TensorCalc

TensorCalc[data,gradients,bvec]

calculates the diffusion tensor for the given dataset. allows for multiple unweighted images and multiple bvalues. allows for different tensor fitting methods. gradient directions must be in the form {{x1,y1,z1}, ..., {xn,yn,zn}} with the unweighted direction as {0,0,0}. bvec the b-vector, with a bvalue defined for each gradient direction. b value for unweighted images is 0.

TensorCalc[data,bmatrix]

calculates the diffusion tensor for the given dataset. allows for multiple unweighted images and multiple bvalues. bmat is the bmatrix which can be generated using Bmatrix. The bvalue assumed to be is in s/mm^2 and therefore the output is in mm^2/2.

TensorCalc[]

is based on DOI: 10.1016/j.neuroimage.2013.05.028 and 10.1002/mrm.25165.

Details
Details and Options Details and Options
QMRITools`
QMRITools`

TensorCalc

TensorCalc[data,gradients,bvec]

calculates the diffusion tensor for the given dataset. allows for multiple unweighted images and multiple bvalues. allows for different tensor fitting methods. gradient directions must be in the form {{x1,y1,z1}, ..., {xn,yn,zn}} with the unweighted direction as {0,0,0}. bvec the b-vector, with a bvalue defined for each gradient direction. b value for unweighted images is 0.

TensorCalc[data,bmatrix]

calculates the diffusion tensor for the given dataset. allows for multiple unweighted images and multiple bvalues. bmat is the bmatrix which can be generated using Bmatrix. The bvalue assumed to be is in s/mm^2 and therefore the output is in mm^2/2.

TensorCalc[]

is based on DOI: 10.1016/j.neuroimage.2013.05.028 and 10.1002/mrm.25165.

Details

  • The following options can be given:
  • MonitorCalcTrueMonitorCalc is an option for many processing functions. When true the process of the calculation is shown.
    Method"iWLLS"Method is an option for various algorithm-intensive functions that specifies what internal methods they should use.
    FullOutputTrueFullOutput is an option for TensorCalc when using b-vector. When True also the s0 is given as output.
    RobustFitTrueRobustFit is an option for TensorCalc. If true outliers will be rejected in the fit, only works with WLLS. If FullOutput is given the outlier map is given.
    ParallelizeTrueParallelize[expr] evaluates expr using automatic parallelization.
    RobustFitParameters{0.1, 5}RobustFitParameters is an option for TensorCalc. gives the threshold for stopping the iterations and the kappa for the outlier margin, {tr,kappa}.