dtiData-class {dti} | R Documentation |
Diffusion Weighted Image (DWI) Data
Objects can be created by calls of function dtiData
.
.Data
:"list"
with component si
c(ddim,ngrad)
level
:"numeric"
minimal valid s0-level.
No evaluation will be performed for voxel with s0-values less than level
. 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. orientation
:"integer"
vector of length 3. Orientation of data according to AFNI convention.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 = "dtiData")
: Create estimates of diffusion tensors in each voxel using structural adaptive spatial smoothing. signature(object = "dtiData")
: Create estimates of diffusion tensors in each voxel. signature(x = "dtiData")
: not yet 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
, dti.smooth
, dti
, dtiTensor
, dtiIndices
showClass("dtiData") ## Not run: demo(dti_art)