| """ |
| Post-process Mindboggle-101 volume images for distribution, |
| using Mindboggle, FreeSurfer, and FSL tools: |
|
|
| # Convert label volume from FreeSurfer to original space |
| # Extract brain by masking with manual cortical |
| and automated subcortical labels |
| # Remove subcortical labels |
| # Convert DKT31 to DKT25 labels |
| # Affine register T1-weighted brain to MNI152 brain |
| # Transfer whole-head images with affine transform |
| # Transfer labeled images with affine transform |
| (and nearest neighbor interpolation) |
|
|
| Authors: Arno Klein . arno@mindboggle.info . www.binarybottle.com |
|
|
| (c) 2013 Mindbogglers (www.mindboggle.info), under Apache License Version 2.0 |
|
|
| """ |
|
|
| import os |
|
|
| # Paths, template, and label conversion files |
| mb101_path = '/hd2/Lab/Brains/Mindboggle101/' |
| mb_info_path = '/projects/Mindboggle/mindboggle/mindboggle/info/' |
| template = mb101_path+'MNI152space/MNI152_T1_1mm_brain.nii.gz' |
| relabel_file = os.path.join(mb_info_path, 'labels.volume.DKT31to25.txt') |
|
|
| # Loop through subjects |
| list_file = mb_info_path + 'atlases101.txt' |
| fid = open(list_file, 'r') |
| subjects = fid.readlines() |
| subjects = [''.join(x.split()) for x in subjects] |
| for subject in subjects: |
|
|
| print(">>> Process subject: {0}...".format(subject)) |
| subject_path = mb101_path + 'subjects/' + subject + '/mri/' |
|
|
| # Identify original files |
| full_labels_orig = subject_path+'aparcNMMjt+aseg.nii.gz' |
| head = subject_path+'t1weighted.nii.gz' |
|
|
| # Name all output files |
| local_labels0 = 'labels.DKT31.manual+aseg.nii.gz' |
| full_labels = subject_path + local_labels0 |
| local_labels = 'labels.DKT31.manual.nii.gz' |
| DKT31_labels = subject_path + local_labels |
| DKT25_labels = subject_path + 'labels.DKT25.manual.nii.gz' |
| brain = subject_path+'t1weighted_brain.nii.gz' |
| xfm_matrix = subject_path+'t1weighted_brain.MNI152.mat' |
| xfm_brain = subject_path+'t1weighted_brain.MNI152.nii.gz' |
| xfm_head = subject_path+'t1weighted.MNI152.nii.gz' |
| xfm_DKT25 = subject_path+'labels.DKT25.manual.MNI152.nii.gz' |
| xfm_DKT31 = subject_path+'labels.DKT31.manual.MNI152.nii.gz' |
| xfm_DKT31aseg = subject_path+'labels.DKT31.manual+aseg.MNI152.nii.gz' |
|
|
| # Convert label volume from FreeSurfer to original space |
| print("Convert label volume from FreeSurfer to original space...") |
| #if 'OASIS-TRT-20-' in subject or 'NKI-TRT-20-' in subject: |
| cmd = ' '.join(['mri_vol2vol --mov', full_labels_orig, '--targ', head, |
| '--regheader --o', full_labels]) |
| #cmd = ' '.join(['mri_convert -rl', head, '-rt nearest', |
| # full_labels_orig, full_labels]) |
| print(cmd); os.system(cmd) |
|
|
| # Extract brain by masking with labels using FreeSurfer |
| print("Extract brain by masking with labels using FreeSurfer...") |
| cmd = ' '.join(['mri_vol2vol --mov', full_labels, '--targ', head, |
| '--o temp.nii.gz --regheader']) |
| print(cmd); os.system(cmd) |
| cmd = ' '.join(['mri_mask', head, 'temp.nii.gz', brain]) |
| #cmd = ' '.join(['/usr/bin/fsl4.1-fslmaths', head, '-mas', full_labels, brain]) |
| print(cmd); os.system(cmd) |
|
|
| # Remove subcortical labels |
| print("Remove subcortical labels...") |
| from mindboggle.label.relabel import remove_volume_labels |
| labels_to_remove = range(1,300) # Remove noncortical (+aseg) labels |
| labels_to_remove.extend([1000,1001,2000,2001]) |
| remove_volume_labels(full_labels, labels_to_remove) |
| cmd = ' '.join(['mv', local_labels0, DKT31_labels]) |
| print(cmd); os.system(cmd) |
|
|
| # Convert DKT31 to DKT25 labels |
| print("Convert DKT31 to DKT25 labels...") |
| from mindboggle.utils.io_file import read_columns |
| from mindboggle.label.relabel import relabel_volume |
| old_labels, new_labels = read_columns(relabel_file, 2) |
| relabel_volume(DKT31_labels, old_labels, new_labels) |
| cmd = ' '.join(['mv', local_labels, DKT25_labels]) |
| print(cmd); os.system(cmd) |
|
|
| # Affine register T1-weighted brain to MNI152 brain using FSL's flirt |
| print("Affine register T1-weighted brain to MNI152 brain using FSL's flirt...") |
| cmd = ' '.join(['flirt', '-in', brain, '-ref', template, |
| '-out', xfm_brain, '-omat', xfm_matrix]) |
| print(cmd); os.system(cmd) |
|
|
| # Transfer whole-head images with affine transform using FSL's flirt |
| print("Transfer whole-head images with affine transform using FSL's flirt...") |
| cmd = ' '.join(['flirt', '-in', head, '-ref', template, |
| '-applyxfm -init', xfm_matrix, '-out', xfm_head]) |
| print(cmd); os.system(cmd) |
|
|
| # Transfer labeled images with affine transform (and nearest neighbor interpolation) |
| print("Transfer labeled images with affine transform " |
| "(and nearest neighbor interpolation)...") |
| cmd = ' '.join(['flirt', '-in', DKT25_labels, '-ref', template, |
| '-applyxfm -init', xfm_matrix, |
| '-interp nearestneighbour -out', xfm_DKT25]) |
| print(cmd); os.system(cmd) |
|
|
| cmd = ' '.join(['flirt', '-in', DKT31_labels, '-ref', template, |
| '-applyxfm -init', xfm_matrix, |
| '-interp nearestneighbour -out', xfm_DKT31]) |
| print(cmd); os.system(cmd) |
|
|
| cmd = ' '.join(['flirt', '-in', full_labels, '-ref', template, |
| '-applyxfm -init', xfm_matrix, |
| '-interp nearestneighbour -out', xfm_DKT31aseg]) |
| print(cmd); os.system(cmd) |
|
|
|
|
