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dti (version 1.2-0.1)

dwiMixtensor-methods: Methods for Function `dwiMixtensor' in Package `dti'

Description

The method estimates, in each voxel, a mixture of radial symmetric tensors from the DWI data contained in an object of class "dtiData".

Usage

## S3 method for class 'dtiData':
dwiMixtensor(object, maxcomp=3,        
          model=c("MT","MTiso","MTisoFA","MTisoEV"), fa=NULL, 
          lambda=NULL, reltol=1e-10, maxit=5000, ngc=1000, 
          nguess=100*maxcomp^2, msc=c("BIC","AIC","AICC","none"), 
          mc.cores = setCores(,reprt=FALSE))
## S3 method for class 'dwiMixtensor,dwiMixtensor':
dwiMtCombine(mtobj1, mtobj2, msc="BIC", where=NULL)

Arguments

object
Object of class "dtiData"
maxcomp
Maximal number of mixture components.
model
Specifies the mixture model used. "MT" corresponds to a mixture of prolate tensors, "MTiso" includes an isotropic compartment, "MTisoFA" additionally fixes FA to the value given in argument fa and
fa
Value for FA in case of model="MTisoFA" or model="MTisoEV"
lambda
Value for first eigenvalue in case of model="MTisoEV"
reltol
Relative tolerance for R's optim() function.
maxit
Maximal number of iterations in R's optim() function.
ngc
provide information on number of voxel processed, elapsed time and estimated remaining time after ngc voxel.
nguess
number of guesses in search for initial estimates
msc
Criterion used to select the order of the mixture model, either BIC (Bayes Information Criterion) AIC (Akaike Information Criterion) or AICC ((Bias-)Corrected Akaike Information Criterion). None ma
mtobj1
For method "dwiMtCombine" an "dwiMixtensor"-object.
where
Mask of voxel for which "dwiMtImprove" or "dwiMtCombine" should be performed.
mtobj2
For method "dwiMtCombine" an "dwiMixtensor"-object obtained from the same "dwiData" object. The maximum number of components in mtobj2 should preferably be less or equal to the maximum number of compone
mc.cores
Number of cores to use. Defaults to number of threads specified for openMP, see documentation of package awsMethods. Our experience suggests to use 4-6 cores if available.

Value

  • An object of class "dwiMixtensor".

Details

For model=="MT" the function estimates, in each voxel, a mixture of radial symmetric (prolate) tensors from the DWI data contained in an object of class "dtiData". The number of mixture components is selected depending on the data, with a maximum number of components specified by maxcomp. Optimization is performed usin R's internal BFGS code with mixture weights (volumes of compartments corresponding to a tensor component) computed using the Lawson-Hannson NNLS code. In case of model=="MTiso" the model additionally contains an isotropic compartment. Optimization uses the internal L-BFGS-B code. model=="MTisoFA" and model=="MTisoEV" fix FA and eigenvalues of the prolate tensors, respectively, in the tensor mixture model with isotropic compartment.

The method "dwiMtCombine" enables to combine results obtained for the same dwi data set with different specifications, e.g. for maximum number of components mcomp and settings that influence initial estimates. The combined result contains in each voxel the best result from both reconstructions with respect to the specified model selection criterion msc.

References

Jian et al. (2007), A novel tensor distribution model for the diffusion-weighted MR signal, NeuroImage 37, 164--176.

See Also

dtiData, readDWIdata, medinria, dtiData, dwiMixtensor

Examples

Run this code
demo(mixtens_art)

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