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 methods_02_lpa(input_dir, verbose):
cenc_dirs = cenc.directories(input_dir)
wm_lesions_dir = cenc_dirs['wmlesions']['dirs']['root']
wm_lesions_lpa_dir = cenc_dirs['wmlesions']['dirs']['lpa']
util.mkcd_dir([cenc_dirs['wmlesions']['dirs']['lpa']], True)
util.copy_inputs([
os.path.join(cenc_dirs['wmlesions']['dirs']['register'],
't2flair_Affine_nu__t2flair_Warped.nii.gz')
], cenc_dirs['wmlesions']['dirs']['lpa'])
glob_files = glob.glob('*.gz')
for ii in glob_files:
os.system('gunzip ' + ii)
os.chmod(str.replace(ii, '.gz', ''),
stat.S_IRUSR | stat.S_IRGRP | stat.S_IWUSR | stat.S_IWGRP)
# Run Matlab
command = ['cenc_wmlesions_run.sh', cenc_dirs['wmlesions']['dirs']['lpa']]
util.iw_subprocess(command, verbose, verbose, False)
os.chdir(cenc_dirs['wmlesions']['dirs']['lpa'])
for ii in glob.glob('*.nii'):
os.system('gzip ' + ii)
os.chmod(str.replace(ii, '.nii', '.nii.gz'),
stat.S_IRUSR | stat.S_IRGRP | stat.S_IWUSR | stat.S_IWGRP)
def results( input_dir ):
""" Gather results and write the MagTran JSON output file"""
cenc_dirs = cenc.directories( input_dir )
mt_input_dir = cenc_dirs['mt']['dirs']['input']
mt_01_register_dir = cenc_dirs['mt']['dirs']['register']
mt_results_dir = cenc_dirs['mt']['dirs']['results']
util.mkcd_dir( [ mt_results_dir ], True)
result_files = [ [ os.path.join( cenc_dirs['mt']['dirs']['register'], 'mt_Affine_nu__mt_m0_Warped.nii.gz'),
os.path.join( cenc_dirs['mt']['dirs']['results'], 'mt_Affine_nu__mt_m0.nii.gz')],
[ os.path.join( cenc_dirs['mt']['dirs']['register'], 'mt_Affine_nu__mt_m1_Warped.nii.gz'),
os.path.join( cenc_dirs['mt']['dirs']['results'], 'mt_Affine_nu__mt_m1.nii.gz')],
[ os.path.join( cenc_dirs['mt']['dirs']['02-stats'], 'magtrans.json'),
os.path.join( cenc_dirs['mt']['dirs']['results'], 'magtrans.json') ],
[ os.path.join( cenc_dirs['mt']['dirs']['register'], 'mtr.nii.gz'),
os.path.join( cenc_dirs['mt']['dirs']['results'], 'mtr.nii.gz') ],
[ os.path.join( cenc_dirs['mt']['dirs']['input'], 'nu.nii.gz'),
os.path.join( cenc_dirs['mt']['dirs']['results'], 'nu.nii.gz') ],
[ os.path.join( cenc_dirs['mt']['dirs']['register'], 'mtr.nii.gz'),
os.path.join( cenc_dirs['results']['dirs']['images'], 'mtr.nii.gz') ]
]
for ii in result_files:
util.force_hard_link( ii[0], ii[1])
return
def mt_link_inputs( input_dir, link_to_dir, change_to_dir = True ):
cenc_dirs = cenc.directories( input_dir )
util.mkcd_dir( [ link_to_dir ], change_to_dir )
input_files = cenc_dirs['mt']['inputs']
label_files = cenc_dirs['mt']['labels']
util.link_inputs( input_files + label_files, link_to_dir )
def methods_02_stats(input_dir, verbose=False):
# Register MT images to nu.nii.gz
cenc_dirs = cenc.directories(input_dir)
util.mkcd_dir( [ cenc_dirs['mt']['dirs']['02-stats'] ], True)
methods_write_json_redcap_mt_instrument(input_dir, verbose)
return
def prepare( cenc_participant_dir ):
freesurfer_input_dir = os.path.join( cenc_participant_dir, 'freesurfer', 'input' )
util.mkcd_dir( [ freesurfer_input_dir ])
input_files = [ os.path.join( cenc_participant_dir, 'reorient', 't1w.nii.gz'),
os.path.join( cenc_participant_dir, 'reorient', 't2flair.nii.gz'),
os.path.join( cenc_participant_dir, 'reorient', 't2tse.nii.gz')
]
util.link_inputs( input_files, freesurfer_input_dir)
return
def prepare( input_dir ):
cenc_dirs = cenc.directories( input_dir )
util.mkcd_dir( [ cenc_dirs['freesurfer']['input'] ])
input_files = [ os.path.join( cenc_dirs['cenc']['reorient'], 't1w.nii.gz'),
os.path.join( cenc_dirs['cenc']['reorient'], 't2flair.nii.gz'),
os.path.join( cenc_dirs['cenc']['reorient'], 't2tse.nii.gz')
]
util.link_inputs( input_files, cenc_dirs['freesurfer']['input'] )
return
def results(cenc_participant_id, cenc_participant_dir, cenc_freesurfer_dir,cenc_results_dir, verbose):
util.mkcd_dir( [ cenc_results_dir ], True)
files_to_convert = [ os.path.join( cenc_freesurfer_dir, cenc_participant_id, 'mri', 'nu.mgz'),
os.path.join( cenc_freesurfer_dir, cenc_participant_id, 'mri', 'aseg.mgz'),
os.path.join( cenc_freesurfer_dir, cenc_participant_id, 'mri', 'brainmask.mgz'),
os.path.join( cenc_freesurfer_dir, cenc_participant_id, 'mri', 'aparc.a2009s+aseg.mgz'),
os.path.join( cenc_freesurfer_dir, cenc_participant_id, 'mri', 'wmparc.mgz')
]
# Check if files exist
print files_to_convert
if util.check_files(files_to_convert, True) == False:
sys.exit()
# Create link to directory
freesurfer_results_dir = os.path.abspath(os.path.join( cenc_participant_dir, 'freesurfer','results'))
if not os.path.exists(freesurfer_results_dir):
util.force_symbolic_link( os.path.join( cenc_freesurfer_dir, cenc_participant_id ), freesurfer_results_dir)
# TODO use input node to run this instead of a loop
mc = Node( fs.MRIConvert( out_type = 'niigz'
),
name="mri_convert"
)
mc.iterables = ( "in_file", files_to_convert )
reorient = Node( fsl.Reorient2Std(), name="reorient" )
workflow_convert = Workflow(name='cenc_freesurfer_nipype_workflow')
workflow_convert.base_dir = cenc_results_dir
workflow_convert.connect( [ (mc, reorient, [('out_file', 'in_file')] )]
)
workflow_convert.run()
# Create final brain mask. This takes forever. Speeding it up would be helpful.
cenc.create_mask( os.path.join( cenc_results_dir, 'brainmask.nii.gz'),
os.path.join( cenc_results_dir, 'aparc.a2009s+aseg.nii.gz'),
os.path.join( cenc_results_dir, 'mask.nii.gz')
)
def results(cenc_participant_id, cenc_participant_dir, cenc_freesurfer_dir,cenc_results_dir, verbose):
util.mkcd_dir( [ cenc_results_dir ], True)
files_to_convert = [ os.path.join( cenc_freesurfer_dir, cenc_participant_id, 'mri', 'nu.mgz'),
os.path.join( cenc_freesurfer_dir, cenc_participant_id, 'mri', 'aseg.mgz'),
os.path.join( cenc_freesurfer_dir, cenc_participant_id, 'mri', 'brainmask.mgz'),
os.path.join( cenc_freesurfer_dir, cenc_participant_id, 'mri', 'aparc.a2009s+aseg.mgz'),
os.path.join( cenc_freesurfer_dir, cenc_participant_id, 'mri', 'wmparc.mgz')
]
# Check if files exist
print files_to_convert
if util.check_files(files_to_convert, True) == False:
sys.exit()
# Create link to directory
freesurfer_results_dir = os.path.abspath(os.path.join( cenc_participant_dir, 'freesurfer','results'))
if not os.path.exists(freesurfer_results_dir):
util.force_symbolic_link( os.path.join( cenc_freesurfer_dir, cenc_participant_id ), freesurfer_results_dir)
# 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_results_dir, 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()
# Create final brain mask.
cenc.create_mask( os.path.join( cenc_results_dir, 'brainmask.nii.gz'),
os.path.join( cenc_results_dir, 'aparc.a2009s+aseg.nii.gz'),
os.path.join( cenc_results_dir, 'mask.nii.gz')
)
# Extract labels for Further processing
cenc_results_labels_dir = os.path.join(cenc_results_dir, 'labels')
util.mkcd_dir( cenc_results_labels_dir, 'labels') )
def methods_00_input(config, verbose):
""" Renames inputs from configureation file to standard naming convention"""
if verbose:
print
print(config['config']['dirs'])
print
print(config['methods']['input'])
print
util.mkcd_dir([config['methods']['input']['dir']], True)
input_output_pairs = zip(config['methods']['input']['inputs'],
config['methods']['input']['outputs'])
for ii in input_output_pairs:
os.link(ii[0], ii[1])
def methods_01_register(input_dir, verbose):
cenc_dirs = cenc.directories(input_dir)
wm_lesions_dir = cenc_dirs['wmlesions']['dirs']['root']
wm_lesions_lpa_dir = cenc_dirs['wmlesions']['dirs']['lpa']
# Register
util.mkcd_dir([cenc_dirs['wmlesions']['dirs']['register']], True)
files = [
os.path.join(cenc_dirs['wmlesions']['dirs']['input'], 'nu.nii.gz'),
os.path.join(cenc_dirs['wmlesions']['dirs']['input'],
't2flair.nii.gz'),
os.path.join(cenc_dirs['results']['dirs']['labels'], 'mask.nii.gz')
]
util.link_inputs(files, cenc_dirs['wmlesions']['dirs']['register'])
ants_register('t2flair')
def prepare(input_dir):
cenc_dirs = cenc.directories(input_dir)
wm_lesions_dir = cenc_dirs['wmlesions']['dirs']['root']
wm_lesions_input_dir = cenc_dirs['wmlesions']['dirs']['input']
wm_lesions_lpa_dir = cenc_dirs['wmlesions']['dirs']['lpa']
# Create Input Directory if it doesn't exist and link files
files = [
os.path.abspath(
os.path.join(cenc_dirs['results']['dirs']['images'], 'nu.nii.gz')),
os.path.abspath(
os.path.join(cenc_dirs['results']['dirs']['labels'],
'mask.nii.gz')),
os.path.abspath(
os.path.join(cenc_dirs['cenc']['reorient'], 't2flair.nii.gz'))
]
util.mkcd_dir(os.path.join(wm_lesions_input_dir))
util.link_inputs(files, wm_lesions_input_dir)
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
util.iw_subprocess( ['cenc_aseg_labels.sh'], True, True, False)
def methods_03_stats(input_dir, verbose=False, min_lesion_volume=10):
cenc_dirs = cenc.directories(input_dir)
wm_lesions_dir = cenc_dirs['wmlesions']['dirs']['root']
wm_lesions_lpa_dir = cenc_dirs['wmlesions']['dirs']['lpa']
util.mkcd_dir([cenc_dirs['wmlesions']['dirs']['stats']], True)
wm_lesions_stats_filename = os.path.join(
cenc_dirs['wmlesions']['dirs']['stats'], 'wmlesions_lpa_labels.csv')
# Create labels file from LPA probability map
iw_labels_label.create(
os.path.join(cenc_dirs['wmlesions']['dirs']['lpa'],
'ples_lpa_mt2flair_Affine_nu__t2flair_Warped.nii.gz'),
os.path.join(cenc_dirs['wmlesions']['dirs']['stats'],
'wmlesions_lpa_labels.nii.gz'))
# Measure statistics of labels
iw_labels_stats.measure(
os.path.join(cenc_dirs['wmlesions']['dirs']['stats'],
'wmlesions_lpa_labels.nii.gz'),
None,
False, ['volume_mm3'],
wm_lesions_stats_filename,
limits_volume_voxels=[min_lesion_volume, numpy.inf],
limits_bb_volume_voxels=[0, numpy.inf],
limits_fill_factor=[0, 1],
sort='volume_mm3',
verbose=verbose,
verbose_nlines=20)
# Keep labels greater than 10 mm^3. Limit is set above
iw_labels_keep.keep(
os.path.join(cenc_dirs['wmlesions']['dirs']['stats'],
'wmlesions_lpa_labels.nii.gz'), [],
wm_lesions_stats_filename,
os.path.join(cenc_dirs['wmlesions']['dirs']['stats'],
'wmlesions_lpa_labels.nii.gz'))
# 1)
# 2) Create a WM Lesions mask
# 3)
command = [[
'fslmaths',
os.path.join(cenc_dirs['wmlesions']['dirs']['stats'],
'wmlesions_lpa_labels.nii.gz'), '-bin', '-mul',
os.path.join(cenc_dirs['wmlesions']['dirs']['lpa'],
'ples_lpa_mt2flair_Affine_nu__t2flair_Warped.nii.gz'),
'-mas',
os.path.join(cenc_dirs['wmlesions']['dirs']['input'], 'mask.nii.gz'),
os.path.join(cenc_dirs['wmlesions']['dirs']['stats'],
'wmlesions_lpa_pmap.nii.gz')
],
[
'fslmaths',
os.path.join(cenc_dirs['wmlesions']['dirs']['stats'],
'wmlesions_lpa_labels.nii.gz'), '-bin',
os.path.join(cenc_dirs['wmlesions']['dirs']['stats'],
'wmlesions_lpa_mask.nii.gz')
],
[
'fslmaths',
os.path.join(cenc_dirs['wmlesions']['dirs']['lpa'],
'mt2flair_Affine_nu__t2flair_Warped.nii.gz'),
'-mas',
os.path.join(cenc_dirs['wmlesions']['dirs']['input'],
'mask.nii.gz'),
os.path.join(cenc_dirs['wmlesions']['dirs']['stats'],
'wmlesions_lpa_t2flair.nii.gz')
]]
for ii in command:
util.iw_subprocess(ii, verbose, verbose, False)
# Write out JSON file with RedCap Instrument
methods_write_json_redcap_instrument(input_dir, wm_lesions_stats_filename,
verbose)
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])
affine_out_iras_to_wras = stage1_output_files[0]
affine_out_wras_to_wlps = stage1_output_files[1]
affine_out_wlps_to_wctf = stage1_output_files[3]
fiducials_out_iras = stage1_output_files[2]
fiducials_out_wlps = stage1_output_files[4]
fiducials_out_wctf = stage1_output_files[5]
print stage1_output_files
if inArgs.run and (1 in inArgs.run_stage):
util.print_stage("Entering Stage 1 - Creating matrices", inArgs.verbose)
util.verify_inputs(stage1_input_files, inArgs.verbose)
util.mkcd_dir( stage1_directory )
util.link_inputs( stage1_input_files, stage1_directory)
#
# Save ITK affine matrix
#
if inArgs.verbose:
print
print "Image affine RAS image to RAS world matrix"
print img_affine_matrix_ras
print
util.save_itk_affine_matrix( img_affine_matrix_ras, affine_out_iras_to_wras, inArgs.verbose )
tarball_filename = inArgs.tarball
else:
tarball_filename = id + '_fmri.tar.gz'
if os.path.isfile(os.path.join(out_dir, tarball_filename)):
sys.exit('fMRI tarball already exists for ' + id + '.')
# Create Output Directory if it doesn't exist
files = [
os.path.abspath(os.path.join(dicom_dir, 'dcmConvertAll.cfg')),
os.path.abspath(os.path.join(dicom_dir, 'dcmConvert_cenc.cfg')),
os.path.abspath(os.path.join(nifti_dir, 'rest.nii.gz'))
]
util.mkcd_dir(out_dir)
util.link_inputs(files, out_dir)
files_to_be_tarred = glob.glob('*')
# Create TarBall
tarball = tarfile.open(tarball_filename, 'w:gz')
for f in files_to_be_tarred:
tarball.add(f)
tarball.close()
# Clean Directory
participant_dir = os.path.abspath(os.path.join(inArgs.cenc_dir, id))
reorient_dir = util.path_relative_to(participant_dir, inArgs.reorient_dir)
wm_lesions_dir = util.path_relative_to(participant_dir, inArgs.out_dir)
wm_lesions_input_dir = os.path.join(wm_lesions_dir, 'input')
wm_lesions_lpa_dir = os.path.join(wm_lesions_dir, '01-lst_lpa')
wm_lesions_lga_dir = os.path.join(wm_lesions_dir, '02-lst_lga')
# Create Output Directory if it doesn't exist
files = [
os.path.abspath(os.path.join(reorient_dir, 't1w.nii.gz')),
os.path.abspath(os.path.join(reorient_dir, 't2flair.nii.gz'))
]
util.mkcd_dir(os.path.join(wm_lesions_input_dir))
util.link_inputs(files, wm_lesions_input_dir)
#
util.mkcd_dir(os.path.join(wm_lesions_lpa_dir), False)
util.mkcd_dir(os.path.join(wm_lesions_lga_dir), True)
util.copy_inputs(files, wm_lesions_lga_dir)
for ii in glob.glob('*.gz'):
os.system('gunzip ' + ii)
util.link_inputs(glob.glob('*.nii'), wm_lesions_lpa_dir)
]
stage0_output_files = stage0_output_files + native_to_template + template_to_native
if os.path.exists(reference_template):
reference_template = util.path_relative_to( stage0_directory, 'reference_template.nii.gz' )
stage0_output_files = stage0_output_files + [ reference_template ]
if inArgs.run and (0 in inArgs.run_stage):
util.print_stage('Entering Stage 0 - Renaming input files to common working names', inArgs.verbose)
util.verify_inputs(stage0_input_files, inArgs.verbose)
util.mkcd_dir( stage0_directory )
for ii in range(0,len(stage0_input_files)):
if os.path.exists( stage0_output_files[ii] ):
os.unlink( stage0_output_files[ii] )
os.link(stage0_input_files[ii], stage0_output_files[ii] )
util.verify_outputs(stage0_output_files, inArgs.verbose)
#
# Stage 1
#
stage1_directory = stage_directory[1];
