def generate_subject_files(subj, fmri_paths, dest_dir, mod_to_update):
import clinica.iotools.converters.adni_to_bids.adni_utils as adni_utils
import clinica.iotools.bids_utils as bids_utils
from clinica.utils.stream import cprint
import subprocess
import os
import shutil
from os import path
from glob import glob
sess_list = fmri_paths[(fmri_paths['Subject_ID'] == subj)]['VISCODE'].values
alpha_id = adni_utils.remove_space_and_symbols(subj)
bids_id = 'sub-ADNI' + alpha_id
# For each session available, create the folder if doesn't exist and convert the files
for ses in sess_list:
with counter.get_lock():
counter.value += 1
cprint('[FLAIR] Processing subject ' + str(subj)
+ ' - session ' + ses + ', ' + str(counter.value)
+ ' / ' + str(len(fmri_paths)))
ses_bids = adni_utils.viscode_to_session(ses)
bids_ses_id = 'ses-' + ses_bids
bids_file_name = bids_id + '_ses-' + ses_bids
ses_path = path.join(dest_dir, bids_id, bids_ses_id)
# If the fmri already exist
existing_fmri = glob(path.join(ses_path, 'func', '*_bold*'))
# if mod_to_add:
# if len(existing_fmri) > 0:
# print 'Fmri already existing. Skipped.'
# continue
if mod_to_update and len(existing_fmri) > 0:
# print 'Removing the old fmri folder...'
os.remove(existing_fmri[0])
if not os.path.exists(ses_path):
if not os.path.exists(path.join(dest_dir, bids_id)):
os.mkdir(path.join(dest_dir, bids_id))
os.mkdir(path.join(dest_dir, bids_id, bids_ses_id))
fmri_info = fmri_paths[(fmri_paths['Subject_ID'] == subj) & (fmri_paths['VISCODE'] == ses)]
if not fmri_info['Path'].values[0] == '':
if type(fmri_info['Path'].values[0]) != float:
if not os.path.exists(path.join(ses_path, 'func')):
os.mkdir(path.join(ses_path, 'func'))
fmri_path = fmri_info['Path'].values[0]
dcm_to_convert = adni_utils.check_two_dcm_folder(fmri_path,
dest_dir,
fmri_info['IMAGEUID'].values[0])
if not os.path.isfile(os.path.join(ses_path, 'func', bids_file_name + '_task-rest_bold.nii.gz')):
bids_utils.convert_fmri(dcm_to_convert, path.join(ses_path, 'func'), bids_file_name)
else:
cprint("Images already converted")
# Delete the temporary folder used for copying fmri with 2 subjects inside the DICOM folder
adni_utils.remove_tmp_dmc_folder(dest_dir, fmri_info['IMAGEUID'].values[0])
def fmri_paths_to_bids(dest_dir, fmri_paths, mod_to_update=False):
"""
Convert the fmri extracted from the fmri_paths to BIDS
Args:
dest_dir: path to the input directory
fmri_paths: path to the BIDS directory
mod_to_add: if True add the fmri only where is missing
mod_to_update: if True overwrite (or create if is missing) all the existing fmri
"""
from clinica.iotools.converters.adni_to_bids import adni_utils
from os import path
import os
import shutil
from glob import glob
import clinica.iotools.bids_utils as bids
from clinica.utils.stream import cprint
subjs_list = fmri_paths['Subject_ID'].drop_duplicates().values
for i in range(0, len(subjs_list)):
# print 'Converting fmri for subject', subjs_list[i]
sess_list = fmri_paths[(
fmri_paths['Subject_ID'] == subjs_list[i])]['VISCODE'].values
alpha_id = adni_utils.remove_space_and_symbols(subjs_list[i])
bids_id = 'sub-ADNI' + alpha_id
# For each session available, create the folder if doesn't exist and convert the files
for ses in sess_list:
ses_bids = adni_utils.viscode_to_session(ses)
bids_ses_id = 'ses-' + ses_bids
bids_file_name = bids_id + '_ses-' + ses_bids
ses_path = path.join(dest_dir, bids_id, bids_ses_id)
# If the fmri already exist
existing_fmri = glob(path.join(ses_path, 'func', '*_bold*'))
# if mod_to_add:
# if len(existing_fmri) > 0:
# print 'Fmri already existing. Skipped.'
# continue
if mod_to_update and len(existing_fmri) > 0:
# print 'Removing the old fmri folder...'
os.remove(existing_fmri[0])
if not os.path.exists(ses_path):
if not os.path.exists(path.join(dest_dir, bids_id)):
os.mkdir(path.join(dest_dir, bids_id))
os.mkdir(path.join(dest_dir, bids_id, bids_ses_id))
fmri_info = fmri_paths[(fmri_paths['Subject_ID'] == subjs_list[i])
& (fmri_paths['VISCODE'] == ses)]
if not fmri_info['Path'].empty:
if type(fmri_info['Path'].values[0]) != float:
if not os.path.exists(path.join(ses_path, 'func')):
os.mkdir(path.join(ses_path, 'func'))
fmri_path = fmri_info['Path'].values[0]
dcm_to_convert = adni_utils.check_two_dcm_folder(
fmri_path, dest_dir, fmri_info['IMAGEUID'].values[0])
cprint(
os.path.join(ses_path, 'func', bids_file_name +
'_task-rest_bold.nii.gz'))
if not os.path.isfile(
os.path.join(
ses_path, 'func',
bids_file_name + '_task-rest_bold.nii.gz')):
bids.convert_fmri(dcm_to_convert,
path.join(ses_path, 'func'),
bids_file_name)
else:
cprint("Images already converted")
# Delete the temporary folder used for copying fmri with 2 subjects inside the DICOM folder
if os.path.exists(path.join(dest_dir, 'tmp_dcm_folder')):
shutil.rmtree(path.join(dest_dir, 'tmp_dcm_folder'))
def fdg_pet_paths_to_bids(images, bids_dir, dcm2niix="dcm2niix", dcm2nii="dcm2nii", mod_to_update=False):
"""
Args:
images:
bids_dir:
dcm2niix:
dcm2nii:
mod_to_update:
Returns:
"""
from clinica.iotools.converters.adni_to_bids import adni_utils
import os
from os import path
import glob
from clinica.utils.stream import cprint
count = 0
total = images.shape[0]
for row in images.iterrows():
image = row[1]
subject = image.Subject_ID
count += 1
if image.Path == '':
cprint('No path specified for ' + image.Subject_ID + ' in session ' + image.VISCODE)
continue
cprint('Processing subject ' + str(subject) + ' - session ' + image.VISCODE + ', ' + str(count) + ' / ' + str(total))
session = adni_utils.viscode_to_session(image.VISCODE)
image_path = image.Path
# ADDED lines
# ------------------
image_id = image.Image_ID
# If the original image is a DICOM, check if contains two DICOM inside the same folder
if image.Is_Dicom:
image_path = adni_utils.check_two_dcm_folder(image_path, bids_dir, image_id)
# ------------------
bids_subj = subject.replace('_', '')
output_path = path.join(bids_dir, 'sub-ADNI' + bids_subj + '/ses-' + session + '/pet')
output_filename = 'sub-ADNI' + bids_subj + '_ses-' + session + '_task-rest_acq-fdg_pet'
# ADDED lines
# ------------------
# If updated mode is selected, check if an old FDG image is existing and remove it
existing_fdg = glob.glob(path.join(output_path, output_filename + '*'))
if mod_to_update and len(existing_fdg) > 0:
cprint('Removing the old FDG image...')
for fdg in existing_fdg:
os.remove(fdg)
# ------------------
try:
os.makedirs(output_path)
except OSError:
if not path.isdir(output_path):
raise
if not image.Is_Dicom:
adni_utils.center_nifti_origin(image_path, path.join(output_path, output_filename + '.nii.gz'))
else:
command = dcm2niix + ' -b n -z n -o ' + output_path + ' -f ' + output_filename + ' ' + image_path
os.system(command)
nifti_file = path.join(output_path, output_filename + '.nii')
output_image = nifti_file + '.gz'
# Check if conversion worked (output file exists?)
if not path.isfile(nifti_file):
command = dcm2nii + ' -a n -d n -e n -i y -g n -p n -m n -r n -x n -o ' + output_path + ' ' + image_path
os.system(command)
nifti_file = path.join(output_path, subject.replace('_', '') + '.nii')
output_image = path.join(output_path, output_filename + '.nii.gz')
if not path.isfile(nifti_file):
cprint('DICOM to NIFTI conversion error for ' + image_path)
continue
adni_utils.center_nifti_origin(nifti_file, output_image)
os.remove(nifti_file)
adni_utils.remove_tmp_dmc_folder(bids_dir)
def create_file(image, modality, total, bids_dir, mod_to_update):
import subprocess
from colorama import Fore
from clinica.utils.stream import cprint
from clinica.iotools.converters.adni_to_bids import adni_utils
from clinica.iotools.utils.data_handling import center_nifti_origin
from numpy import nan
import os
from os import path
from glob import glob
modality_specific = {
't1': {
'output_path': 'anat',
'output_filename': '_T1w'
},
'fdg': {
'output_path': 'pet',
'output_filename': '_task-rest_acq-fdg_pet'
},
'pib': {
'output_path': 'pet',
'output_filename': '_task-rest_acq-pib_pet'
},
'av45': {
'output_path': 'pet',
'output_filename': '_task-rest_acq-av45_pet'
},
'fbb': {
'output_path': 'pet',
'output_filename': '_task-rest_acq-fbb_pet'
},
'tau': {
'output_path': 'pet',
'output_filename': '_task-rest_acq-tau_pet'
}
}
global counter
with counter.get_lock():
counter.value += 1
subject = image.Subject_ID
if modality == 'av45_fbb':
modality = image.Tracer.lower()
if image.Path == '':
cprint(Fore.RED + '[' + modality.upper() + '] No path specified for ' +
image.Subject_ID + ' in session ' + image.VISCODE + ' ' +
str(counter.value) + ' / ' + str(total) + Fore.RESET)
return nan
cprint('[' + modality.upper() + '] Processing subject ' + str(subject) +
' - session ' + image.VISCODE + ', ' + str(counter.value) + ' / ' +
str(total))
session = adni_utils.viscode_to_session(image.VISCODE)
image_path = image.Path
image_id = image.Image_ID
# If the original image is a DICOM, check if contains two DICOM
# inside the same folder
if image.Is_Dicom:
image_path = adni_utils.check_two_dcm_folder(image_path, bids_dir,
image_id)
bids_subj = subject.replace('_', '')
output_path = path.join(bids_dir, 'sub-ADNI' + bids_subj, 'ses-' + session,
modality_specific[modality]['output_path'])
output_filename = 'sub-ADNI' + bids_subj + '_ses-' + session + modality_specific[
modality]['output_filename']
# If updated mode is selected, check if an old image is existing and remove it
existing_im = glob(path.join(output_path, output_filename + '*'))
if mod_to_update and len(existing_im) > 0:
print('Removing the old image...')
for im in existing_im:
os.remove(im)
try:
os.makedirs(output_path)
except OSError:
# Folder already created with previous instance
pass
if image.Is_Dicom:
command = 'dcm2niix -b n -z n -o ' + output_path + ' -f ' + output_filename + ' ' + image_path
subprocess.run(command,
shell=True,
stderr=subprocess.DEVNULL,
stdout=subprocess.DEVNULL)
nifti_file = path.join(output_path, output_filename + '.nii')
output_image = nifti_file + '.gz'
# Check if conversion worked (output file exists?)
if not path.isfile(nifti_file):
cprint('\tConversion with dcm2niix failed, trying with dcm2nii')
command = 'dcm2nii -a n -d n -e n -i y -g n -p n -m n -r n -x n -o ' + output_path + ' ' + image_path
subprocess.run(command,
shell=True,
stdout=subprocess.DEVNULL,
stderr=subprocess.DEVNULL)
nifti_file = path.join(output_path,
subject.replace('_', '') + '.nii')
output_image = path.join(output_path, output_filename + '.nii.gz')
if not path.isfile(nifti_file):
cprint('DICOM to NIFTI conversion error for ' + image_path)
return nan
center_nifti_origin(nifti_file, output_image)
os.remove(nifti_file)
else:
output_image = path.join(output_path, output_filename + '.nii.gz')
center_nifti_origin(image_path, output_image)
if output_image is None:
cprint(
"Error: For subject %s in session%s an error occurred recentering Nifti image:%s"
% (subject, session, image_path))
# Check if there is still the folder tmp_dcm_folder and remove it
adni_utils.remove_tmp_dmc_folder(bids_dir, image_id)
return output_image
def av45_pet_paths_to_bids(images, bids_dir, dcm2niix="dcm2niix", dcm2nii="dcm2nii", mod_to_update=False):
"""
Read the paths generated by the method compute_av45_pet and convert the original images to the BIDS standard
Args:
images: the dataframe returned by the method compute_av45_pet
bids_dir: path to the BIDS directory
dcm2niix: path to the dcm2niix tool (not useful anymore)
dcm2nii: path to the dcm2nii tool (not useful anymore
"""
import os
import glob
from numpy import nan
from clinica.iotools.converters.adni_to_bids import adni_utils
from clinica.utils.stream import cprint
count = 0
total = images.shape[0]
for row in images.iterrows():
image = row[1]
subject = image.Subject_ID
count += 1
if image.Path is nan:
cprint('No path specified for ' + image.Subject_ID + ' in session ' + image.VISCODE)
continue
cprint('Processing subject ' + str(subject) + ' - session ' + image.VISCODE + ', ' + str(count) + ' / ' + str(total))
session = adni_utils.viscode_to_session(image.VISCODE)
image_path = image.Path
# ADDED lines
# ------------------
image_id = image.Image_ID
# If the original image is a DICOM, check if contains two DICOM inside the same folder
if image.Is_Dicom:
image_path = adni_utils.check_two_dcm_folder(image_path, bids_dir, image_id)
# ------------------
bids_subj = subject.replace('_', '')
output_path = os.path.join(bids_dir, 'sub-ADNI' + bids_subj +'/ses-' + session + '/pet')
output_filename = 'sub-ADNI' + bids_subj + '_ses-' + session + '_task-rest_acq-av45_pet'
# ADDED lines
# ------------------
# If updated mode is selected, check if an old AV45 image is existing and remove it
existing_av45 = glob.glob(os.path.join(output_path, output_filename + '*'))
if mod_to_update and len(existing_av45) > 0:
cprint('Removing the old AV45 image...')
for av45 in existing_av45:
os.remove(av45)
# ------------------
try:
os.makedirs(output_path)
except OSError:
if not os.path.isdir(output_path):
raise
if not image.Is_Dicom:
adni_utils.center_nifti_origin(image_path, os.path.join(output_path, output_filename + '.nii.gz'))
else:
command = dcm2niix + ' -b n -z n -o ' + output_path + ' -f ' + output_filename + ' ' + image_path
os.system(command)
nifti_file = os.path.join(output_path, output_filename + '.nii')
output_image = nifti_file + '.gz'
# Check if conversion worked (output file exists?)
if not os.path.isfile(nifti_file):
cprint('Conversion with dcm2niix failed, trying with dcm2nii')
command = dcm2nii + ' -a n -d n -e n -i y -g n -p n -m n -r n -x n -o ' + output_path + ' ' + image_path
os.system(command)
nifti_file = os.path.join(output_path, subject.replace('_', '') + '.nii')
output_image = os.path.join(output_path, output_filename + '.nii.gz')
if not os.path.isfile(nifti_file):
cprint('DICOM to NIFTI conversion error for ' + image_path)
continue
adni_utils.center_nifti_origin(nifti_file, output_image)
os.remove(nifti_file)
adni_utils.remove_tmp_dmc_folder(bids_dir)
def generate_subject_files(subj, images, dest_dir, mod_to_update):
import clinica.iotools.bids_utils as bids
import clinica.iotools.converters.adni_to_bids.adni_utils as adni_utils
from clinica.utils.stream import cprint
import subprocess
import os
import shutil
from os import path
from glob import glob
global counter
alpha_id = bids.remove_space_and_symbols(subj)
bids_id = 'sub-ADNI' + alpha_id
# Extract the list of sessions available from the dwi paths files, removing the duplicates
sess_list = images[(images['Subject_ID'] == subj)]['VISCODE'].unique()
if not os.path.exists(path.join(dest_dir, bids_id)):
os.mkdir(path.join(dest_dir, bids_id))
# For each session available, create the folder if doesn't exist and convert the files
for ses in sess_list:
with counter.get_lock():
counter.value += 1
cprint('[DWI] Processing subject ' + str(subj) + ' - session ' + ses +
', ' + str(counter.value) + ' / ' + str(len(images)))
ses_bids = adni_utils.viscode_to_session(ses)
bids_ses_id = 'ses-' + ses_bids
bids_file_name = bids_id + '_ses-' + ses_bids
ses_path = path.join(dest_dir, bids_id, bids_ses_id)
if mod_to_update:
if os.path.exists(path.join(ses_path, 'dwi')):
shutil.rmtree(path.join(ses_path, 'dwi'))
if not os.path.exists(ses_path):
os.mkdir(ses_path)
dwi_info = images[(images['Subject_ID'] == subj)
& (images['VISCODE'] == ses)]
# For the same subject, same session there could be multiple dwi with different acq label
for j in range(len(dwi_info)):
dwi_subj = dwi_info.iloc[j]
if type(dwi_subj['Path']) != float and dwi_subj['Path'] != '':
if not os.path.exists(path.join(ses_path, 'dwi')):
os.mkdir(path.join(ses_path, 'dwi'))
dwi_path = dwi_subj['Path']
bids_name = bids_file_name + '_acq-axial_dwi'
bids_dest_dir = path.join(ses_path, 'dwi')
if not os.path.exists(bids_dest_dir):
os.mkdir(dest_dir)
command = 'dcm2niix -b n -z y -o ' + bids_dest_dir + ' -f ' + bids_name + ' ' + dwi_path
subprocess.run(command,
shell=True,
stdout=subprocess.DEVNULL,
stderr=subprocess.DEVNULL)
# Removing ADC images
adc_image = path.join(bids_dest_dir, bids_name + '_ADC.nii.gz')
if os.path.exists(adc_image):
os.remove(adc_image)
# If dcm2niix didn't work use dcm2nii
# print path.join(dest_dir, bids_name + '.nii.gz')
if not os.path.exists(
path.join(bids_dest_dir, bids_name + '.nii.gz')
) or not os.path.exists(
path.join(bids_dest_dir, bids_name + '.bvec')
or not os.path.exists(
path.join(bids_dest_dir, bids_name + '.bval'))):
cprint(
'\tConversion with dcm2niix failed, trying with dcm2nii'
)
# Find all the files eventually created by dcm2niix and remove them
dwi_dcm2niix = glob(
path.join(bids_dest_dir, bids_name + '*'))
for d in dwi_dcm2niix:
# print 'Removing the old', d
os.remove(d)
command = 'dcm2nii -a n -d n -e n -i y -g y -p n -m n -r n -x n -o %s %s' \
% (bids_dest_dir, dwi_path)
subprocess.run(command,
shell=True,
stdout=subprocess.DEVNULL,
stderr=subprocess.DEVNULL)
nii_file = path.join(bids_dest_dir,
subj.replace('_', '') + '.nii.gz')
bvec_file = path.join(bids_dest_dir,
subj.replace('_', '') + '.bvec')
bval_file = path.join(bids_dest_dir,
subj.replace('_', '') + '.bval')
if os.path.exists(bvec_file) and os.path.exists(bval_file):
os.rename(
bvec_file,
path.join(bids_dest_dir, bids_name + '.bvec'))
os.rename(
bval_file,
path.join(bids_dest_dir, bids_name + '.bval'))
else:
cprint(
'WARNING: bvec and bval not generated by dcm2nii' +
' for subject ' + subj + ' and session ' + ses)
if os.path.exists(nii_file):
os.rename(
nii_file,
path.join(bids_dest_dir, bids_name + '.nii.gz'))
else:
cprint('WARNING: CONVERSION FAILED...' +
' for subject ' + subj + ' and session ' + ses)
def dwi_paths_to_bids(images, dest_dir, mod_to_update=False):
"""
Convert DWI images
Args:
images: dataframe returned by the method compute_dwi_paths
dest_dir: path to the destination directory
mod_to_update: if is true and an image is already existing it will overwrite the old version
"""
import clinica.iotools.bids_utils as bids
import clinica.iotools.converters.adni_to_bids.adni_utils as adni_utils
from os import path
import os
from glob import glob
import shutil
from clinica.utils.stream import cprint
subjs_list = images['Subject_ID'].unique()
for i in range(0, len(subjs_list)):
# print '--Converting dwi for subject ', subjs_list[i], '--'
alpha_id = bids.remove_space_and_symbols(subjs_list[i])
bids_id = 'sub-ADNI' + alpha_id
# Extract the list of sessions available from the dwi paths files, removing the duplicates
sess_list = images[(
images['Subject_ID'] == subjs_list[i])]['VISCODE'].unique()
if not os.path.exists(path.join(dest_dir, bids_id)):
os.mkdir(path.join(dest_dir, bids_id))
# For each session available, create the folder if doesn't exist and convert the files
for ses in sess_list:
ses_bids = adni_utils.viscode_to_session(ses)
bids_ses_id = 'ses-' + ses_bids
bids_file_name = bids_id + '_ses-' + ses_bids
ses_path = path.join(dest_dir, bids_id, bids_ses_id)
if mod_to_update:
if os.path.exists(path.join(ses_path, 'dwi')):
shutil.rmtree(path.join(ses_path, 'dwi'))
if not os.path.exists(ses_path):
os.mkdir(ses_path)
dwi_info = images[(images['Subject_ID'] == subjs_list[i])
& (images['VISCODE'] == ses)]
# For the same subject, same session there could be multiple dwi with different acq label
for j in range(0, len(dwi_info)):
dwi_subj = dwi_info.iloc[j]
# TODO For now in CLINICA we ignore Enhanced DWI.
if dwi_subj['Enhanced']:
continue
if type(dwi_subj['Path']) != float and dwi_subj['Path'] != '':
if not os.path.exists(path.join(ses_path, 'dwi')):
os.mkdir(path.join(ses_path, 'dwi'))
dwi_path = dwi_subj['Path']
bids_name = bids_file_name + '_acq-' + (
'axialEnhanced'
if dwi_subj['Enhanced'] else 'axial') + '_dwi'
# bids.dcm_to_nii(dwi_path, path.join(ses_path, 'dwi'), bids_name)
bids_dest_dir = path.join(ses_path, 'dwi')
if not os.path.exists(bids_dest_dir):
os.mkdir(dest_dir)
os.system('dcm2niix -b n -z y -o ' + bids_dest_dir +
' -f ' + bids_name + ' ' + dwi_path)
# If dcm2niix didn't work use dcm2nii
# print path.join(dest_dir, bids_name + '.nii.gz')
if not os.path.exists(
path.join(bids_dest_dir, bids_name + '.nii.gz')
) or not os.path.exists(
path.join(bids_dest_dir, bids_name + '.bvec')
or not os.path.exists(
path.join(bids_dest_dir,
bids_name + '.bval'))):
cprint(
'\nConversion with dcm2niix failed, trying with dcm2nii'
)
# Find all the files eventually created by dcm2niix and remove them
dwi_dcm2niix = glob(
path.join(bids_dest_dir, bids_name + '*'))
for d in dwi_dcm2niix:
# print 'Removing the old', d
os.remove(d)
os.system(
'dcm2nii -a n -d n -e n -i y -g y -p n -m n -r n -x n -o '
+ bids_dest_dir + ' ' + dwi_path)
nii_file = path.join(
bids_dest_dir,
subjs_list[i].replace('_', '') + '.nii.gz')
bvec_file = path.join(
bids_dest_dir,
subjs_list[i].replace('_', '') + '.bvec')
bval_file = path.join(
bids_dest_dir,
subjs_list[i].replace('_', '') + '.bval')
if os.path.exists(bvec_file) and os.path.exists(
bval_file):
os.rename(
bvec_file,
path.join(bids_dest_dir, bids_name + '.bvec'))
os.rename(
bval_file,
path.join(bids_dest_dir, bids_name + '.bval'))
else:
cprint(
'WARNING: bvec and bval not generated by dcm2nii'
)
if os.path.exists(nii_file):
os.rename(
nii_file,
path.join(bids_dest_dir,
bids_name + '.nii.gz'))
else:
cprint('WARNING: CONVERSION FAILED...')
def t1_paths_to_bids(images,
bids_dir,
dcm2niix="dcm2niix",
dcm2nii="dcm2nii",
mod_to_update=False):
import os
from os import path
from numpy import nan
from clinica.iotools.converters.adni_to_bids import adni_utils
from glob import glob
from clinica.utils.stream import cprint
count = 0
total = images.shape[0]
for row in images.iterrows():
image = row[1]
subject = image.Subject_ID
count += 1
if image.Path is nan:
cprint('No path specified for ' + image.Subject_ID +
' in session ' + image.VISCODE)
continue
cprint('Processing subject ' + str(subject) + ' - session ' +
image.VISCODE + ', ' + str(count) + ' / ' + str(total))
session = adni_utils.viscode_to_session(image.VISCODE)
image_path = image.Path
# ADDED lines
# ------------------
image_id = image.Image_ID
# If the original image is a DICOM, check if contains two DICOM inside the same folder
if image.Is_Dicom:
image_path = adni_utils.check_two_dcm_folder(
image_path, bids_dir, image_id)
# ------------------
bids_subj = subject.replace('_', '')
output_path = path.join(bids_dir, 'sub-ADNI' + bids_subj,
'ses-' + session, 'anat')
output_filename = 'sub-ADNI' + bids_subj + '_ses-' + session + '_T1w'
# ADDED lines
# ------------------
# If updated mode is selected, check if an old T1 image is existing and remove it
existing_t1 = glob(path.join(output_path, output_filename + '*'))
if mod_to_update and len(existing_t1) > 0:
print 'Removing the old T1 image...'
for t1 in existing_t1:
os.remove(t1)
# ------------------
try:
os.makedirs(output_path)
except OSError:
if not path.isdir(output_path):
raise
if image.Is_Dicom:
command = dcm2niix + ' -b n -z n -o ' + output_path + ' -f ' + output_filename + ' ' + image_path
os.system(command)
nifti_file = path.join(output_path, output_filename + '.nii')
output_image = nifti_file + '.gz'
# Check if conversion worked (output file exists?)
if not path.isfile(nifti_file):
cprint('Conversion with dcm2niix failed, trying with dcm2nii')
command = dcm2nii + ' -a n -d n -e n -i y -g n -p n -m n -r n -x n -o ' + output_path + ' ' + image_path
os.system(command)
nifti_file = path.join(output_path,
subject.replace('_', '') + '.nii')
output_image = path.join(output_path,
output_filename + '.nii.gz')
if not path.isfile(nifti_file):
# TODO - LOG THIS
cprint('DICOM to NIFTI conversion error for ' + image_path)
continue
adni_utils.center_nifti_origin(nifti_file, output_image)
os.remove(nifti_file)
else:
output_image = path.join(output_path, output_filename + '.nii.gz')
adni_utils.center_nifti_origin(image_path, output_image)
# Check if there is still the folder tmp_dcm_folder and remove it
adni_utils.remove_tmp_dmc_folder(bids_dir)
def generate_subject_files(subj, images, dest_dir, mod_to_update):
import clinica.iotools.bids_utils as bids
import clinica.iotools.converters.adni_to_bids.adni_utils as adni_utils
from clinica.utils.stream import cprint
import subprocess
import os
import shutil
from os import path
from glob import glob
alpha_id = bids.remove_space_and_symbols(subj)
bids_id = 'sub-ADNI' + alpha_id
# Extract the list of sessions available from the flair paths files, removing the duplicates
sess_list = images[(images['Subject_ID'] == subj)]['VISCODE'].unique()
if not os.path.exists(path.join(dest_dir, bids_id)):
os.mkdir(path.join(dest_dir, bids_id))
# For each session available, create the folder if doesn't exist and convert the files
for ses in sess_list:
with counter.get_lock():
counter.value += 1
cprint('[FLAIR] Processing subject ' + str(subj) + ' - session ' +
ses + ', ' + str(counter.value) + ' / ' + str(len(images)))
ses_bids = adni_utils.viscode_to_session(ses)
bids_ses_id = 'ses-' + ses_bids
bids_file_name = bids_id + '_ses-' + ses_bids
ses_path = path.join(dest_dir, bids_id, bids_ses_id)
if mod_to_update:
if os.path.exists(path.join(ses_path, 'FLAIR')):
shutil.rmtree(path.join(ses_path, 'FLAIR'))
if not os.path.exists(ses_path):
os.mkdir(ses_path)
flair_info = images[(images['Subject_ID'] == subj)
& (images['VISCODE'] == ses)]
# For the same subject, same session there could be multiple flar with different acq label
for j in range(len(flair_info)):
flair_subj = flair_info.iloc[j]
# TODO For now in CLINICA we ignore Enhanced FLAIR.
if flair_subj['Enhanced']:
continue
if type(flair_subj['Path']) != float and flair_subj['Path'] != '':
if not os.path.exists(path.join(ses_path, 'FLAIR')):
os.mkdir(path.join(ses_path, 'FLAIR'))
flair_path = flair_subj['Path']
bids_name = bids_file_name + '_FLAIR'
# bids.dcm_to_nii(dwi_path, path.join(ses_path, 'dwi'), bids_name)
bids_dest_dir = path.join(ses_path, 'FLAIR')
if not os.path.exists(bids_dest_dir):
os.mkdir(dest_dir)
command = 'dcm2niix -b y -z y -o ' + bids_dest_dir + ' -f ' + bids_name + ' ' + flair_path
subprocess.run(command,
shell=True,
stderr=subprocess.DEVNULL,
stdout=subprocess.DEVNULL)
# If dcm2niix didn't work use dcm2nii
# print path.join(dest_dir, bids_name + '.nii.gz')
if not os.path.exists(
path.join(bids_dest_dir, bids_name + '.nii.gz')):
cprint(
'\tConversion with dcm2niix failed, trying with dcm2nii'
)
# Find all the files eventually created by dcm2niix and remove them
flair_dcm2niix = glob(
path.join(bids_dest_dir, bids_name + '*'))
for d in flair_dcm2niix:
os.remove(d)
command = 'dcm2nii -a n -d n -e n -i y -g y -p n -m n -r n -x n -o ' + bids_dest_dir + ' ' + flair_path
subprocess.run(command,
shell=True,
stdout=subprocess.DEVNULL,
stderr=subprocess.DEVNULL)
nii_file = path.join(bids_dest_dir,
subj.replace('_', '') + '.nii.gz')
if os.path.exists(nii_file):
os.rename(
nii_file,
path.join(bids_dest_dir, bids_name + '.nii.gz'))
else:
cprint('WARNING: CONVERSION FAILED...')
