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TendEstim

Information

Package: Teem
Catagory: Tend
Author(s): Martin Cole
Status: Supported in latest version
Version: 3.0

Description

Summary

Estimate tensors from a set of DW images.

Detailed Description

Estimate tensors from a set of DW images. The various DWI volumes must be stacked along axis 0 (as with the output of "tend epireg"). The tensor coefficient weightings associated with each of the DWIs, the B-matrix, is given as a seperate array, see "tend bmat" usage info for details. 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.

B0 is stored as first DWI value : Determines if the B=0 non-diffusion-weighted reference image is known, or if it has to be estimated along with the tensor elements. Check it if true to indicate that the B=0 image is the FIRST input image given , and hence the B-matrix has ONE LESS row than the number of of input images. If false, there is no reference image; all the input images are diffusion-weighted in some way or another, and there exactly as many rows in the B-matrix as there are input images

Threshold :

Soft : how fuzzy the confidence boundary should be. By default, confidence boundary is perfectly sharp. This value should be a float.

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. This value should be a float.



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