Open garincle opened 6 years ago
Yes, you are right. I think AFNI can take a path instead of a resolution value to choose the grid of the output of 3dNwarpApply, so may be this would be a better option in PR #68
actually I was wondering if we can directly give the downsampled version of the template as master
for the 3dNwarpApply
.
@nadkarni-na if all the registration steps are done with say dorr at 0.1mm and then we use 3dNwarpApply
with master being dorr at 0.2 mm, will this be handled OK by AFNI ?
I think so
actually I don't know how your template200 has been generated from the template100. If I do a simple AFNI 3dresample, I get the following affine
array([[ 0.2 , -0. , -0. , -6.18499994],
[-0. , 0.2 , -0. , -8.08499908],
[ 0. , 0. , 0.2 , -4.08499956],
[ 0. , 0. , 0. , 1. ]])
and this is exactly (no numeric errors) the same affine you get for your registered functional to template100 with voxel_size=(.2, .2, .2)
. So you need to get the information how template200 has been generated.
Affine difference for functional images after registration.fmri_sessions_to_template on a brain 100µm template and a func_resolution at 200µm given. Affine diff near 10*10^7
The differance could be du to numeric error. To fixe the problem: New template at the resolution wanted only for the func_to_template function ?