def dcm_to_nifti(dicom_dir, nifti_dir, split=True, tool_used='dcm2niix'):
for patient in os.listdir(dicom_dir):
path_dicom = os.path.join(dicom_dir, patient)
path_nifti = os.path.join(nifti_dir, patient)
# make subfolder for each patient
if not os.path.exists(path_nifti):
os.makedirs(path_nifti)
if split == False:
if tool_used == 'dcm2niix':
converter = Dcm2niix()
converter.inputs.source_dir = path_dicom
converter.inputs.compression = 5
converter.inputs.merge_imgs = True
converter.inputs.out_filename = '%d'
converter.inputs.output_dir = path_nifti
converter.run()
elif tool_used == 'dcm2nii':
converter = Dcm2nii()
converter.inputs.source_dir = path_dicom
converter.inputs.gzip_output = True
converter.inputs.output_dir = path_nifti
converter.run()
else:
raise Warning("tool used does not exist, please enter dcm2nii or dcm2niix")
else:
for s in os.listdir(path_dicom):
if tool_used == 'dcm2niix':
converter = Dcm2niix()
converter.inputs.source_dir = path_dicom + '/' + s
converter.inputs.compression = 5
converter.inputs.merge_imgs = True
converter.inputs.out_filename = 'x_%d'
converter.inputs.output_dir = path_nifti
converter.run()
elif tool_used == 'dcm2nii':
converter = Dcm2nii()
converter.inputs.source_dir = path_dicom + '/' + s
converter.inputs.gzip_output = True
converter.inputs.output_dir = path_nifti
converter.run()
else:
raise Warning("tool used does not exist, please enter dcm2nii or dcm2niix")
#dcm_to_nifti(dicom_split_dir, nifti_dir, True, 'dcm2nii')
#dcm_to_nifti(dicom_split_dir, nifti_dir, True, 'dcm2niix')
def process_data_folder(self, analysis, options):
# since the conversion takes a while, change cursor to hourglass
QApplication.setOverrideCursor(QtCore.Qt.WaitCursor)
if analysis == 'Dcm2nii':
process = Dcm2niix()
else:
process = []
for opt, value in options.items():
process.inputs.__setattr__(opt, value)
if not os.path.isdir(os.path.join(self.baseDir,
analysis.capitalize())):
os.mkdir(os.path.join(self.baseDir, analysis.capitalize()))
process.inputs.source_dir = self.baseDir
process.inputs.output_dir = os.path.join(self.baseDir,
analysis.capitalize())
try:
out = process.run()
except RuntimeError as err:
self.logFile += str(err)
else:
self.logFile += out.runtime.stdout
# update GUI
self.scanDirectory(self.baseDir)
self.updateGUI(0)
self.updateFileNavigator(['.nii'])
QApplication.restoreOverrideCursor()
self.postProcessDisplayUpdate()
def test_dcm2niix_dwi(tmpdir):
tmpdir.chdir()
try:
datadir = fetch_data(tmpdir.strpath, 'Siemens_Sag_DTI_20160825_145811')
except IncompleteResultsError as exc:
pytest.skip("Failed to fetch test data: %s" % str(exc))
def assert_dwi(eg, bids):
"Some assertions we will make"
assert eg.outputs.converted_files
assert eg.outputs.bvals
assert eg.outputs.bvecs
outputs = [y for x, y in eg.outputs.get().items()]
if bids:
# ensure all outputs are of equal lengths
assert len(set(map(len, outputs))) == 1
else:
assert not eg.outputs.bids
dcm = Dcm2niix()
dcm.inputs.source_dir = datadir
dcm.inputs.out_filename = '%u%z'
assert_dwi(dcm.run(), True)
# now run specifying output directory and removing BIDS option
outdir = tmpdir.mkdir('conversion').strpath
dcm.inputs.output_dir = outdir
dcm.inputs.bids_format = False
assert_dwi(dcm.run(), False)
def run_dcm2niix(bids_name, bids_modality, bvecs_from_scanner_file, mapping_file, nii_file, nii_output_dir,
out_filename, par_file, public_output, task):
'''
Converts one par/rec pair to nii.gz.
Adds scan duration and dcm2niix & docker container version to bids file.
'''
abs_par_file = os.path.abspath(par_file)
abs_rec_file = os.path.splitext(abs_par_file)[0] + ".rec"
assert os.path.exists(abs_rec_file), "REC file does not exist %s" % abs_rec_file
# run converter
converter = Dcm2niix()
converter.inputs.source_names = [abs_par_file]
converter.inputs.bids_format = True
converter.inputs.compress = 'i'
converter.inputs.has_private = True
converter.inputs.out_filename = out_filename
converter.inputs.output_dir = nii_output_dir
print("XXXXXXX running dcm2niix command")
print(converter.cmdline)
converter_results = converter.run()
bids_file = converter_results.outputs.bids
# add additional information to json
## scan duration
add_additional_bids_parameters_from_par(abs_par_file, bids_file, {"scan_duration": "ScanDurationSec",
"technique": "PulseSequenceType",
"protocol_name": "PulseSequenceDetails"})
add_flip_angle_from_par(abs_par_file, bids_file)
add_total_readout_time_from_par(abs_par_file, bids_file)
## lhab_pipelines
add_info_to_json(bids_file, {"LhabPipelinesVersion": lhab_pipelines.__version__})
## task
if task:
add_info_to_json(bids_file, {"TaskName": task})
## time
add_info_to_json(bids_file, {"ConversionTimestamp": str(dt.datetime.now())})
if not public_output:
# write par 2 nii mapping file only for private use
with open(mapping_file, "a") as fi:
fi.write("%s %s\n" % (abs_par_file, nii_file))
else:
# remove info file generated by dcm2niix
os.remove(os.path.join(nii_output_dir, out_filename + '.txt'))
# rotate bvecs and add angulation to json for dwi
if (bids_name == "dwi") & (bids_modality != "fmap"):
dwi_treat_bvecs(abs_par_file, bids_file, bvecs_from_scanner_file, nii_output_dir, par_file)
# remove _dwi_ADC.nii.gz file created by dcm2niix
adc_file = glob(os.path.join(nii_output_dir, "*_dwi_ADC.nii.gz"))[0]
os.remove(adc_file)
return bids_file, converter_results
def zip2nii(zipfname, outdir):
with tempfile.TemporaryDirectory() as tmpdir:
with tempfile.TemporaryDirectory() as outtmpdir:
shutil.copy(zipfname, tmpdir)
_, fname = os.path.split(zipfname)
fname = os.path.join(tmpdir, fname)
zip_ref = zipfile.ZipFile(fname, 'r')
zip_ref.extractall(tmpdir)
zip_ref.close()
os.remove(fname)
converter = Dcm2niix()
converter.inputs.source_dir = tmpdir
converter.inputs.compression = 5
converter.inputs.output_dir = outtmpdir
converter.inputs.out_filename = '%p_%t_%s'
print(converter.cmdline)
#'dcm2niix -b y -z y -5 -x n -t n -m n -o ds005 -s n -v n tmpdir'
converter.run()
dirlist = glob.glob(outtmpdir + '/' + '*.gz')
for file_name in dirlist:
if (os.path.isfile(file_name)):
shutil.copy(file_name, outdir)
def nipype_convert(item_dicoms, prefix, with_prov, bids, tmpdir):
""" """
import nipype
if with_prov:
from nipype import config
config.enable_provenance()
from nipype import Node
from nipype.interfaces.dcm2nii import Dcm2niix
item_dicoms = list(map(op.abspath, item_dicoms)) # absolute paths
dicom_dir = op.dirname(item_dicoms[0]) if item_dicoms else None
convertnode = Node(Dcm2niix(), name='convert')
convertnode.base_dir = tmpdir
convertnode.inputs.source_dir = dicom_dir
convertnode.inputs.out_filename = op.basename(op.dirname(prefix))
if nipype.__version__.split('.')[0] == '0':
# deprecated since 1.0, might be needed(?) before
convertnode.inputs.terminal_output = 'allatonce'
else:
convertnode.terminal_output = 'allatonce'
convertnode.inputs.bids_format = bids
eg = convertnode.run()
# prov information
prov_file = prefix + '_prov.ttl' if with_prov else None
if prov_file:
safe_copyfile(
op.join(convertnode.base_dir, convertnode.name, 'provenance.ttl'),
prov_file)
return eg, prov_file
def dcm_nii():
g = os.walk("/project/data/dicom/gp_1/")
for path, dir_list, file_list in g:
print('*' * 10)
print(path)
print(dir_list)
print(file_list)
if len(dir_list) == 0 and len(file_list) > 0:
print(path)
# print(len(file_list))
converter = Dcm2niix()
converter.inputs.bids_format = False
converter.inputs.compress = 'n'
converter.inputs.merge_imgs = True
print(path)
if path.split('/')[-1] == 'CT':
temp = 'CT'
else:
temp = 'MR'
converter.inputs.out_filename = temp
outpath = path.split('New')[0] + 'New_nii' + path.split('New')[-1]
if not os.path.exists(outpath):
os.makedirs(outpath)
converter.inputs.output_dir = outpath
converter.inputs.source_dir = path
converter.run()
def test_dcm2niix_dti(fetch_data, tmpdir):
tmpdir.chdir()
datadir = tmpdir.mkdir('data').strpath
dicoms = fetch_data(datadir, 'Siemens_Sag_DTI_20160825_145811')
def assert_dti(res):
"Some assertions we will make"
assert res.outputs.converted_files
assert res.outputs.bvals
assert res.outputs.bvecs
outputs = [y for x, y in res.outputs.get().items()]
if res.inputs.get('bids_format'):
# ensure all outputs are of equal lengths
assert len(set(map(len, outputs))) == 1
else:
assert not res.outputs.bids
dcm = Dcm2niix()
dcm.inputs.source_dir = dicoms
dcm.inputs.out_filename = '%u%z'
assert_dti(dcm.run())
# now run specifying output directory and removing BIDS option
outdir = tmpdir.mkdir('conversion').strpath
dcm.inputs.output_dir = outdir
dcm.inputs.bids_format = False
assert_dti(dcm.run())
def dcm2niix_wf(wf_name='dcm2niix'):
"""Run dcm2niix over one folder with DICOM files.
Nipype Inputs
-------------
dcm2niix.in_dcmdir: traits.Dir
path to the DICOM images folder.
Nipype Outputs
--------------
dcm2niix.bids: (a list of items which are an existing file name)
dcm2niix.bvals: (a list of items which are an existing file name)
dcm2niix.bvecs: (a list of items which are an existing file name)
dcm2niix.converted_files: (a list of items which are an existing file name)
Returns
-------
wf: nipype Workflow
"""
# Create the workflow object
wf = pe.Workflow(name=wf_name)
# specify input and output fields
in_fields = [
"in_dcmdir",
]
out_fields = ["bids", "bvals", "bvecs", "converted_files"]
# input node
dcm2niix_input = setup_node(IdentityInterface(fields=in_fields,
mandatory_inputs=True),
name="dcm2niix_input")
# T1 preprocessing nodes
dcm2niix = setup_node(Dcm2niix(), name="dcm2niix")
# output node
dcm2niix_output = setup_node(IdentityInterface(fields=out_fields),
name="dcm2niix_output")
# Connect the nodes
wf.connect([
# input
(dcm2niix_input, dcm2niix, [
("in_dcmdir", "source_dir"),
]),
# output
(dcm2niix, dcm2niix_output, [
("bids", "bids"),
("bvals", "bvals"),
("bvecs", "bvecs"),
("converted_files", "converted_files"),
]),
])
return wf
def nipype_convert(item_dicoms,
prefix,
with_prov,
bids_options,
tmpdir,
dcmconfig=None):
"""
Converts DICOMs grouped from heuristic using Nipype's Dcm2niix interface.
Parameters
----------
item_dicoms : List
DICOM files to convert
prefix : String
Heuristic output path
with_prov : Bool
Store provenance information
bids_options : List or None
If not None then output BIDS sidecar JSONs
List may contain bids specific options
tmpdir : Directory
Conversion working directory
dcmconfig : File (optional)
JSON file used for additional Dcm2niix configuration
"""
import nipype
if with_prov:
from nipype import config
config.enable_provenance()
from nipype import Node
from nipype.interfaces.dcm2nii import Dcm2niix
item_dicoms = list(map(op.abspath, item_dicoms)) # absolute paths
fromfile = dcmconfig if dcmconfig else None
if fromfile:
lgr.info("Using custom config file %s", fromfile)
convertnode = Node(Dcm2niix(from_file=fromfile), name='convert')
convertnode.base_dir = tmpdir
convertnode.inputs.source_names = item_dicoms
convertnode.inputs.out_filename = prefix
if nipype.__version__.split('.')[0] == '0':
# deprecated since 1.0, might be needed(?) before
convertnode.inputs.terminal_output = 'allatonce'
else:
convertnode.terminal_output = 'allatonce'
convertnode.inputs.bids_format = bids_options is not None
eg = convertnode.run()
# prov information
prov_file = prefix + '_prov.ttl' if with_prov else None
if prov_file:
safe_copyfile(
op.join(convertnode.base_dir, convertnode.name, 'provenance.ttl'),
prov_file)
return eg, prov_file
def dicom_converter(out_dir=None, source_dir=None, filename=None):
converter = Dcm2niix()
converter.inputs.bids_format = True
converter.inputs.anon_bids = True
converter.inputs.compress = 'y'
converter.inputs.output_dir = out_dir
converter.inputs.source_dir = source_dir
converter.inputs.out_filename = filename
converter.run()
def my_dcm2niix(folder):
# convert dcm series to nii.gz and .json using nipype and dcm2niix
from nipype.interfaces.dcm2nii import Dcm2niix
converter = Dcm2niix()
converter.inputs.source_dir = folder
converter.inputs.compression = 5
converter.inputs.output_dir = folder
converter.inputs.out_filename = '%i_%4s_%d'
converter.cmdline
converted_files = converter.run()
return converted_files
def convert_to_nifti(studydir):
logging.info("Converting to nifti")
dicomdir = pjoin(studydir, "scans")
niftidir = pjoin(studydir, "nifti")
os.mkdir(niftidir)
dcm = Dcm2niix()
dcm.ignore_exception = True
dcm.inputs.source_dir = dicomdir
dcm.inputs.output_dir = niftidir
dcm.inputs.out_filename = "%d_%s"
dcm.run()
def dicom_convert(self):
if not getattr(self,"_dicom_convert",None):
#self._dicom_convert = pe.Node(name="dicom_convert", interface=Dcm2nii())
#self._dicom_convert = pe.Node(name="dicom_convert", interface=HCDcm2nii())
self._dicom_convert = pe.Node(name="dicom_convert", interface=Dcm2niix())
self._dicom_convert.inputs.out_filename="%p_s%s"
#self._dicom_convert.inputs.convert_all_pars = True
#self._dicom_convert.inputs.gzip_output = False
#self._dicom_convert.inputs.reorient = False
#self._dicom_convert.inputs.reorient_and_crop = False
#self._dicom_convert.inputs.events_in_filename=True
#self._dicom_convert.inputs.protocol_in_filename=True
#self._dicom_convert.inputs.date_in_filename= False
return self._dicom_convert
def convert_to_nifti(studydir):
# convert both to nifti and to separated dicom dirs
dicomdir = pjoin(studydir, "dicom")
niftidir = pjoin(studydir, "nifti")
dicomdirsdir = pjoin(studydir, "dicomdirs")
os.mkdir(niftidir)
os.mkdir(dicomdirsdir)
subprocess.call(
["/usr/local/bin/dcm2niix", "-r", "y", "-o", dicomdirsdir, dicomdir])
dcm = Dcm2niix()
dcm.inputs.source_dir = dicomdir
dcm.inputs.output_dir = niftidir
dcm.inputs.out_filename = "%d_%s"
dcm.run()
def convert (source_dir, output_dir, subName, session): # this is a function that takes input directory, output directory and subject name and then converts everything accordingly
try:
os.makedirs(os.path.join(output_dir, subName, session))
except:
print ("folder already there")
# try:
# os.makedirs(os.path.join(output_dir, subName, ))
# except:
# print("Folder Exist")
converter = Dcm2niix()
converter.inputs.source_dir = source_dir
converter.inputs.compression = 7
converter.inputs.output_dir = os.path.join(output_dir, subName, session)
converter.inputs.out_filename = subName + 'seriesNo' '_' + '%2s' + '%p'
converter.run()
def convert_to_nifti(studydir, newdir):
niftidir = str(studydir) + "_nifti"
os.mkdir(niftidir)
dcm = Dcm2niix()
dcm.inputs.source_dir = studydir
dcm.inputs.output_dir = niftidir
dcm.inputs.out_filename = "%d_%s"
dcm.run()
shutil.rmtree(studydir)
newold = newdir.with_suffix(".old")
if os.path.exists(newdir):
if os.path.exists(newold):
shutil.rmtree(newold)
os.rename(newdir, newold)
os.rename(niftidir, newdir)
def convert_dcm(scan_key):
""" convert dicom with dcm2niix """
chdir(scan_key)
ZipFile('dicomdata.zip').extractall()
converter = Dcm2niix()
converter.inputs.source_dir = './dicomdata/DICOM/'
converter.inputs.output_dir = '.'
converter.inputs.ignore_deriv = True
converter.inputs.single_file = True
converter.inputs.out_filename = "%d"
converter.run()
rmtree('dicomdata')
system('rm *.json *.zip [DEFMS]* T2*a.nii.gz Q*[1-5].nii.gz')
return converter.cmdline
def nipype_convert(item_dicoms, prefix, with_prov, bids, tmpdir):
""" """
if with_prov:
from nipype import config
config.enable_provenance()
from nipype import Node
from nipype.interfaces.dcm2nii import Dcm2niix
item_dicoms = list(map(op.abspath, item_dicoms)) # absolute paths
convertnode = Node(Dcm2niix(), name='convert')
convertnode.base_dir = tmpdir
convertnode.inputs.source_names = item_dicoms
convertnode.inputs.out_filename = op.basename(op.dirname(prefix))
convertnode.inputs.bids_format = bids
convertnode.inputs.anon_bids = False
return convertnode.run()
def go(self):
# since the conversion takes a while, change cursor to hourglass
QApplication.setOverrideCursor(QtCore.Qt.WaitCursor)
dcm_node = pe.MapNode(interface=Dcm2niix(),
name='dcmnode',
iterfield=['source_dir'])
options = dict()
options['anon_bids'] = self.chk_anon.isChecked()
options['merge_imgs'] = self.chk_3D.isChecked()
options['compression'] = self.comp.currentIndex() + 1
if self.chk_GZ.isChecked():
options['compress'] = 'y'
out_format = '.nii.gz'
else:
options['compress'] = 'n'
out_format = '.nii'
for opt, value in options.items():
dcm_node.inputs.__setattr__(opt, value)
# get selected files
# since dcm2niix uses directories to convert files we will get the containing directory as input to the script
# instead of a list of file names
in_dirs = [
os.path.split(row.in_file.text())[0] for row in self.dcm_rows
]
dcm_node.inputs.output_dir = self.dir_dic['temp_dir']
dcm_node.inputs.source_dir = in_dirs
dcm_node.run()
# rename and move files into appropriate bids folders
self.move_and_rename(dcm_node.result.outputs.bids,
dcm_node.result.outputs.bvals,
dcm_node.result.outputs.bvecs,
dcm_node.result.outputs.converted_files,
self.process_out_files(), out_format)
QApplication.restoreOverrideCursor()
self.parentWidget.post_process_update()
def convert_nii(path="/home/alisher/Documents/data/umc/РДЦ/ПАТОЛОГИЯ",
new_path='/home/alisher/Documents/data/umc/Patology',
tag='converted'):
assert os.path.exists(path)
create_direct(new_path)
damaged_files = []
for folder in os.listdir(path):
patient_path = f'{path}/{folder}'
patient_number = os.listdir(patient_path)[0]
patient_dicom = f'{patient_path}/{patient_number}'
subject_path = f'{new_path}/{folder}'
converted_path = f'{subject_path}/{tag}'
create_direct(subject_path)
create_direct(converted_path)
if not len(os.listdir(converted_path)) == 0:
logger.info(f"Already converted {folder}")
continue
converter = Dcm2niix()
converter.inputs.compression = 5
# ignore derived, localizer and 2D images
converter.inputs.ignore_deriv = True
converter.inputs.source_dir = patient_dicom
converter.inputs.output_dir = converted_path
# run converter
logger.info(f"Started converting for {folder}")
try:
converter.run()
except:
logger.info(f"Something went wrong with {folder}")
damaged_files.append(folder)
logger.info(f"Completed converting for {folder}")
logger.info(f"Finished converting {len(os.listdir(path))} subjects")
logger.info("*" * 30)
logger.info(f"Damaged_files: {damaged_files}")
def dcm_to_nifti(dicom_dir, nifti_dir, split=True, tool_used='dcm2niix'):
for patient in os.listdir(dicom_dir):
path_dicom = os.path.join(dicom_dir, patient)
path_nifti = os.path.join(nifti_dir, patient)
# make subfolder for each patient
if not os.path.exists(path_nifti):
os.makedirs(path_nifti)
if not split:
if tool_used == 'dcm2niix':
converter = Dcm2niix()
converter.inputs.source_dir = path_dicom
converter.inputs.compression = 5
converter.inputs.merge_imgs = True
converter.inputs.out_filename = '%d'
converter.inputs.output_dir = path_nifti
converter.run()
elif tool_used == 'dcm2nii':
converter = Dcm2nii()
converter.inputs.source_dir = path_dicom
converter.inputs.gzip_output = True
converter.inputs.output_dir = path_nifti
converter.run()
else:
raise Warning("tool used does not exist, please enter dcm2nii or dcm2niix")
else:
for s in os.listdir(path_dicom):
if tool_used == 'dcm2niix':
try:
subprocess.call('/home/harryzhang/toolbox/dcm2niix/console/dcm2niix -m y -5 -f %%d -o %s %s' %
(path_nifti, path_dicom + '/'+s), shell=True)
except:
pass
elif tool_used == 'dcm2nii':
converter = Dcm2nii()
converter.inputs.source_dir = path_dicom + '/' + s
converter.inputs.gzip_output = True
converter.inputs.output_dir = path_nifti
converter.run()
else:
raise Warning("tool used does not exist, please enter dcm2nii or dcm2niix")
def dcmToniix(dst):
for root, dirs, files in os.walk(dst):
if len(files) == 0:
continue
sourceList = []
for file in files:
if '.dcm' in file:
sourceList.append(os.path.join(root, file))
print('Converting files in : ' + root + ' to .nii')
converter = Dcm2niix()
#print(sourceList)
converter.inputs.source_names = sourceList
converter.inputs.compression = 5
#print('root is ', root)
converter.inputs.output_dir = root
#print('\n\n\nconverter is :', converter.cmdline)
#converter.run() # this does not yet work due to some unicode error ?? No idea why
#print('Converting files in : '+root+ ' to .nii')
os.system('echo "' + converter.cmdline + '">>' + dst + '/runNiix.log')
runNiix = converter.cmdline + ' >> ' + dst + '/runNiix.log'
os.system(runNiix) # use this code .. this works
def convert(path):
'''
Converts .dcms to .nii.gz
Input:
path: (path) Path to folder containing DICOMS
'''
dirs = path.split('/')
if dirs[-1] == 'anat':
filename = dirs[-2]+'_T1w'
print(filename)
elif dirs[-1] =='func':
filename = dirs[-2]+'_task-rest_bold'
print(filename)
converter = Dcm2niix()
converter.inputs.source_dir = path
converter.inputs.output_dir = path
converter.inputs.out_filename = filename
converter.run()
print("Completed conversion: {}".format(path))
return
def convert(items, anonymizer=None, symlink=True, converter=None):
prov_files = []
tmpdir = mkdtemp()
for item in items:
if isinstance(item[1], (list, tuple)):
outtypes = item[1]
else:
outtypes = [item[1]]
prefix = item[0]
print('Converting %s' % prefix)
dirname = os.path.dirname(prefix + '.ext')
print(dirname)
if not os.path.exists(dirname):
os.makedirs(dirname)
for outtype in outtypes:
print(outtype)
if outtype == 'dicom':
dicomdir = prefix + '_dicom'
if os.path.exists(dicomdir):
shutil.rmtree(dicomdir)
os.mkdir(dicomdir)
for filename in item[2]:
outfile = os.path.join(dicomdir,
os.path.split(filename)[1])
if not os.path.islink(outfile):
if symlink:
os.symlink(filename, outfile)
else:
os.link(filename, outfile)
elif outtype in ['nii', 'nii.gz']:
outname = prefix + '.' + outtype
scaninfo = prefix + '_scaninfo.json'
if not os.path.exists(outname):
from nipype import config
config.enable_provenance()
from nipype import Function, Node
from nipype.interfaces.base import isdefined
print converter
if converter == 'mri_convert':
from nipype.interfaces.freesurfer.preprocess import MRIConvert
convertnode = Node(MRIConvert(), name='convert')
convertnode.base_dir = tmpdir
if outtype == 'nii.gz':
convertnode.inputs.out_type = 'niigz'
convertnode.inputs.in_file = item[2][0]
convertnode.inputs.out_file = outname
#cmd = 'mri_convert %s %s' % (item[2][0], outname)
#print(cmd)
#os.system(cmd)
res = convertnode.run()
elif converter == 'dcm2nii':
from nipype.interfaces.dcm2nii import Dcm2niix
convertnode = Node(Dcm2niix(), name='convert')
convertnode.base_dir = tmpdir
convertnode.inputs.source_names = item[2]
res = convertnode.run()
if isinstance(res.outputs.converted_files, list):
print(
"Cannot convert dicom files - series likely has multiple orientations: ",
item[2])
continue
else:
shutil.copyfile(res.outputs.converted_files,
outname)
if isdefined(res.outputs.bvecs):
outname_bvecs = prefix + '.bvecs'
outname_bvals = prefix + '.bvals'
shutil.copyfile(res.outputs.bvecs, outname_bvecs)
shutil.copyfile(res.outputs.bvals, outname_bvals)
prov_file = prefix + '_prov.ttl'
shutil.copyfile(
os.path.join(convertnode.base_dir, convertnode.name,
'provenance.ttl'), prov_file)
prov_files.append(prov_file)
embedfunc = Node(Function(input_names=[
'dcmfiles', 'niftifile', 'infofile', 'force'
],
output_names=['outfile', 'meta'],
function=embed_nifti),
name='embedder')
embedfunc.inputs.dcmfiles = item[2]
embedfunc.inputs.niftifile = outname
embedfunc.inputs.infofile = scaninfo
embedfunc.inputs.force = True
embedfunc.base_dir = tmpdir
res = embedfunc.run()
#g = res.provenance.rdf()
#g.parse(prov_file,
# format='turtle')
#g.serialize(prov_file, format='turtle')
#out_file, meta_dict = embed_nifti(item[2], outname, force=True)
os.chmod(outname, 0440)
os.chmod(scaninfo, 0440)
os.chmod(prov_file, 0440)
shutil.rmtree(tmpdir)
def run_pipeline(write_dir,
smri_data,
realign,
slicetiming,
datasink,
fmri_preprocess,
data_type=None,
**template_dict):
"""This function runs pipeline"""
write_dir = write_dir + '/' + template_dict[
'output_zip_dir'] # Store outputs in this directory for zipping the directory
error_log = dict() # dict for storing error log
print('fmri pipeline is running...')
each_sub=smri_data
try:
# Extract subject id and name of nifti file
if data_type == 'bids':
write_dir = write_dir + '/' + template_dict[
'output_zip_dir'] # Store outputs in this directory for zipping the directory
sub_id = 'sub-' + each_sub.subject
session_id = getattr(each_sub, 'session', None)
if session_id is not None:
session = 'ses-' + getattr(each_sub, 'session', None)
else:
session = ''
nii_output = ((each_sub.filename).split('/')[-1]).split('.gz')[0]
n1_img = nib.load(each_sub.filename)
if data_type == 'nifti':
sub_id = template_dict['subject']
session = template_dict['session']
nii_output = ((each_sub).split('/')[-1]).split('.gz')[0]
n1_img = nib.load(each_sub)
if data_type == 'dicoms':
sub_id = template_dict['subject']
session = template_dict['session']
fmri_out = os.path.join(write_dir, sub_id, session, 'func')
os.makedirs(fmri_out, exist_ok=True)
## This code runs the dicom to nifti conversion here
from nipype.interfaces.dcm2nii import Dcm2niix
dcm_nii_convert = Dcm2niix()
dcm_nii_convert.inputs.source_dir = each_sub
dcm_nii_convert.inputs.output_dir = fmri_out
with stdchannel_redirected(sys.stderr, os.devnull):
dcm_nii_convert.run()
with stdchannel_redirected(sys.stderr, os.devnull):
n1_img = nib.load(glob.glob(os.path.join(fmri_out, '*.nii*'))[0])
nii_output = ((glob.glob(os.path.join(fmri_out, '*.nii*'))[0]).split('/')[-1]).split('.gz')[0]
# Directory in which fmri outputs will be written
fmri_out = os.path.join(write_dir, sub_id, session, 'func')
# Create output dir for sub_id
os.makedirs(fmri_out, exist_ok=True)
if n1_img:
"""
Save nifti file from input data into output directory only if data_type !=dicoms because the dcm_nii_convert in the previous
step saves the nifti file to output directory
"""
nib.save(n1_img, os.path.join(fmri_out, nii_output))
#os.remove(glob.glob(os.path.join(fmri_out, '*.gz'))[0])
# Create fmri_spm12 dir under the specific sub-id/func
os.makedirs(
os.path.join(fmri_out, template_dict['fmri_output_dirname']),
exist_ok=True)
nifti_file = glob.glob(os.path.join(fmri_out, '*.nii'))[0]
# run reorientation node and pass to realign
try:
with stdchannel_redirected(sys.stderr, os.devnull):
convert_and_run_reorient_script(nifti_file)
except:
pass
# Edit realign node inputs
realign.node.inputs.in_files = nifti_file
# realign.node.inputs.out_file = fmri_out + "/" + template_dict['fmri_output_dirname'] + "/Re.nii"
# realign.node.run()
if template_dict['slicetime_ref_slice'] is not None:slicetiming.node.inputs.ref_slice=template_dict['slicetime_ref_slice']
if template_dict['num_slices'] is not None:slicetiming.node.inputs.num_slices=template_dict['num_slices']
if template_dict['repetition_time'] is not None:TR=template_dict['repetition_time']
if template_dict['acquisition_order'] is not None:acq_order=template_dict['acquisition_order']
# Edit Slicetiming node inputs
TR = n1_img.header.get_zooms()[-1]
num_slices = n1_img.shape[2]
slicetiming.node.inputs.in_files = nifti_file
slicetiming.node.inputs.num_slices = num_slices
slicetiming.node.inputs.ref_slice = int(num_slices / 2)
slicetiming.node.inputs.time_repetition = TR
time_for_one_slice = TR / num_slices
slicetiming.node.inputs.time_acquisition = TR - time_for_one_slice
odd = range(1, num_slices + 1, 2)
even = range(2, num_slices + 1, 2)
acq_order = list(odd) + list(even)
slicetiming.node.inputs.slice_order = acq_order
# Edit datasink node inputs
datasink.node.inputs.base_directory = fmri_out
# Run the nipype pipeline
with stdchannel_redirected(sys.stderr, os.devnull):
fmri_preprocess.run()
# Motion quality control: Calculate Framewise Displacement
calculate_FD(glob.glob(os.path.join(fmri_out,
template_dict['fmri_output_dirname'], 'rp*.txt'))[0], **template_dict)
# Write readme files
write_readme_files(write_dir, data_type, **template_dict)
except Exception as e:
# If the above code fails for any reason update the error log for the subject id
# ex: the nifti file is not a nifti file
# the input file is not a brian scan
error_log.update({sub_id: str(e)})
finally:
remove_tmp_files()
output_message = "FMRI preprocessing completed. "
if bool(error_log):
output_message = output_message + " Error log:" + str(error_log)
return output_message
infosource.iterables = [('subject_id', sub_list)]
# ======================================================================
# DEFINE SELECTFILES NODE
# ======================================================================
path_root = dicom_directory #os.path.dirname(os.getcwd())
path_app = os.path.dirname(os.getcwd())
templates = dict(dicom=opj(path_root, '', '{subject_id}'))
test = opj(path_app, 'CLF-python')
# define the selectfiles node:
selectfiles = Node(SelectFiles(templates), name='selectfiles')
# ======================================================================
# DICOM 2 NIFTI CONVERSION
# ======================================================================
# function: put dcm2niix into a node:
dcm2niix = Node(Dcm2niix(), name='dcm2niix')
dcm2niix.inputs.out_filename = '%i_%4s_%d'
print(dcm2niix.inputs.out_filename)
# ======================================================================
# DEFINE FREESURFER NODE
# ======================================================================
# function: autorecon1
# 1. Motion Correction and Conform
# 2. NU (Non-Uniform intensity normalization)
# 3. Talairach transform computation
# 4. Intensity Normalization 1
# 5. Skull Strip
#bk#fs_recon1 = create_AutoRecon1()
#fs_recon1.inputs.inputspec.subject_id = 'subj1'
#fs_recon1.inputs.inputspec.subjects_dir = '.'
import os
import pytest
import shutil
from nipype.interfaces.dcm2nii import Dcm2niix
no_dcm2niix = not bool(Dcm2niix().version)
no_datalad = False
try:
from datalad import api # to pull and grab data
from datalad.support.exceptions import IncompleteResultsError
except ImportError:
no_datalad = True
DICOM_DIR = 'http://datasets-tests.datalad.org/dicoms/dcm2niix-tests'
@pytest.fixture
def fetch_data():
def _fetch_data(datadir, dicoms):
try:
"""Fetches some test DICOMs using datalad"""
api.install(path=datadir, source=DICOM_DIR)
data = os.path.join(datadir, dicoms)
api.get(path=data)
except IncompleteResultsError as exc:
pytest.skip("Failed to fetch test data: %s" % str(exc))
return data
return _fetch_data
os.makedirs(output_dir)
for sub_id in sub_id_list:
subject_out_dir = os.path.join(output_dir, sub_id)
os.makedirs(subject_out_dir, exist_ok=True)
par_list = glob(os.path.join(raw_dir, sub_id, "*t1w*.par"))
if not par_list:
raise Exception("No t1w images for {}".format(sub_id))
for par in par_list:
out_filename = os.path.basename(par).split(".par")[0]
full_out_path = os.path.join(subject_out_dir,
out_filename + ".nii.gz")
print(full_out_path)
if not os.path.isfile(full_out_path):
converter = Dcm2niix()
converter.inputs.source_names = [par]
converter.inputs.bids_format = True
converter.inputs.compress = 'i'
converter.inputs.has_private = True
converter.inputs.output_dir = subject_out_dir
converter.inputs.out_filename = out_filename
print("XXXXXXX running dcm2niix command")
print(converter.cmdline)
converter_results = converter.run()
reorient = Reorient2Std()
reorient.inputs.in_file = converter_results.outputs.converted_files
reorient.inputs.out_file = converter_results.outputs.converted_files
datasource_rt = nipype.Node(
interface=nipype.DataGrabber(infields=['rt_files'], outfields=['directory']),
name='datasource_rt')
datasource_rt.inputs.base_directory = base_dir
datasource_rt.inputs.template = '*'
datasource_rt.inputs.sort_filelist = True
datasource_rt.inputs.field_template = dict(directory='*/*/%s/1-*')
dc_rt = nipype.MapNode(interface=DicomCheck(), iterfield=['dicom_dir'], name='dc_rt')
dc_rt.inputs.working_dir = result_dir
dc = nipype.MapNode(interface=DicomCheck(), iterfield=['dicom_dir'], name='dc')
dc.inputs.working_dir = result_dir
converter = nipype.MapNode(interface=Dcm2niix(),
iterfield=['source_dir', 'out_filename', 'output_dir'],
name='converter')
converter.inputs.compress = 'y'
converter.inputs.philips_float = False
converter.inputs.merge_imgs = True
check = nipype.MapNode(interface=ConversionCheck(),
iterfield=['in_file', 'file_name'],
name='check_conversion')
workflow = nipype.Workflow('data_preparation_workflow', base_dir=cache_dir)
workflow.connect(inputnode, 'contrasts', datasource, 'contrasts')
workflow.connect(datasource, 'directory', dc, 'dicom_dir')
workflow.connect(inputnode_rt, 'rt_files', datasource_rt, 'rt_files')
workflow.connect(datasource_rt, 'directory', dc_rt, 'dicom_dir')
