def initialize(self, data_collection):
super(SkullStrip, self).initialize(data_collection)
for label, data_group in data_collection.data_groups.iteritems():
reference_filename = data_group.data[data_collection.current_case][
self.reference_channel]
self.mask_filename = self.generate_output_filename(
reference_filename, self.mask_string)
if type(data_group.preprocessed_case) is list:
input_file = data_group.preprocessed_case[
self.reference_channel]
else:
# What to do about affines here... Also, reroute this file to a temporary directory.
input_file = save_numpy_2_nifti(
data_group.preprocessed_case[..., self.reference_channel],
data_group.preprocessed_affine,
self.generate_output_filename(reference_filename))
specific_command = self.command + [
quotes(input_file),
quotes(self.mask_filename), '-f',
str(self.bet2_f), '-g',
str(self.bet2_g), '-m'
]
subprocess.call(' '.join(specific_command), shell=True)
os.rename(self.mask_filename + '_mask.nii.gz', self.mask_filename)
self.mask_numpy = read_image_files(self.mask_filename,
return_affine=False)
def preprocess(self, data_group):
for file_idx, filename in enumerate(data_group.preprocessed_case):
if self.reference_channel is None:
specific_command = self.command + [
'ResampleScalarVolume', '-i', self.interpolation, '-s',
self.dimensions,
quotes(filename),
quotes(self.output_filenames[file_idx])
]
else:
specific_command = self.command + [
'ResampleScalarVectorDWIVolume', '-R',
self.reference_channel, '--interpolation',
self.interpolation_dict[self.interpolation],
quotes(self.base_file),
quotes(self.output_filename)
]
subprocess.call(' '.join(specific_command),
shell=True,
stdout=FNULL,
stderr=subprocess.STDOUT)
self.output_data = self.output_filenames
data_group.preprocessed_case = self.output_filenames
def preprocess(self, data_group):
for file_idx, filename in enumerate(data_group.preprocessed_case):
transform_filename = self.generate_output_filename(filename, self.transform_string, file_extension='.tfm')
if self.reference_channel is not None:
if self.reference_channel == file_idx:
self.output_filenames[file_idx] = filename
self.output_transforms += [None]
continue
else:
specific_command = self.command + ['--fixedVolume', quotes(data_group.preprocessed_case[self.reference_channel]), '--transformType', self.transform_type, '--initializeTransformMode', self.transform_initialization, '--interpolationMode', self.interpolation, '--samplingPercentage', str(self.sampling_percentage), '--movingVolume', quotes(filename), '--outputVolume', quotes(self.output_filenames[file_idx]), '--outputTransform', quotes(transform_filename)]
else:
specific_command = self.command + ['--fixedVolume', quotes(self.reference_file), '--transformType', self.transform_type, '--initializeTransformMode', self.transform_initialization, '--interpolationMode', self.interpolation, '--samplingPercentage', str(self.sampling_percentage), '--movingVolume', quotes(self.base_file), '--outputVolume', quotes(self.output_filename), '--outputTransform', quotes(transform_filename)]
subprocess.call(' '.join(specific_command), shell=True, stdout=FNULL, stderr=subprocess.STDOUT)
# self.output_transforms += [read_image_files(transform_filename)]
if not self.save_transforms:
os.remove(transform_filename)
self.output_data = self.output_filenames
data_group.preprocessed_case = self.output_filenames
def save_input_2_dso(input_data, reference_dicom_filepath, dso_metadata, reference_nifti_filepath=None, output_filepath=None, command='/home/abeers/Software/dcmqi-1.0.9-linux/bin/itkimage2segimage', verbose=True):
""" Given an DICOM directory to reference and a list of files (and in the future Nifti files), save these files
to a DSO object.
"""
reference_dicom_filepath = os.path.abspath(reference_dicom_filepath)
output_filepath = os.path.abspath(output_filepath)
dso_metadata = os.path.abspath(dso_metadata)
base_command = [command, '--inputDICOMDirectory', quotes(reference_dicom_filepath), '--outputDICOM', output_filepath, '--inputMetadata', dso_metadata, '--inputImageList']
if type(input_data) is not list:
input_data = [input_data]
input_data_string = ''
for data_object in input_data:
if input_data_string != '':
input_data_string += ','
# Check this typing syntax for Python 3
if type(data_object) is str:
data_object = os.path.abspath(data_object)
input_data_string += data_object
else:
pass
# TODO: Put in utility for converting numpy to DSO.
base_command += [input_data_string]
print((' '.join(base_command)))
subprocess.call(' '.join(base_command), shell=True)
return output_filepath
def preprocess(self, data_group):
for file_idx, filename in enumerate(data_group.preprocessed_case):
specific_command = self.command + ['N4ITKBiasFieldCorrection', quotes(filename), quotes(self.output_filenames[file_idx])]
subprocess.call(' '.join(specific_command), shell=True, stdout=FNULL, stderr=subprocess.STDOUT)
self.output_data = self.output_filenames
data_group.preprocessed_case = self.output_filenames
def singularity_wrapper(command,
cli_args=None,
filename_args=None,
interactive=False,
container='deepneuro'):
raise NotImplementedError
if filename_args is not None:
filename_args = [
arg for arg in filename_args if cli_args[arg] is not None
]
mounted_dir = os.path.abspath(
os.path.dirname(
os.path.commonprefix([cli_args[arg]
for arg in filename_args])))
for arg in filename_args:
after_mounted = os.path.abspath(cli_args[arg]).split(
mounted_dir, 1)[1].lstrip(os.sep)
cli_args[arg] = quotes(os.path.join('/INPUT_DATA', after_mounted))
else:
pass # TODO: Default behavior when mounted directory not needed.
if interactive:
docker_command = [
'nvidia-docker', 'run', '-it', '-v', mounted_dir + ':/INPUT_DATA',
container, 'bash'
]
else:
docker_command = [
'nvidia-docker', 'run', '--rm', '-v', mounted_dir + ':/INPUT_DATA',
container
] + command
# This presumes everything is an optional arg, which is wrong.
# Rewrite this to accept command line strings, instead of Python variables.
# Would solve problem..
for arg in cli_args:
if cli_args[arg] is True:
docker_command += ['-' + str(arg)]
elif not cli_args[arg] or cli_args[arg] is None:
continue
else:
docker_command += ['-' + str(arg) + ' ' + cli_args[arg]]
call(' '.join(docker_command), shell=True)
