Summary of what happened:
Dear Neurostars experts,
I am currently trying to project 3D density maps in individual diffusion space onto the cortical surface (within individual space).
I’m not sure which registration function to use to obtain the register.dat file required for mri_vol2surf .
I used bbregister but I am quite sure this is not the function I should use in this situation. Assuming I create a registration from diffusion space (RASmm/ACPC) to fsnative, would the --mov file as the T1w in diffusion space – same affine as that of the diffusion data– (obtained from qsiprep) work with the target being the T1 in fsnative space?
What other type of function such as tkregister2 or not freesurfer function can I use here?
Command used (and if a helper script was used, a link to the helper script or the command generated):
template_file = op.join(bids_path, 'derivatives', 'qsiprep', participant, 'anat',f"{participant}_space-ACPC_desc-preproc_T1w.nii.gz")
registration_file = op.join(out_dir, 'ACPC2fsnative_register.dat')
# 1) Generate registration file .dat
cmd = ["bbregister",
"--s", participant,
"--sd", fs_path,
"--mov", template_file,
"--reg", registration_file,
"--init-fsl",
"--t1"
]
print("Running:", " ".join(cmd))
subprocess.run(cmd, check=True, env={**os.environ, "SUBJECTS_DIR": fs_path})
#2) Apply ACPC2fsNative registration and project density map to surface
hemisphere = ['L', 'R']
roi = ['LeftMTxWMxLGN', 'RightMTxWMxLGN']
for h, hemi in enumerate(hemisphere):
mask = roi[h]
density_map = op.join(analysis_path, 'tdi_maps', 'dipy_tdi_maps', participant, f"{participant}_ses-concat_desc-{mask}_tdi_map.nii.gz")
# density_img = nib.load(density_map)
# print(density_img.affine)
# Output file name
out_file = os.path.join(out_dir, f"{participant}_hemi-{hemi}_space-fsnative_label-{mask}_tdi_on_surf.mgh")
if hemi == 'L':
hm = 'lh'
else:
hm = 'rh'
# Build mri_vol2surf command
cmd = [
"mri_vol2surf",
"--mov", density_map,
"--regheader", participant,
"--hemi", hm,
"--reg", registration_file,
"--surf", "white",
"--projfrac", "0",
"--sd", fs_path,
"--out", out_file
]
# Run the command
print("Running:", " ".join(cmd))
subprocess.run(cmd, check=True, env={**os.environ, "SUBJECTS_DIR": fs_path})
### Screenshots / relevant information:
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