def dicom_to_nifti(dicom_input, output_file=None):
"""
This is the main dicom to nifti conversion fuction for ge images.
As input ge images are required. It will then determine the type of images and do the correct conversion
Examples: See unit test
:param output_file: the filepath to the output nifti file
:param dicom_input: list with dicom objects
"""
assert common.is_ge(dicom_input)
# remove duplicate slices based on position and data
dicom_input = convert_generic.remove_duplicate_slices(dicom_input)
# remove localizers based on image type
dicom_input = convert_generic.remove_localizers_by_imagetype(dicom_input)
# remove_localizers based on image orientation (only valid if slicecount is validated)
dicom_input = convert_generic.remove_localizers_by_orientation(dicom_input)
logger.info('Reading and sorting dicom files')
grouped_dicoms = _get_grouped_dicoms(dicom_input)
if _is_4d(grouped_dicoms):
logger.info('Found sequence type: 4D')
return _4d_to_nifti(grouped_dicoms, output_file)
logger.info('Assuming anatomical data')
return convert_generic.dicom_to_nifti(dicom_input, output_file)
def dicom_to_nifti(dicom_input, output_file=None):
"""
This is the main dicom to nifti conversion fuction for hitachi images.
As input hitachi images are required. It will then determine the type of images and do the correct conversion
Examples: See unit test
:param output_file: file path to the output nifti
:param dicom_input: directory with dicom files for 1 scan
"""
assert common.is_hitachi(dicom_input)
# remove duplicate slices based on position and data
dicom_input = convert_generic.remove_duplicate_slices(dicom_input)
# remove localizers based on image type
dicom_input = convert_generic.remove_localizers_by_imagetype(dicom_input)
# remove_localizers based on image orientation (only valid if slicecount is validated)
dicom_input = convert_generic.remove_localizers_by_orientation(dicom_input)
# TODO add validations and conversion for DTI and fMRI once testdata is available
logger.info('Assuming anatomical data')
return convert_generic.dicom_to_nifti(dicom_input, output_file)
def dicom_to_nifti(dicom_input, output_file=None):
"""
This is the main dicom to nifti conversion function for ge images.
As input ge images are required. It will then determine the type of images and do the correct conversion
:param output_file: filepath to the output nifti
:param dicom_input: directory with dicom files for 1 scan
"""
assert common.is_siemens(dicom_input)
# remove duplicate slices based on position and data
dicom_input = convert_generic.remove_duplicate_slices(dicom_input)
# remove localizers based on image type
dicom_input = convert_generic.remove_localizers_by_imagetype(dicom_input)
# remove_localizers based on image orientation (only valid if slicecount is validated)
dicom_input = convert_generic.remove_localizers_by_orientation(dicom_input)
if _is_4d(dicom_input):
logger.info('Found sequence type: MOSAIC 4D')
return _mosaic_4d_to_nifti(dicom_input, output_file)
grouped_dicoms = _classic_get_grouped_dicoms(dicom_input)
if _is_classic_4d(grouped_dicoms):
logger.info('Found sequence type: CLASSIC 4D')
return _classic_4d_to_nifti(grouped_dicoms, output_file)
logger.info('Assuming anatomical data')
return convert_generic.dicom_to_nifti(dicom_input, output_file)
def dicom_to_nifti(dicom_input, output_file=None):
"""
This is the main dicom to nifti conversion fuction for philips images.
As input philips images are required. It will then determine the type of images and do the correct conversion
Examples: See unit test
:param output_file: file path to the output nifti
:param dicom_input: directory with dicom files for 1 scan
"""
assert common.is_philips(dicom_input)
# remove duplicate slices based on position and data
dicom_input = convert_generic.remove_duplicate_slices(dicom_input)
# remove localizers based on image type
dicom_input = convert_generic.remove_localizers_by_imagetype(dicom_input)
# remove_localizers based on image orientation (only valid if slicecount is validated)
dicom_input = convert_generic.remove_localizers_by_orientation(dicom_input)
# if no dicoms remain raise exception
if not dicom_input:
raise ConversionValidationError('TOO_FEW_SLICES/LOCALIZER')
if common.is_multiframe_dicom(dicom_input):
_assert_explicit_vr(dicom_input)
logger.info('Found multiframe dicom')
if _is_multiframe_4d(dicom_input):
logger.info('Found sequence type: MULTIFRAME 4D')
return _multiframe_to_nifti(dicom_input, output_file)
if _is_multiframe_anatomical(dicom_input):
logger.info('Found sequence type: MULTIFRAME ANATOMICAL')
return _multiframe_to_nifti(dicom_input, output_file)
else:
logger.info('Found singleframe dicom')
grouped_dicoms = _get_grouped_dicoms(dicom_input)
if _is_singleframe_4d(dicom_input):
logger.info('Found sequence type: SINGLEFRAME 4D')
return _singleframe_to_nifti(grouped_dicoms, output_file)
logger.info('Assuming anatomical data')
return convert_generic.dicom_to_nifti(dicom_input, output_file)