dwiMD

dwiMD,ANY-method

dwiMD,dtiData-method

dwiMD,dtiTensor-method

Object of class <code>"dtiData"</code> or <code>"dtiTensor"</code>

object

tolerance in search for good gradient combinations.

Compute mean diffusivity (MD) from dtiData or dtiTensor objects

methods

model

dwiMD-methods

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

dwiMD-methods function

<dl class="dl-horizontal"><dt><code>signature(object = "ANY")</code></dt><dd>Returns a warning</dd><dt><code>signature(object = "dtiData")</code></dt><dd>searches for three gradients that enable best MD evaluation. Returns MD.</dd>
<dt><code>signature(object = "dtiTensor")</code></dt><dd>calculates MD values from estimated difusion tensors</dd>
</dl>

dwiMD-methods: Methods for Mean Diffusivity in Package `dti'

Description

Usage

Arguments

Value

Methods

See Also