def results(ants_ct_info, verbose=False):
# Create results directory and populate
util.mkcd_dir([ants_ct_info['base']['results']], True)
files_to_link = [
(ants_ct_info['segment']['p_wm'], ants_ct_info['results']['p_wm']),
(ants_ct_info['segment']['segment'],
ants_ct_info['results']['segment']),
(ants_ct_info['register']['ct'], ants_ct_info['results']['ct']),
(ants_ct_info['register']['subject_to_template_affine'],
ants_ct_info['results']['subject_to_template_affine']),
(ants_ct_info['register']['subject_to_template_warp'],
ants_ct_info['results']['subject_to_template_warp']),
(ants_ct_info['register']['subject_to_template_jacobian'],
ants_ct_info['results']['subject_to_template_jacobian']),
(ants_ct_info['register']['template_to_subject_affine'],
ants_ct_info['results']['template_to_subject_affine']),
(ants_ct_info['register']['template_to_subject_warp'],
ants_ct_info['results']['template_to_subject_warp'])
]
for ii in files_to_link:
util.force_hard_link(ii[0], ii[1])
fsl_command = [
'fslmaths', ants_ct_info['segment']['p_gm_cortical'], '-add',
ants_ct_info['segment']['p_gm_subcortical'],
ants_ct_info['results']['p_gm']
]
util.iw_subprocess(fsl_command)
methods_write_json_redcap_ants_ct_instrument(ants_ct_info, verbose)
def methods_02_stats(config, verbose=False):
input_dir = config['dirs']['input']
util.mkcd_dir([config['methods']['results']['dir']], True)
command = [
'fslmaths',
os.path.join(config['dirs']['methods']['01-register'],
'nu_brain.nii.gz'), '-bin',
os.path.join(config['dirs']['methods']['results'], 'brain_mask.nii.gz')
]
util.iw_subprocess(command, verbose, verbose, False)
for ii in ['swi', 'swi_magnitude', 'swi_phase']:
command = [
'fslmaths',
os.path.join(config['dirs']['methods']['01-register'],
'swi_Affine_nu__' + ii + '.nii.gz'), '-mas',
'brain_mask.nii.gz', ii + '.nii.gz'
]
util.iw_subprocess(command, verbose, verbose, False)
util.force_hard_link(
os.path.join(config['methods']['input']['dir'], 'nu.nii.gz'),
'nu.nii.gz')
util.force_hard_link(
os.path.join(config['methods']['input']['dir'], 'nu_brain.nii.gz'),
'nu_brain.nii.gz')
def results(input_dir):
""" Gather results and write the MagTran JSON output file"""
cenc_dirs = cenc.directories(input_dir)
swi_input_dir = cenc_dirs['swi']['dirs']['input']
swi_01_register_dir = cenc_dirs['swi']['dirs']['register']
swi_results_dir = cenc_dirs['swi']['dirs']['results']
util.mkcd_dir([swi_results_dir], True)
result_files = [[
os.path.join(cenc_dirs['swi']['dirs']['register'],
'swi_Affine_nu__swi_m0_Warped.nii.gz'),
os.path.join(cenc_dirs['swi']['dirs']['results'],
'swi_Affine_nu__swi_m0.nii.gz')
],
[
os.path.join(cenc_dirs['swi']['dirs']['register'],
'swi_Affine_nu__swi_m1_Warped.nii.gz'),
os.path.join(cenc_dirs['swi']['dirs']['results'],
'swi_Affine_nu__swi_m1.nii.gz')
],
[
os.path.join(cenc_dirs['swi']['dirs']['results'],
'magtrans.json'),
os.path.join(cenc_dirs['swi']['dirs']['results'],
'magtrans.json')
],
[
os.path.join(cenc_dirs['swi']['dirs']['register'],
'swir.nii.gz'),
os.path.join(cenc_dirs['swi']['dirs']['results'],
'swir.nii.gz')
],
[
os.path.join(cenc_dirs['swi']['dirs']['input'],
'nu.nii.gz'),
os.path.join(cenc_dirs['swi']['dirs']['results'],
'nu.nii.gz')
],
[
os.path.join(cenc_dirs['swi']['dirs']['register'],
'swir.nii.gz'),
os.path.join(cenc_dirs['results']['dirs']['images'],
'swir.nii.gz')
]]
for ii in result_files:
util.force_hard_link(ii[0], ii[1])
return
def methods_01_register(input_dir, verbose=False):
# Register SWI images to nu.nii.gz
cenc_dirs = cenc.directories(input_dir)
swi_link_inputs(input_dir, cenc_dirs['swi']['dirs']['register'])
ants_register('swi_magnitude')
util.force_hard_link('swi_Affine_nu__swi_magnitude_Warped.nii.gz',
'swi_Affine_nu__swi_magnitude.nii.gz')
ants_apply_transform('swi')
ants_apply_transform('swi_phase')
return
def results( input_dir):
cenc_dirs = cenc.directories( input_dir)
util.mkcd_dir( [ cenc_dirs['wmlesions']['dirs']['results'] ], True)
# Link Files
link_result_files = [ [ os.path.join( cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_t2flair.nii.gz'),
os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_t2flair.nii.gz') ],
[ os.path.join( cenc_dirs['wmlesions']['dirs']['input'], 'nu.nii.gz'),
os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'nu.nii.gz') ],
[ os.path.join( cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_pmap.nii.gz'),
os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_pmap.nii.gz')],
[ os.path.join( cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions.json'),
os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions.json')],
[os.path.join(cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_labels.nii.gz'),
os.path.join(cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_labels.nii.gz')],
[os.path.join(cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_labels.csv'),
os.path.join(cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_labels.csv')],
[ os.path.join( cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_mask.nii.gz'),
os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_mask.nii.gz')],
[ os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_pmap.nii.gz'),
os.path.join( cenc_dirs['results']['dirs']['images'], 'wmlesions_lpa_pmap.nii.gz')],
[ os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_mask.nii.gz'),
os.path.join( cenc_dirs['results']['dirs']['labels'], 'wmlesions_lpa_mask.nii.gz')],
[ os.path.join( cenc_dirs['wmlesions']['dirs']['results'], 'wmlesions_lpa_labels.nii.gz'),
os.path.join( cenc_dirs['results']['dirs']['labels'], 'wmlesions_lpa_labels.nii.gz')
]
]
for ii in link_result_files:
util.force_hard_link( ii[0], ii[1])
def results(input_dir, verbose):
cenc_dirs = cenc.directories(input_dir)
cenc_freesurfer_dir = cenc_dirs['freesurfer']['mri']
util.mkcd_dir([
cenc_dirs['results']['dirs']['root'],
cenc_dirs['results']['dirs']['images'],
cenc_dirs['results']['dirs']['labels']
], True)
files_to_convert = [
os.path.join(cenc_freesurfer_dir, 'nu.mgz'),
os.path.join(cenc_freesurfer_dir, 'aseg.mgz'),
os.path.join(cenc_freesurfer_dir, 'brainmask.mgz'),
os.path.join(cenc_freesurfer_dir, 'aparc.a2009s+aseg.mgz'),
os.path.join(cenc_freesurfer_dir, 'wmparc.mgz')
]
# Check if files exist
if util.check_files(files_to_convert, True) == False:
sys.exit()
# Create link to directory
if not os.path.exists(cenc_dirs['freesurfer']['results']):
util.force_symbolic_link(cenc_dirs['freesurfer']['mri'],
cenc_dirs['freesurfer']['results'])
# TODO use input node to run this instead of a loop. The trick part is to have the files named correctly.
for ii in files_to_convert:
mc = fs.MRIConvert(in_file=ii,
out_file=os.path.join(
cenc_dirs['results']['dirs']['labels'],
str.replace(os.path.basename(ii), '.mgz',
'.nii.gz')),
out_type='niigz')
mc.run()
reorient = fsl.Reorient2Std(in_file=mc.inputs.out_file,
out_file=mc.inputs.out_file)
reorient.run()
# Link nu.nii.gz to results/native/images
result_files = [[
os.path.join(cenc_dirs['results']['dirs']['labels'], 'nu.nii.gz'),
os.path.join(cenc_dirs['results']['dirs']['images'], 'nu.nii.gz')
]]
for ii in result_files:
util.force_hard_link(ii[0], ii[1])
# Create final brain mask.
cenc.create_mask(
os.path.join(cenc_dirs['results']['dirs']['labels'],
'brainmask.nii.gz'),
os.path.join(cenc_dirs['results']['dirs']['labels'],
'aparc.a2009s+aseg.nii.gz'),
os.path.join(cenc_dirs['results']['dirs']['labels'], 'mask.nii.gz'))
# Create macroscopic labels
labels.extract(os.path.join(cenc_dirs['results']['dirs']['labels'],
'aseg.nii.gz'), [],
[10, 11, 12, 13, 17, 18, 49, 50, 51, 52, 53, 54],
os.path.join(cenc_dirs['results']['dirs']['labels'],
'gm.subcortical.nii.gz'),
merge=1)
labels.extract(os.path.join(cenc_dirs['results']['dirs']['labels'],
'aseg.nii.gz'), [], [3, 42],
os.path.join(cenc_dirs['results']['dirs']['labels'],
'gm.cerebral_cortex.nii.gz'),
merge=1)
labels.extract(os.path.join(cenc_dirs['results']['dirs']['labels'],
'aseg.nii.gz'), [], [8, 47],
os.path.join(cenc_dirs['results']['dirs']['labels'],
'gm.cerebellum.nii.gz'),
merge=1)
labels.extract(os.path.join(cenc_dirs['results']['dirs']['labels'],
'aseg.nii.gz'), [], [2, 41],
os.path.join(cenc_dirs['results']['dirs']['labels'],
'wm.cerebral.nii.gz'),
merge=1)
labels.extract(os.path.join(cenc_dirs['results']['dirs']['labels'],
'aseg.nii.gz'), [], [7, 46],
os.path.join(cenc_dirs['results']['dirs']['labels'],
'wm.cerebellum.nii.gz'),
merge=1)
labels.extract(os.path.join(cenc_dirs['results']['dirs']['labels'],
'aseg.nii.gz'), [], [4, 43],
os.path.join(cenc_dirs['results']['dirs']['labels'],
'ventricles.nii.gz'),
merge=1)
# Brain extraction nu.nii.gz
util.iw_subprocess([
'fslmaths',
os.path.join(cenc_dirs['results']['dirs']['images'], 'nu.nii.gz'),
'-mas',
os.path.join(cenc_dirs['results']['dirs']['labels'], 'mask.nii.gz'),
os.path.join(cenc_dirs['results']['dirs']['images'], 'nu_brain.nii.gz')
])
