polyeder

icosa0

icosa1

icosa2

icosa3

icosa4

icosa0 - icosa4 provide a description of regular polyeders
       derived from the Icosahedron (icosa0) by 
       sequential triangulation of surface triangles

datasets

Diffusion Weighted Imaging is a Magnetic Resonance Imaging
        modality, that measures diffusion of water in tissues like the
        human brain. The package contains R-functions to process
        diffusion-weighted data in the context of the diffusion tensor
        model (DTI). This includes the calculation of anisotropy
        measures and, most important, the implementation of our
        structural adaptive smoothing algorithm as described in K.
        Tabelow, J. Polzehl, V. Spokoiny, and H.U. Voss, Diffusion
        Tensor Imaging: Structural Adaptive Smoothing, Neuroimage
        39(4), 1763-1773 (2008).

Karsten Tabelow

DTI/DWI Analysis

polyeder function

a list with components 
    <ul><li>vertices</li></ul>{array of dimension <code>c(3,nv)</code> containing cartesian coordinate of the <code>nv</code> vertices.}
       <item>indices</item>{Indices of vertices that define surface triangles of the polyeder.}
       <item>edges</item>{Indices of vertices that define edges of the polyeder.}
       <item>nv</item>{number of vertices}
       <item>ne</item>{number of edges}
       <item>ni</item>{number of triangles}

format

Polyeders derived from the Icosahedron (icosa0) by 
       sequential triangulation of surface triangles

polyeder: Polyeders derived from the Icosahedron (icosa0) by sequential triangulation of surface triangles

Description

Usage

Arguments

format