[Neuroimaging] [Nibabel] Public dataset generates unexpected

[Eleftherios Garyfallidis]

Thanks for the feedback Matthew.

Here is also a script that corrects another problem in the DWI data. There
the last bvector is incorrect.

https://gist.github.com/Garyfallidis/199813624bb6d2dac3f51aa6b41717af

I will send the authors an e-mail with both issues.
For the first issue I think they used some tool that does not contain the
affine after reslicing.
Probably the original data have an actual resolution of 2x2x3.7 which is
not ideal for tracking (even after reslicing).

Cheers,
Eleftherios

On Sun, Sep 10, 2017 at 4:04 PM Eleftherios Garyfallidis <elef at indiana.edu>
wrote:

> Clearly the title was meant to be "Public dataset generates unexpected
> affine matrix" :)
> Apologies,
> Eleftherios
>
> On Sun, Sep 10, 2017 at 1:31 PM Eleftherios Garyfallidis <elef at indiana.edu>
> wrote:
>
>> Hello Matthew and all,
>>
>> I downloaded a dataset from NITRC  by Boekel et al.
>> https://www.nitrc.org/projects/dwi_test-retest/
>>
>> and I used nibabel to get the affine and voxel size. The authors claimed
>> that the voxel size is 2x2x2mm^3 however the affine tells a different story.
>>
>> import nibabel as nib
>>
>> img = nib.load('pp26_dwi_run01_A.nii.gz')
>>
>> print(img.affine)
>> [[  -1.999    0.047    0.077  108.292]
>>  [   0.042    1.984   -0.471  -94.461]
>>  [   0.047    0.251    3.703 -116.857]
>>  [   0.       0.       0.       1.   ]]
>>
>> nib.affines.voxel_sizes(img.affine)
>> *array([ 2.   ,  2.   ,  3.733])*
>>
>> The zoom function gives a different answer in agreement with the authors'
>> claim.
>>
>> img.header.get_zooms()[:3]
>> *(2.0, 2.0, 2.0)*
>>
>> Could it be that the authors damaged the header during preprocessing?
>> I am assuming here that nibabel is bringing the correct information i.e.
>> whatever is in the Nifti1 image.
>>
>> If you agree that this is an issue with the data itself. It would be nice
>> to contact the authors.
>>
>> Best regards,
>> Eleftherios
>>
>
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