dtiTensor-class {dti} | R Documentation |
Diffusion Tensor object. Containes the results of estimating a diffusion tensor from diffusion weighted image (DWI) data.
Objects can be created by calls to functions dtiTensor
, dti.smooth
or medinria2tensor
.
.Data
:"list"
with optional components
s2rician
rician=TRUE
in function dti.smooth
ni
dti.smooth
)D
:"array"
contains estimated tensors, dimension c(6,ddim)
.
Tensors are stored as upper diagonal matrices.th0
:"array"
contains estimated intensities in S0 images, dimension ddim
sigma
:"array"
containing estimated error variancesscorr
:"numeric"
containing estimated spatial correlations in coordinate directionsbw
:"numeric"
containing bandwidth for a Gaussian kernel that approximately creates
the estimated spatial correlations. Needed for adjustments of critical values in the adaptive smoothing algorithm used in function dti.smooth
mask
:"array"
, logical array indicating the voxel where the tensor was estimated.level
:"numeric"
minimal valid s0-level.
No evaluation was be performed for voxel with s0-values less than level
. Used to determine mask
.hmax
:"numeric"
maximal bandwidth in case of adaptive smoothing. contains 1 otherwise.method
:"character"
either "linear"
or "nonlinear"
or "unknown"
. Indicates the regression model used for estimating the tensors.btb
:"matrix"
matrix of dimension c(6,ngrad)
obtained from gradient directions.ngrad
:"integer"
number of gradients (including zero gradients) s0ind
:"integer"
index of zero gradients within sequence 1:ngrad
replind
:"integer"
index (identifier) of unique
gradient directions. Used to charactreize replications in the gradient design by identical indices. length is ngrad
ddim
:"integer"
dimension of original image cubes. Integer vector of length 3. ddim0
:"integer"
dimension of subcube defined by xind
, yind
and zind
. xind
:"integer"
index for subcube definition in x-direction yind
:"integer"
index for subcube definition in y-direction zind
:"integer"
index for subcube definition in z-direction voxelext
:"numeric"
voxel extensions in x-, y- and z-direction. vector of length 3. source
:"character"
name of the imgfile used to create the data.
Class "list"
, from data part.
Class "dti"
, directly.
Class "vector"
, by class "list", distance 2.
signature(object = "dtiTensor")
: Calculate fractal anisotropy (FA) and main directions of anisotropy from diffusion tensors. signature(object = "dtiTensor")
: Smooth diffusion tensor. For exploration only. We strictly recommend using function dti.smooth
on a dtiData
-object. signature(x = "dtiTensor")
: not jet implemented. Karsten Tabelow tabelow@wias-berlin.de, J"org Polzehl polzehl@wias-berlin.de
K. Tabelow, J. Polzehl, H.U. Voss, and V. Spokoiny. Diffusion Tensor Imaging: Structural adaptive smoothing, NeuroImage 39(4), 1763-1773 (2008).
http://www.wias-berlin.de/projects/matheon_a3/
dtiData
,dtiTensor
,dtiIndices
,dti.smooth
, dti
, dtiData
, dtiIndices
showClass("dtiTensor") ## Not run: demo(dti_art)