I'm making progress, but I can't fix this. the output is:

start volume math
end volume math
volume thresholds are nan to nan
start raw mapping
nan% of in-range, in-mask voxels failed the threshold
nan% of in-range, in-mask voxels failed the threshold
end raw mapping
start correction
Out of 240195 cortex nodes:
100% were zero and needed reconstruction
0% were discarded by threshold
When reconstructing discarded nodes:
100% were zero and not used
0% were outside threshold and ignored
Out of 241248 cortex nodes:
100% were zero and needed reconstruction
0% were discarded by threshold
When reconstructing discarded nodes:
100% were zero and not used
0% were outside threshold and ignored
end correction


I have: a left and right white, pial, midthickness (average). these
surfaces were transformed into caret space much in the way you describe on
the wiki, but with an extra bit to resacle to 0.25mm from 1mm.

the T1w is perfectly in register with the surfaces. It has 0.25mm voxels,
and it's an MTR. I scaled it so that the WM is generally around 110, as in
FS. the T2w is a mask of T1w with all non-zero voxels set to 1, so that
T1w/T2w=T1w which is what I want since I'm using MTR. the ribbon is the
freesurfer ribbon, again reset to 0.25mm voxels. I set the right side of
the ribbon to 255 and the left to 120.

All the volumes are in perfect register. all have the same AC setting in
caret. All have voxel ordering +++. The surfaces are all perfectly
registered to the volumes.

the thickness metric was obtained by changing the FS max from 5 to 40mm,
converting the thickness file as instructed to a metric, dividing that by
4, to get thickness for 0.25mm via the 1mm trick. loading the metric files
give plausible values on the surface of about 1mm in V1, up to a maximum of
maybe 3mm in dorsal motor regions. The curvature metric also seems exactly
right.

the topo is derived from the freesurfer wm surface.

I've run out of ideas. I'll try making the ribbon a volume of ones. I doubt
that'll fix it.

sorry about this, it would really be nice to get this myelin map for the
monkey. tests using simpler mapping methods indicate it's definitely worth
it.

We want to see how this relates to some diffusion properties in the GM, and
actually tracking termination patterns also.

best,

Colin
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