# tend-estim - Man Page

estimate tensors from a set of DW images

## Synopsis

**tend estim** [**-old**] [**-sigma** <*sigma*>] [**-v** <*verbose*>] [**-est** <*estimate method*>] [**-wlsi** <*WLS iters*>] [**-fixneg**] [**-ee** <*filename*>] [**-eb** <*filename*>] [**-t** <*thresh*>] [**-soft** <*soft*>] [**-scale** <*scale*>] [**-mv** <*min val*>] **-B** <*B-list*> [**-b** <*b*>] **-knownB0** <*bool*> [**-i** <*dwi0 dwi1* ...>] [**-o** <*nout*>]

## Description

Estimate tensors from a set of DW images. The tensor coefficient weightings associated with each of the DWIs, the B-matrix, is given either as a separate array, (see tend-bmat(1)**for** details), or by the key-value pairs in the DWI *nrrd* header. A “confidence” value is computed with the tensor, based on a soft thresholding of the sum of all the DWIs, according to the threshold and softness parameters.

## Options

- -old
instead of the new

**tenEstimateContext**code, use the old**tenEstimateLinear**code- -sigma <
*sigma*> Rician noise parameter (

*float*)- -v <
*verbose*> verbosity level (

*int*) default: “**0**”- -est <
*estimate method*> estimation method to use. “

**lls**”: linear-least squares; default: “**lls**”- -wlsi <
*WLS iters*> when using weighted-least-squares (“

**-est wls**”), how many iterations to do after the initial weighted fit. (*unsigned int*) default: “**1**”- -fixneg
after estimating the tensor, ensure that there are no negative eigenvalues by adding (to all eigenvalues) the amount by which the smallest is negative (corresponding to increasing the non-DWI image value).

- -ee <
*filename*> Giving a filename here allows you to save out the tensor estimation error: a value which measures how much error there is between the tensor model and the given diffusion weighted measurements for each sample. By default, no such error calculation is saved. (

*string*)- -eb <
*filename*> In those cases where there is no B=0 reference image given (“

**-knownB0 false**”), giving a filename here allows you to save out the**B=0**image which is estimated from the data. By default, this image value is estimated but not saved. (*string*)- -t <
*thresh*> value at which to threshold the mean DWI value per pixel in order to generate the “confidence” mask. By default, the threshold value is calculated automatically, based on histogram analysis. (

*double*)- -soft <
*soft*> how fuzzy the confidence boundary should be. By default, confidence boundary is perfectly sharp (

*float*) default: “**0**”- -scale <
*scale*> After estimating the tensor, scale all of its elements (but not the confidence value) by this amount. Can help with downstream numerical precision if values are very large or small. (

*float*) default: “**1**”- -mv <
*min val*> minimum plausible value (especially important for linear least squares estimation) (

*double*) default: “**1.0**”- -B <
*B-list*> 6-by-N list of B-matrices characterizing the diffusion weighting for each image. tend-bmat(1) is one source for such a matrix; see its usage info for specifics on how the coefficients of the B-matrix are ordered. An unadorned plain text file is a great way to specify the B-matrix.

**OR**Can say just “

**-B kvp**” to try to learn B matrices from key/value pair information in input images.(

*string*)- -b <
*b*> “b” diffusion-weighting factor (units of sec/mm^2) (

*double*)- -knownB0 <
*bool*> Indicates if the

**B=0**non-diffusion-weighted reference image is known, or if it has to be estimated along with the tensor elements- if “
**true**”: in the given list of diffusion gradients or B-matrices, there are one or more with zero norm, which are simply averaged to find the**B=0**reference image value - if “
**false**”: there may or may not be diffusion-weighted images among the input; the**B=0**image value is going to be estimated along with the diffusion model

(

*bool*)- if “
- -i <
*dwi0 dwi1*...> all the diffusion-weighted images (DWIs), as separate 3D

*nrrd*s,**OR**: One 4D*nrrd*of all DWIs stacked along axis 0 (1 or more*nrrd*s); default: “**-**”- -o <
*nout*> output tensor volume (

*string*) default: “**-**”

## See Also

## Referenced By

tend(1), tend-bmat(1), tend-msim(1), tend-sim(1).