def test_validate_sliceincrement(self):
validate_sliceincrement(
sort_dicoms(read_dicom_directory(test_data.GE_ANATOMICAL)))
self.assertRaises(
ConversionValidationError, validate_sliceincrement,
sort_dicoms(read_dicom_directory(
test_data.FAILING_SLICEINCREMENT)))
def dicom_to_nifti(dicom_input, output_file):
"""
This function will convert an anatomical dicom series to a nifti
Examples: See unit test
:param output_file: filepath to the output nifti
:param dicom_input: directory with the dicom files for a single scan, or list of read in dicoms
"""
if len(dicom_input) <= 0:
raise ConversionError('NO_DICOM_FILES_FOUND')
# remove duplicate slices based on position and data
dicom_input = _remove_duplicate_slices(dicom_input)
# remove localizers based on image type
dicom_input = _remove_localizers_by_imagetype(dicom_input)
if settings.validate_slicecount:
# remove_localizers based on image orientation (only valid if slicecount is validated)
dicom_input = _remove_localizers_by_orientation(dicom_input)
# validate all the dicom files for correct orientations
common.validate_slicecount(dicom_input)
if settings.validate_orientation:
# validate that all slices have the same orientation
common.validate_orientation(dicom_input)
if settings.validate_orthogonal:
# validate that we have an orthogonal image (to detect gantry tilting etc)
common.validate_orthogonal(dicom_input)
# sort the dicoms
dicom_input = common.sort_dicoms(dicom_input)
if settings.validate_sliceincrement:
# validate that all slices have a consistent slice increment
common.validate_sliceincrement(dicom_input)
# Get data; originally z,y,x, transposed to x,y,z
data = common.get_volume_pixeldata(dicom_input)
affine = common.create_affine(dicom_input)
# Convert to nifti
nii_image = nibabel.Nifti1Image(data, affine)
# Set TR and TE if available
if Tag(0x0018, 0x0081) in dicom_input[0] and Tag(0x0018,
0x0081) in dicom_input[0]:
common.set_tr_te(nii_image, float(dicom_input[0].RepetitionTime),
float(dicom_input[0].EchoTime))
# Save to disk
if output_file is not None:
logger.info('Saving nifti to disk %s' % output_file)
nii_image.to_filename(output_file)
return {'NII_FILE': output_file, 'NII': nii_image}