# skullstrip anatomy
print("Skullstrip INV2")
skullstrip_spm12(fileINV2, pathSPM12, path)
# bring skullstrip_mask in conformed space (mri_vol2vol, NN)
transmask = ApplyVolTransform()
transmask.inputs.source_file = os.path.join(path_skull,
"skullstrip_mask.nii")
transmask.inputs.target_file = os.path.join(path, sub, "mri", "orig.mgz")
transmask.inputs.reg_header = True
transmask.inputs.interp = "nearest"
transmask.inputs.transformed_file = os.path.join(path, sub, "mri",
"skullstrip_mask.nii")
transmask.inputs.args = "--no-save-reg"
transmask.run()
# apply skullstrip mask to T1 and save as brainmask
multiply_images(os.path.join(path, sub, "mri", "T1.mgz"),
os.path.join(path, sub, "mri", "skullstrip_mask.nii"),
os.path.join(path, sub, "mri", "brainmask.mgz"))
multiply_images(os.path.join(path, sub, "mri", "T1.mgz"),
os.path.join(path, sub, "mri", "skullstrip_mask.nii"),
os.path.join(path, sub, "mri", "brainmask.auto.mgz"))
# autorecon2 and autorecon3
print("Autorecon2 and Autorecon3")
os.system("recon-all" + \
" -hires" + \
" -autorecon2" + " -autorecon3" + \
def skullstrip_refined(file_mask1, file_mask2):
"""
The purpose of the following function is to enhance the skullstrip mask in native space. It
uses a second mask which was manually corrected during the freesurfer segmentation. This
corrected brainmask is converted to native space and multiplied with the initial brainmask.
Inputs:
*file_mask1: brainmask in original space.
*file_mask2: manually corrected brainmask in freesurfer space (brain.finalsurfs.mgz).
Outputs:
*file_out: filename of enhanced brainmask.
created by Daniel Haenelt
Date created: 31-01-2020
Last modified: 31-01-2020
"""
import os
import nibabel as nb
from nipype.interfaces.freesurfer import ApplyVolTransform
from lib.io.get_filename import get_filename
# get output path and basename
path_output, name_output, _ = get_filename(file_mask1)
# filename of temporary and enhanced brainmask
file_temp = os.path.join(path_output, "temp.nii")
file_out = os.path.join(path_output, name_output + "_enhanced.nii")
# bring skullstrip_mask from conformed space into original space
transmask = ApplyVolTransform()
transmask.inputs.source_file = file_mask2
transmask.inputs.target_file = file_mask1
transmask.inputs.reg_header = True
transmask.inputs.interp = "nearest"
transmask.inputs.transformed_file = file_temp
transmask.inputs.args = "--no-save-reg"
transmask.run()
# load first brainmask in original space
mask1 = nb.load(file_mask1)
mask1_array = mask1.get_fdata()
# load second brainmask transformed into original space
mask2 = nb.load(file_temp)
mask2_array = mask2.get_fdata()
# make second brainmask binary
mask2_array[mask2_array == 1] = 0
mask2_array[mask2_array > 0] = 1
# multiply both masks
mask_enhanced_array = mask1_array * mask2_array
# write enhancec brainmask
mask_enhanced = nb.Nifti1Image(mask_enhanced_array, mask1.affine,
mask1.header)
nb.save(mask_enhanced, file_out)
# remove temporary file
os.remove(file_temp)
return file_out
# binarise and overwrite mask
mask = nb.load(os.path.join(path_t1, "mask.nii"))
mask_array = mask.get_fdata()
mask_array[mask_array <= mask_threshold] = 0
mask_array[mask_array != 0] = 1
output = nb.Nifti1Image(mask_array, mask.affine, mask.header)
nb.save(output, os.path.join(path_t1, "mask.nii"))
# transform to mp2rage space via scanner coordinates
applyreg = ApplyVolTransform()
applyreg.inputs.source_file = os.path.join(path_t1, "mask.nii")
applyreg.inputs.target_file = os.path.join(path_t1, "T1.nii")
applyreg.inputs.transformed_file = os.path.join(path_t1, "mask.nii")
applyreg.inputs.reg_header = True
applyreg.inputs.interp = "nearest"
applyreg.run()
"""
convert orig to nifti
"""
mc = MRIConvert()
mc.inputs.in_file = os.path.join(path_orig, "orig.mgz")
mc.inputs.out_file = os.path.join(path_orig, "orig.nii")
mc.inputs.in_type = "mgz"
mc.inputs.out_type = "nii"
mc.run()
"""
scanner transformation
"""
get_scanner_transform(os.path.join(path_orig, "orig.nii"),
os.path.join(path_t1, "T1.nii"), path_scanner, False)
get_scanner_transform(os.path.join(path_t1, "T1.nii"),