Most likely. Please add an issue in Github! Thank you Giulia!

On Thu, Nov 21, 2019 at 1:37 PM Giulia Berto' <gberto@fbk.eu> wrote:

Great, thank you!

Does then the example "Automatic Fiber Bundle Extraction with RecoBundles" here https://dipy.org/documentation/1.0.0./examples_built/bundle_extraction/ need to be updated? I guess that sft_atlas = load_trk(atlas_file, "same", bbox_valid_check=False) needs a reference rather that "same".

Thank you.

best,

Giulia

On Thu, Nov 21, 2019 at 6:30 PM Eleftherios Garyfallidis <elef@indiana.edu> wrote:

Yes, you can correct the affine by using the StatefulTractogram and the affine of the data that generated the tracks or the original tractogram

https://dipy.org/documentation/1.0.0./examples_built/streamline_formats/#example-streamline-formats

On Thu, Nov 21, 2019 at 12:28 PM Giulia Berto' <gberto@fbk.eu> wrote:

Hi,

I am trying to use the atlas of 80 bundles you distribute here https://figshare.com/articles/Advanced_Atlas_of_80_Bundles_in_MNI_space/737588, but I am encountering some issues.

It is written that the files are in MNI space ICBM 2009a, which has affine equal to

array([[   1.,    0.,    0.,  -98.],
       [   0.,    1.,    0., -134.],
       [   0.,    0.,    1.,  -72.],
       [   0.,    0.,    0.,    1.]])

However, all the trk files have affine equal to the identity matrix. Is there a reason why you stored in the header of the trk files the identity matrix? This for example prevents their correct visualization in TrackVis. 

Another question: the file whole_brain_MNI.trk, besides having the same issue with the affine, has 144678 streamlines. Is it the same whole brain tractogram Yeh is referring to in their paper? In that paper they obtained a tractogram of 550000 streamlines. Or is it maybe the union of the 80 bundles?

Thank you a lot for your help,

best regards,

Giulia

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