Dear experts,
I am trying to use pyAFQ to visualize my tract. And I found ‘AFQ.viz.plotly_backend.visualize_bundles’ in the example. And I meet a problem while using my own tract data.
I generated a .tck file from Mrtrix and I cleaned it by pyAFQ ‘clean_bundle’ function successfully. So I want to visualize the cleaned tract.
According to the API_reference , it shows that
AFQ.viz.plotly_backend.visualize_bundles(sft, n_points=None, bundle_dict=None, bundle=None, colors=None, shade_by_volume=None, color_by_streamline=None, sbv_lims=[None, None], include_profiles=(None, None), flip_axes=[False, False, False], opacity=1.0, figure=None, background=(1, 1, 1), interact=False, inline=False)
So I wrote:
MNI_T2_img = afd.read_mni_template()
callosal_templates = afd.read_callosum_templates(resample_to=MNI_T2_img)
bundle_to_viz = SegmentedSFT({“ROItract”: load_tractogram(
tract_dir, img, to_space=Space.VOX)}, Space.VOX)
plotly.io.show(visualize_bundles(bundle_to_viz,
figure=visualize_volume(dtiFile),
shade_by_volume=faFile,
bundle_dict=bundles))
However, the result figure is somewhat strange and incorrect. But if I didn’t provide the variable ‘bundle_dict’, it will result in an error without result. And I don’t understand the meaning of variable ‘bundle_dict’. If I used my own DTI file(.nii.gz), FA_map file(.nii.gz) and track file(.tck), how should I create the variable ‘bundle_dict’ for my data?
When I used other MRI software, it seems that you should just provide a structure file (nii.gz) and a tract file (such as .tck) to present the tract in the space. So when I use ‘AFQ.viz.plotly_backend.visualize_bundles’, I am a little confused to provide the ‘bundle_dict’ after the tract file, dti file and FA file.
By the way, because most pyAFQ examples used python package to import example img data. It confused me quitely how to use my own data presented by pyAFQ if I don’t use it to pre-process my data. But i just want to visualize the tract and dti img generated from Mrtrix because my ROIs are not common brain areas but customized.
Thanks for your time.
Best wishes.
Roger