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 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)
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 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)
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 _get_vendor(dicom_input):
"""
This function will check the dicom headers to see which type of series it is
Possibilities are fMRI, DTI, Anatomical (if no clear type is found anatomical is used)
"""
# check if it is siemens
if common.is_siemens(dicom_input):
logger.info('Found manufacturer: SIEMENS')
return Vendor.SIEMENS
# check if it is ge
if common.is_ge(dicom_input):
logger.info('Found manufacturer: GE')
return Vendor.GE
# check if it is philips
if common.is_philips(dicom_input):
logger.info('Found manufacturer: PHILIPS')
return Vendor.PHILIPS
# check if it is philips
if common.is_hitachi(dicom_input):
logger.info('Found manufacturer: HITACHI')
return Vendor.HITACHI
# generic by default
logger.info('WARNING: Assuming generic vendor conversion (ANATOMICAL)')
return Vendor.GENERIC
def _get_vendor(dicom_input):
"""
This function will check the dicom headers to see which type of series it is
Possibilities are fMRI, DTI, Anatomical (if no clear type is found anatomical is used)
"""
# check if it is siemens
if common.is_siemens(dicom_input):
logger.info('Found manufacturer: SIEMENS')
return Vendor.SIEMENS
# check if it is ge
if common.is_ge(dicom_input):
logger.info('Found manufacturer: GE')
return Vendor.GE
# check if it is philips
if common.is_philips(dicom_input):
logger.info('Found manufacturer: PHILIPS')
return Vendor.PHILIPS
# check if it is philips
if common.is_hitachi(dicom_input):
logger.info('Found manufacturer: HITACHI')
return Vendor.HITACHI
# generic by default
logger.info('WARNING: Assuming generic vendor conversion (ANATOMICAL)')
return Vendor.GENERIC
def test_is_siemens(self):
assert not common.is_siemens(read_dicom_directory(test_data.PHILIPS_ANATOMICAL))
assert common.is_siemens(read_dicom_directory(test_data.SIEMENS_ANATOMICAL))
assert not common.is_siemens(read_dicom_directory(test_data.GE_ANATOMICAL))
assert not common.is_siemens(read_dicom_directory(test_data.GENERIC_ANATOMICAL))
assert not common.is_siemens(read_dicom_directory(test_data.HITACHI_ANATOMICAL))
def anonymize_directory(input_directory, output_directory=None):
if output_directory is None:
output_directory = input_directory
study_uid = pydicom.uid.generate_uid()
series_uid = pydicom.uid.generate_uid()
date = datetime.datetime.now().strftime("%Y%m%d")
time = datetime.datetime.now().strftime("%H%M%S.000000")
fields_to_keep = {
'SpecificCharacterSet':
None,
'ImageType':
None,
'AcquisitionMatrix':
None,
'SOPClassUID':
None,
'SOPInstanceUID':
None, # Will be replaced by file-unique UID
'StudyDate':
date,
'SeriesDate':
date,
'AcquisitionDate':
date,
'ContentDate':
date,
'StudyTime':
time,
'AcquisitionTime':
time,
'AcquisitionNumber':
None,
'Modality':
None,
'Manufacturer':
None,
'ManufacturersModelName':
None,
'PatientName':
'dicom2nifti',
'PatientID':
'dicom2nifti',
'PatientsBirthDate':
date,
'PatientsSex':
None,
'PatientsAge':
'0Y',
'PatientPosition':
None,
'ScanningSequence':
None,
'SequenceVariant':
None,
'MRAcquisitionType':
None,
'SequenceName':
'dicom2nifti',
'RepetitionTime':
None,
'EchoTime':
None,
'InversionTime':
None,
'DeviceSerialNumber':
'1234',
'StudyInstanceUID':
study_uid,
'SeriesInstanceUID':
series_uid,
'StudyID':
'dicom2nifti',
'SeriesNumber':
None,
'InstanceNumber':
None,
'ImagePositionPatient':
None,
'ImageOrientationPatient':
None,
'SliceLocation':
None,
'PhotometricInterpretation':
None,
'Rows':
None,
'Columns':
None,
'PixelSpacing':
None,
'BitsAllocated':
None,
'BitsStored':
None,
'HighBit':
None,
'RescaleSlope':
None,
'RescaleIntercept':
None,
'PixelRepresentation':
None,
'NumberOfFrames':
None,
'SamplesPerPixel':
None,
'SpacingBetweenSlices':
None,
# Pixel Data must be specified with hex code as it will not work for compressed dicoms
(0x7fe0, 0x0010):
None
}
if is_philips(read_dicom_directory(input_directory)):
philips_fields = {
(0x2001, 0x100a): None,
(0x2001, 0x1003): None,
(0x2001, 0x105f): None,
(0x2005, 0x100d): None,
(0x2005, 0x100e): None,
(0x2005, 0x10b0): None,
(0x2005, 0x10b1): None,
(0x2005, 0x10b2): None,
(0x0018, 0x9087): None,
(0x0018, 0x9089): None,
(0x5200, 0x9230): None,
'SharedFunctionalGroupsSequence': None
}
fields_to_keep.update(philips_fields)
if is_siemens(read_dicom_directory(input_directory)):
siemens_fields = {
(0x0019, 0x100c): None,
(0x0029, 0x1020): None,
(0x0051, 0x100b): None,
(0x0019, 0x100e): None
}
fields_to_keep.update(siemens_fields)
if is_ge(read_dicom_directory(input_directory)):
ge_fields = {
(0x0020, 0x9056): None,
(0x0020, 0x9057): None,
(0x0043, 0x1039): None,
(0x0019, 0x10bb): None,
(0x0019, 0x10bc): None,
(0x0019, 0x10bd): None
}
fields_to_keep.update(ge_fields)
_anonymize_files(input_directory, output_directory, fields_to_keep)
