[Neuroimaging] Reconstruction of the diffusion signal with the Tensor model after de-noising

[Samuel Pilgrim]

Neuroimaging mailing list,

I'm an undergraduate experimenting with dipy and am currently working on a
project that would combine a few of the examples given in the
documentation.  In particular, I'd like to be able to take one of the
sample data-sets, apply the de-noising procedure described in the
documentation under "Denoise images using Non-Local Means" and then use the
tensor model to reconstruct the diffusion signal using the de-noised data.
I have scripts that do each of these things separately, but when I try to
do reconstruction with de-noised data, I get an alignment error on the line
that reads "  tenfit = tenmodel.fit(maskdata)  ".  I believe the issue is
caused by a command in the de-noising part of the script that goes  "  data
= data[..., 1]  ".  After this line, the dimension of the object data has
been reduced by one, (i.e. the command print(data.shape) returns a tuple of
3 integers instead of 4.  I think this is what's causing the alignment
issue later, but I also can't get it to run without this line.  Any
assistance would be greatly appreciated.

Best,
Sam
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