def create_dcm_file(self):
suffix = '.dcm'
filename_little_endian = tempfile.NamedTemporaryFile(
suffix=suffix).name
filename_big_endian = tempfile.NamedTemporaryFile(suffix=suffix).name
print("Setting file meta information...")
file_meta = Dataset()
file_meta.MediaStorageSOPClassUID = '1.2.840.10008.5.1.4.1.1.2'
file_meta.MediaStorageSOPInstanceUID = "1.2.3"
file_meta.ImplementationClassUID = "1.2.3.4"
print("Setting dataset values...")
ds = FileDataset(filename_little_endian, {},
file_meta=file_meta,
preamble=b"\0" * 128)
ds.PatientName = self.get_patient_name(
) + " " + self.get_patient_surname()
ds.PatientID = self.get_patient_id()
ds.PatientSex = self.get_patient_sex()
ds.PatientAge = self.get_patient_age()
ds.PatientWeight = self.get_patient_weight()
ds.ImageComment = self.get_patient_comment()
ds.PatientBirthDate = self.get_patient_birth()
# Set the transfer syntax
ds.is_little_endian = True
ds.is_implicit_VR = True
# Set creation date/time
dt = datetime.datetime.now()
ds.ContentDate = dt.strftime('%Y%m%d')
timeStr = dt.strftime('%H%M%S.%f') # long format with micro seconds
ds.ContentTime = timeStr
ds.BitsAllocated = 16
ds.Rows = self.image.shape[0]
ds.Columns = self.image.shape[1]
ds.PixelRepresentation = 0
ds.SamplesPerPixel = 1
ds.PhotometricInterpretation = "MONOCHROME2"
image = self.image
image *= 255
image = image.astype("uint16")
ds.PixelData = Image.fromarray(image).tobytes()
print("Writing test file", filename_little_endian)
ds.save_as(filename_little_endian)
print("File saved.")
ds.file_meta.TransferSyntaxUID = pydicom.uid.ExplicitVRBigEndian
ds.is_little_endian = False
ds.is_implicit_VR = False
print("Writing test file as Big Endian Explicit VR",
filename_big_endian)
ds.save_as(filename_big_endian)
return ds
def generate_common_dicom_dataset_series(self, slice_count: int,
system: Modality) -> list:
output_dataset = []
slice_pos = 0
slice_thickness = 0
study_uid = generate_uid()
series_uid = generate_uid()
frame_of_ref_uid = generate_uid()
date_ = datetime.now().date()
age = timedelta(days=45 * 365)
time_ = datetime.now().time()
cols = 2
rows = 2
bytes_per_voxel = 2
for i in range(0, slice_count):
file_meta = Dataset()
pixel_array = b"\0" * cols * rows * bytes_per_voxel
file_meta.MediaStorageSOPClassUID = sop_classes[system][1]
file_meta.MediaStorageSOPInstanceUID = generate_uid()
file_meta.ImplementationClassUID = generate_uid()
tmp_dataset = FileDataset('', {},
file_meta=file_meta,
preamble=pixel_array)
tmp_dataset.file_meta.TransferSyntaxUID = "1.2.840.10008.1.2.1"
tmp_dataset.SliceLocation = slice_pos + i * slice_thickness
tmp_dataset.SliceThickness = slice_thickness
tmp_dataset.WindowCenter = 1
tmp_dataset.WindowWidth = 2
tmp_dataset.AcquisitionNumber = 1
tmp_dataset.InstanceNumber = i
tmp_dataset.SeriesNumber = 1
tmp_dataset.ImageOrientationPatient = [
1.000000, 0.000000, 0.000000, 0.000000, 1.000000, 0.000000
]
tmp_dataset.ImagePositionPatient = [
0.0, 0.0, tmp_dataset.SliceLocation
]
tmp_dataset.ImageType = ['ORIGINAL', 'PRIMARY', 'AXIAL']
tmp_dataset.PixelSpacing = [1, 1]
tmp_dataset.PatientName = 'John Doe'
tmp_dataset.FrameOfReferenceUID = frame_of_ref_uid
tmp_dataset.SOPClassUID = sop_classes[system][1]
tmp_dataset.SOPInstanceUID = generate_uid()
tmp_dataset.SeriesInstanceUID = series_uid
tmp_dataset.StudyInstanceUID = study_uid
tmp_dataset.BitsAllocated = bytes_per_voxel * 8
tmp_dataset.BitsStored = bytes_per_voxel * 8
tmp_dataset.HighBit = (bytes_per_voxel * 8 - 1)
tmp_dataset.PixelRepresentation = 1
tmp_dataset.Columns = cols
tmp_dataset.Rows = rows
tmp_dataset.SamplesPerPixel = 1
tmp_dataset.AccessionNumber = '2'
tmp_dataset.AcquisitionDate = date_
tmp_dataset.AcquisitionTime = datetime.now().time()
tmp_dataset.AdditionalPatientHistory = 'UTERINE CA PRE-OP EVAL'
tmp_dataset.ContentDate = date_
tmp_dataset.ContentTime = datetime.now().time()
tmp_dataset.Manufacturer = 'Mnufacturer'
tmp_dataset.ManufacturerModelName = 'Model'
tmp_dataset.Modality = sop_classes[system][0]
tmp_dataset.PatientAge = '064Y'
tmp_dataset.PatientBirthDate = date_ - age
tmp_dataset.PatientID = 'ID0001'
tmp_dataset.PatientIdentityRemoved = 'YES'
tmp_dataset.PatientPosition = 'FFS'
tmp_dataset.PatientSex = 'F'
tmp_dataset.PhotometricInterpretation = 'MONOCHROME2'
tmp_dataset.PixelData = pixel_array
tmp_dataset.PositionReferenceIndicator = 'XY'
tmp_dataset.ProtocolName = 'some protocole'
tmp_dataset.ReferringPhysicianName = ''
tmp_dataset.SeriesDate = date_
tmp_dataset.SeriesDescription = 'test series '
tmp_dataset.SeriesTime = time_
tmp_dataset.SoftwareVersions = '01'
tmp_dataset.SpecificCharacterSet = 'ISO_IR 100'
tmp_dataset.StudyDate = date_
tmp_dataset.StudyDescription = 'test study'
tmp_dataset.StudyID = ''
if (system == Modality.CT):
tmp_dataset.RescaleIntercept = 0
tmp_dataset.RescaleSlope = 1
tmp_dataset.StudyTime = time_
output_dataset.append(tmp_dataset)
return output_dataset