdimap::gqi.odfpeaklines">gqi.odfpeaklines</a></code>, and <code><a href="/link/gqi.odfpeaks?package=gdimap&version=0.0-3" rd-options="" data-mini-rdoc="gdimap::gqi.odfpeaks">gqi.odfpeaks</a></code>.
Visualization of RGB-maps and glyph-maps is implemented through <code><a href="/link/rgbvolmap?package=gdimap&version=0.0-3" rd-options="" data-mini-rdoc="gdimap::rgbvolmap">rgbvolmap</a></code> and <code><a href="/link/gqi.odfvxgrid?package=gdimap&version=0.0-3" rd-options="" data-mini-rdoc="gdimap::gqi.odfvxgrid">gqi.odfvxgrid</a></code>, respectively.
Various types of simulations of diffusion and ODF profiles, illustrating the application of vMF mixtures for fibre orientation estimation are implemented in <code><a href="/link/simulglyph.vmf?package=gdimap&version=0.0-3" rd-options="" data-mini-rdoc="gdimap::simulglyph.vmf">simulglyph.vmf</a></code>, <code><a href="/link/simul.simplefield?package=gdimap&version=0.0-3" rd-options="" data-mini-rdoc="gdimap::simul.simplefield">simul.simplefield</a></code>, <code><a href="/link/simul.fandtasia?package=gdimap&version=0.0-3" rd-options="" data-mini-rdoc="gdimap::simul.fandtasia">simul.fandtasia</a></code>.
Data sets used in the examples are documented.

package

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).  An optimized reconstruction technique based on the
        generalized q-sampling imaging (GQI) approach is adopted to
        reconstruct orientation distribution function (ODF) profiles.
        Two methods have been implemented to estimate fibre
        orientations. 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.  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.

gdimap-package: Generalized Diffusion Magnetic Resonance Imaging

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