5ttgen warning poor registration

Dear community:
I have run the code below,
5ttgen fsl anat.mif 5tt_nocoreg.mif -mask mask.mif -force

and it gavem me this warning

5ttgen: [WARNING] Generated image does not perfectly conform to 5TT format:
5ttgen: [WARNING] 5ttcheck: [WARNING] Image “result.mif” contains 44 brain voxels with non-unity sum of partial volume fractions
5ttgen: [WARNING] 5ttcheck: [WARNING] Input image does not perfectly conform to 5TT format, but may still be applicable (suggest re-running using the -masks option to see voxels where tissue fractions do not sum to 1.0)

if i continue the processing towards the structural connectome

tck2connectome: [WARNING] The following nodes do not have any streamlines assigned:
tck2connectome: [WARNING] 1, 3, 7, 8, 10, 14, 17, 18, 19, 21, 23, 26, 29, 30, 31, 33, 36, 37, 38, 39, 40, 42, 43, 44, 46, 80
tck2connectome: [WARNING] (This may indicate a poor registration)

Hey there - a few questions/suggestions for troubleshooting:

  1. Did you inspect the 5tt_nocoreg.mif image after you generated it? Does the segmentation into gray matter, white matter, etc. make sense? If you’re using the gmwm boundary, overlay that on the image as a sanity check.
  2. Did anything funky happen when you generated whole-brain streamlines? Do you find streamlines across the whole-brain when you overlay the tractography on the diffusion image? (Warning: don’t overlay the main streamline output, but a tck file with a smaller number of streamlines to avoid crashing your computer.)
  3. What about QAing the atlas-related outputs in the steps between 5ttgen and tck2connectome? The tck2connectome suggestion about poor registration means you should probably make sure that nothing went wrong for: atlas parcellation of your T1 anat image, the transformation from T1-space to diffusion space?

Good luck!

5tt_nocoreg.mif makes no sense. It seems everything is condensed in one image. I don’t know how to explain just that you don’t have all the views normally but just one square with all brain views superimposed. Anyways thats the issue. I don’t know if just omit this subject from the study or there is any fix.