This question was originally asked on an existing thread, and is really a specific question of its own. As such, it has been split into its own new topic.
Because it contained two separate “starting” points, I have also merged those here.
Hope that isn’t confusing, but this should be clearer to follow as a single thread now, I think.
--------------------------- original question/post --------------------------
I have a relevant question here. Actually, what I want to do is to nonlinearly-warp back the data from the standard space to individual native space. For example, I would like to obtain a set of masks (i.e., atlas) in each individual’s native space. Those masks have been registered to a template in standard space. I used auto_warp.py to warp a subject’s structural image to a template:
auto_warp.py -base template_t1.nii -input subject_t1.nii -skull_strip_input yes
Then, I consider using 3dNwarpApply with -iwarp option as follow:
3dNwarpApply -master subject_t1.nii -dxyz 2 -source atlas_masks.nii -iwarp -nwarp ‘anat.un.aff.qw_WARP.nii anat.un.aff.nii.Xaff.1D’ -ainterp NN -prefix atlas_native_space.nii
I am not sure if I understand option -iwarp correctly, but the result given by script above does not match the subject_t1 image. Actually, it is far away from the subject_t1 image. Could you help to take a look at if this script is the correct way to do this? If not, how can I achieve my goal (i.e., warp-back the masks from standard space to native space according to the nonlinear transformation of subject’s t1 to the template)? Thanks!
To make my question clear: what I want to do is similar as a warp that we can do via affine transformation. For example: we can first register an individual’s structural image to a template by using:
@auto_tlrc -base template+tlrc -input t1+orig -suffix _al
and then, inverse warp a set of masks from standard space back to the native space by using:
cat_matvec -ONELINE t1_al+tlrc::WARP_DATA > tlrc.aff12.1D
3dAllineate -1Dmatrix_apply tlrc.aff12.1D -source masks+tlrc -master t1+orig -prefix masks_in_native_space -final NN
But I would like to do this (both steps) via a nonlinear transformation approach. Is this possible? and any suggestions?