Given the results here, as well as the presence of your other post, this is almost certainly an issue with the diffusion gradient orientations. If your image axes are permuted in any way, the gradient vectors need to be correspondingly modified.
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The
tournieralgorithm gives the result it does because it relies on direct averaging of the signal in the top 300 single-fibre voxels, after rotating those signals such that the fibre direction is along the z-axis. So if the gradient directions are incorrect, that averaging process goes awry. But there’s a good chance that the selected voxels themselves (as shown by the-sf_voxelsoption) will in fact be appropriate. -
The
taxalgorithm relies on iteratively rejecting voxels from the single-fibre selection, based on the response function estimated during the previous iteration. But if calculation of said response function from single-voxel averaging (see point above) is going awry, you end up with a bad response function, concomitantly bad FODs, and all voxels rejected from the single-fibre mask. The message isn’t quite right (it should just print ‘Aborting: All voxels have been excluded from single-fibre selection’, but I’ve failed to import the library function to print said message; I’ll fix that), but the point stands nonetheless.
Cheers
Rob