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 (DWI) 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. The functionality includes diffusion tensor imaging (DTI),
diffusion kurtosis imaging (DKI), modeling for high angular resolution
diffusion weighted imaging (HARDI) using Q-ball-reconstruction and
tensor mixture models, several methods for structural adaptive
smoothing including POAS and msPOAS, and a streamline fiber tracking
for tensor and tensor mixture models.
The package provides functionality to manipulate and visualize results
in 2D and 3D.

Karsten Tabelow

Analysis of Diffusion Weighted Imaging (DWI) Data

Joerg Polzehl

Felix Anker

polyeder function

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

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

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

Description

Usage

Arguments

Format