def _write_dicom_file(np_slice: np.ndarray, header: pydicom.FileDataset,
file_path: str):
"""Replace data in header with 2D numpy array and write to `file_path`.
Args:
np_slice (np.ndarray): 2D slice to encode in dicom file.
header (pydicom.FileDataset): DICOM header.
file_path: File path to write to.
"""
# Deep copy required in case headers are shared.
header = copy.deepcopy(header)
expected_dimensions = header.Rows, header.Columns
assert (
np_slice.shape == expected_dimensions
), "In-plane dimension mismatch - expected shape {}, got {}".format(
str(expected_dimensions), str(np_slice.shape))
np_slice_bytes = np_slice.tobytes()
bit_depth = int(
len(np_slice_bytes) / (np_slice.shape[0] * np_slice.shape[1]) * 8)
if bit_depth != header.BitsAllocated:
np_slice = _update_np_dtype(np_slice, header.BitsAllocated)
np_slice_bytes = np_slice.tobytes()
bit_depth = int(
len(np_slice_bytes) / (np_slice.shape[0] * np_slice.shape[1]) * 8)
assert bit_depth == header.BitsAllocated, "Bit depth mismatch: Expected {:d} got {:d}".format(
header.BitsAllocated, bit_depth)
header.PixelData = np_slice_bytes
header.save_as(file_path)
def __write_dicom_file__(self, np_slice: np.ndarray,
header: pydicom.FileDataset, filepath: str):
"""
Replace data in header with 2D numpy array and write to filepath
:param np_slice: a 2D numpy array
:param header: a pydicom.FileDataset with fields populated
:param filepath: Filepath to write dicom to
"""
expected_dimensions = header.Rows, header.Columns
assert np_slice.shape == expected_dimensions, "In-plane dimension mismatch - expected shape %s, got %s" % (
str(expected_dimensions), str(np_slice.shape))
np_slice_bytes = np_slice.tobytes()
bit_depth = int(
len(np_slice_bytes) / (np_slice.shape[0] * np_slice.shape[1]) * 8)
if bit_depth != header.BitsAllocated:
np_slice = __update_np_dtype__(np_slice, header.BitsAllocated)
np_slice_bytes = np_slice.tobytes()
bit_depth = int(
len(np_slice_bytes) / (np_slice.shape[0] * np_slice.shape[1]) *
8)
assert bit_depth == header.BitsAllocated, "Bit depth mismatch: Expected %d got %d" % (
header.BitsAllocated, bit_depth)
header.PixelData = np_slice_bytes
header.save_as(filepath)
def _get_window(dicom_file: pydicom.FileDataset, window='default', unit=None):
if isinstance(window, dict):
wc = window.get('window_center')
ww = window.get('window_width')
elif window == 'default' or unit is None:
try:
wc = dicom_file.WindowCenter
ww = dicom_file.WindowWidth
if isinstance(wc, pydicom.multival.MultiValue):
wc = wc[0]
if isinstance(ww, pydicom.multival.MultiValue):
ww = ww[0]
except:
BitsStored = dicom_file.get('BitsStored')
wc = 2**(BitsStored - 1)
ww = 2**BitsStored
elif isinstance(window, str) and unit in ['HU', 'Hounsfield Unit']:
wc, ww = get_ct_window(window)
else:
try:
wc = dicom_file.WindowCenter
ww = dicom_file.WindowWidth
if isinstance(wc, pydicom.multival.MultiValue):
wc = wc[0]
if isinstance(ww, pydicom.multival.MultiValue):
ww = ww[0]
except:
wc = None
ww = None
if wc is None or ww is None:
raise ValueError('Either window center or window width not found')
return wc, ww
def voi_lut_trans(dicom_file: pydicom.FileDataset,
image_data: numpy.ndarray,
depth,
window='default',
unit: str = None):
VOILUTSequence = getattr(dicom_file, 'VOILUTSequence', [{}])[0]
lut_descriptor = VOILUTSequence.get('LUTDescriptor')
if lut_descriptor is None:
lut_descriptor = VOILUTSequence.get('LUTDescriptor')
if isinstance(lut_descriptor, bytes):
PixelRepresentation = int(dicom_file.get('PixelRepresentation'))
if modality_classifier(
dicom_file) is None and PixelRepresentation == 0:
dtype = numpy.ushort
else:
dtype = numpy.short
lut_descriptor = numpy.frombuffer(lut_descriptor, dtype)
lut_data = VOILUTSequence.get('LUTData')
if isinstance(lut_data, bytes):
if lut_descriptor[2] == 8:
dtype = numpy.uint8
elif lut_descriptor[2] == 16:
dtype = numpy.uint16
else:
raise ValueError(
f'LUTDescriptor[2] should be 8 or 16. Got {lut_descriptor[2]}')
lut_data = numpy.frombuffer(lut_data, dtype)
scale_factor = depth / int(2**getattr(dicom_file, 'BitsStored', 12))
return lut_trans(image_data, lut_descriptor, lut_data, scale_factor)
def test_force_is_true(self):
"""
- Writes dicom file from scratch without File Meta Information Header
- read with force = True
- Check it doesn't raise InvalidDicomError Exception
- Check file_meta has length 0
"""
original_ds = FileDataset(FILENAME_PATH, {}, file_meta=None)
ds_creation_util.save_ds_file_as_dicom(original_ds)
ds = dcmread(FILENAME_PATH, force=True)
self.assertTrue(len(ds.file_meta) == 0)
def voi_classifier(dicom_file: pydicom.FileDataset):
"""
Get value of interest (voi) transform method name from dicom object
:param dicom_file: object read from pydicom
:return: voi transform method name. Includes
'LINEAR', 'LINEAR_EXACT', 'SIGMOID', 'TABLE', or None
"""
VOILUTFunction = dicom_file.get('VOILUTFunction')
VOILUTSequence = dicom_file.get('VOILUTSequence')
WindowCenter = dicom_file.get('WindowCenter')
if (VOILUTSequence is not None) and (WindowCenter is None):
return 'TABLE'
elif WindowCenter is not None:
if VOILUTFunction is None:
return 'LINEAR'
else:
return VOILUTFunction
else:
return 'LINEAR'
def modality_lut_trans(dicom_file: pydicom.FileDataset, image_data: numpy.ndarray):
ModalityLUTSequence = dicom_file.get('ModalityLUTSequence')[0]
lut_descriptor = ModalityLUTSequence.get('LUTDescriptor')
if lut_descriptor is None: # debug
lut_descriptor = ModalityLUTSequence.get('LUTDescriptor') # if don't do this line, line 40 will be None
if isinstance(lut_descriptor, bytes):
PixelRepresentation = int(dicom_file.get('PixelRepresentation'))
dtype = numpy.ushort if PixelRepresentation == 0 else numpy.short
lut_descriptor = numpy.frombuffer(lut_descriptor, dtype)
lut_data = ModalityLUTSequence.get('LUTData')
if isinstance(lut_data, bytes):
if lut_descriptor[2] == 8:
dtype = numpy.uint8
elif lut_descriptor[2] == 16:
dtype = numpy.uint16
else:
raise ValueError(f'LUTDescriptor[2] should be 8 or 16. Got {lut_descriptor[2]}')
lut_data = numpy.frombuffer(lut_data, dtype)
unit = ModalityLUTSequence.get('ModalityLUTType')
return lut_trans(image_data, lut_descriptor, lut_data), unit
def test_force_is_default_false_raise_exception(self):
"""
- Writes dicom file from scratch without File Meta Information Header
- read with force = False
- Check it raises InvalidDicomError Exception
"""
original_ds = FileDataset(FILENAME_PATH, {})
ds_creation_util.save_ds_file_as_dicom(original_ds)
try:
dcmread(FILENAME_PATH)
self.fail()
except InvalidDicomError:
pass
except:
self.fail()
def __init__(self, iod_type):
"""
Parameters
----------
iod_type : Type of IOD, i.e. DICOM object of class IODTypes
"""
self.iod_type = iod_type
file_meta = Dataset()
file_meta.MediaStorageSOPClassUID = iod_type.value
file_meta.MediaStorageSOPInstanceUID = uid.generate_uid()
file_meta.ImplementationClassUID = "1.2.752.24.16.4.1"
self.dataset = FileDataset(None, {},
file_meta=file_meta,
preamble=b"\0" * 128)
self.dataset.is_little_endian = True
self.dataset.is_implicit_VR = False
self.dataset.file_meta.TransferSyntaxUID = uid.ExplicitVRLittleEndian
def on_c_store(self, ds: Dataset, context, info):
logger.info('C-Store processing')
file_meta = Dataset()
file_meta.TransferSyntaxUID = ImplicitVRLittleEndian
file_meta.MediaStorageSOPClassUID = ds.SOPClassUID
file_meta.MediaStorageSOPInstanceUID = ds.SOPInstanceUID
file_meta.ImplementationClassUID = '1.3.6.1.4.1.9590.100.1.0.100.4.0'
fds = FileDataset(None, {}, file_meta=file_meta, preamble=b'\0' * 128)
fds.update(ds)
fds.is_little_endian = True
fds.is_implicit_VR = True
DicomSaver.save(fds)
logger.info('C-Store succeeded')
return 0x0000
def get_dcm_filed(__dcm: pydicom.FileDataset, __field_name: str):
__field = __dcm.get(__field_name)
if type(__field) == pydicom.multival.MultiValue:
return int(__field[0])
else:
return int(__field)
def dump_dicom(data, folder, spacing=(1, 1, 1),
origin=(0, 0, 0), intercept=0, slope=1):
""" Dump 3D scan in dicom format.
Parameters
----------
data : ndarray
3D numpy array containing ct scan's data.
folder : str
folder where dicom files will be dumped.
spacing : ArrayLike
ndarray of shape (3,) that contains spacing along z, y, x axes.
origin : ArrayLike
ndarray of shape (3,) that contains origin for z, y, x axes.
interception : float
interception value. Default is 0.
slope : float
slope value. Default is 1.
"""
spacing = np.array(spacing).reshape(-1)
origin = np.array(origin).reshape(-1)
if not os.path.exists(folder):
os.makedirs(folder)
num_slices = data.shape[0]
scan_id = np.random.randint(2 ** 16)
for i in range(num_slices):
slice_name = (
hex(scan_id + i)
.replace('x', '')
.upper()
.zfill(8)
)
filename = os.path.join(folder, slice_name)
pixel_array = (data[i, ...] - intercept) / slope
locZ, locY, locX = (float(origin[0] + spacing[0] * i),
float(origin[1]), float(origin[2]))
file_meta = Dataset()
file_meta.MediaStorageSOPClassUID = 'Secondary Capture Image Storage'
file_meta.MediaStorageSOPInstanceUID = (
hex(scan_id)
.replace('x', '')
.upper()
.zfill(8)
)
file_meta.ImplementationClassUID = slice_name
dataset = FileDataset(filename, {},
file_meta=file_meta,
preamble=b"\0"*128)
dataset.PixelData = pixel_array.astype(np.uint16).tostring()
dataset.RescaleSlope = slope
dataset.RescaleIntercept = intercept
dataset.ImagePositionPatient = MultiValue(type_constructor=float,
iterable=[locZ, locY, locX])
dataset.PixelSpacing = MultiValue(type_constructor=float,
iterable=[float(spacing[1]),
float(spacing[2])])
dataset.SliceThickness = float(spacing[0])
dataset.Modality = 'WSD'
dataset.Columns = pixel_array.shape[0]
dataset.Rows = pixel_array.shape[1]
dataset.file_meta.TransferSyntaxUID = pydicom.uid.ImplicitVRLittleEndian
dataset.PixelRepresentation = 1
dataset.BitsAllocated = 16
dataset.BitsStored = 16
dataset.SamplesPerPixel = 1
write_file(filename, dataset)
def generate_dicom_scans(dst, num_scans=10, intercept=0, slope=1):
spacing = (0.4 + 0.4 * np.random.rand(num_scans, 3) +
np.array([1 + 0.5 * np.random.rand(), 0, 0]))
origin = np.random.randint(-200, 200, (num_scans, 3))
for i in range(num_scans):
num_slices = np.random.randint(128, 169)
scan_id = np.random.randint(2**16)
scan_data = np.random.randint(0, 256, (num_slices, 128, 128))
folder = os.path.join(dst,
hex(scan_id).replace('x', '').upper().zfill(8))
if not os.path.exists(folder):
os.makedirs(folder)
for k in range(num_slices):
slice_name = (hex(scan_id + k).replace('x', '').upper().zfill(8))
filename = os.path.join(folder, slice_name)
pixel_array = (scan_data[k, ...] - intercept) / slope
locZ = float(origin[i, 0] + spacing[i, 0] * k)
locY, locX = float(origin[i, 1]), float(origin[i, 2])
file_meta = DicomDataset()
file_meta.MediaStorageSOPClassUID = "Secondary Capture Image Storage"
file_meta.MediaStorateSOPInstanceUID = (hex(scan_id).replace(
'x', '').upper().zfill(8))
file_meta.ImplementationClassUID = slice_name
dataset = DicomFileDataset(filename, {},
file_meta=file_meta,
preamble=b"\0" * 128)
dataset.PixelData = pixel_array.astype(np.uint16).tostring()
dataset.RescaleSlope = slope
dataset.RescaleIntercept = intercept
dataset.ImagePositionPatient = MultiValue(
type_constructor=float, iterable=[locZ, locY, locX])
dataset.PixelSpacing = MultiValue(
type_constructor=float,
iterable=[float(spacing[i, 1]),
float(spacing[i, 2])])
dataset.SliceThickness = float(spacing[i, 0])
dataset.Modality = 'WSD'
dataset.Columns = pixel_array.shape[0]
dataset.Rows = pixel_array.shape[1]
dataset.file_meta.TransferSyntaxUID = pydicom.uid.ImplicitVRLittleEndian
dataset.PixelRepresentation = 1
dataset.BitsAllocated = 16
dataset.BitsStored = 16
dataset.SamplesPerPixel = 1
write_file(filename, dataset)
def createStructDS(self, planData, ImageInfoUIDs, setupPosition,
roiShiftVector):
print("Creating Data structure")
# create RS SOPInstanceUID
structSOPInstanceUID = pydicom.uid.generate_uid()
structSeriesInstanceUID = pydicom.uid.generate_uid()
# get image header info from ImageSet_0.ImageInfo
structFrameUID = ''
structStudyInstanceUID = ''
structSeriesUID = ''
structClassUID = '1.2.840.10008.5.1.4.1.1.481.3'
if "ImageInfoList" in ImageInfoUIDs:
structFrameUID = ImageInfoUIDs.ImageInfoList[0].FrameUID
structStudyInstanceUID = ImageInfoUIDs.ImageInfoList[
0].StudyInstanceUID
structSeriesUID = ImageInfoUIDs.ImageInfoList[0].SeriesUID
# structClassUID = ImageInfoUIDs.ImageInfoList[0].ClassUID
# Populate required values for file meta information
file_meta = Dataset()
# RT Structure Set Storage
file_meta.MediaStorageSOPClassUID = structClassUID
file_meta.MediaStorageSOPInstanceUID = structSOPInstanceUID
structfilename = "RS." + structSOPInstanceUID + ".dcm"
# this value remains static since implementation for creating file is the same
file_meta.ImplementationClassUID = '1.2.826.0.1.3680043.8.498.75006884747854523615841001'
# Create the FileDataset instance (initially no data elements, but file_meta supplied)
ds = FileDataset(structfilename, {},
file_meta=file_meta,
preamble=b'\x00' * 128)
# print(file_meta.preamble)
# add info_data,basic patientinfo
# [0008,0005] - [0008,0018]
ds.SpecificCharacterSet = 'ISO_IR 100'
ds.InstanceCreationDate = time.strftime("%Y%m%d")
ds.InstanceCreationTime = time.strftime("%H%M%S")
ds.SOPClassUID = structClassUID
ds.SOPInstanceUID = structSOPInstanceUID
ds.Modality = 'RTSTRUCT'
ds.AccessionNumber = ""
ds.Manufacturer = 'Pinnalce3' # from sample dicom file, maybe should change?
# not sure where to get information for this element can find this and read in from
ds.StationName = "adacp3u7"
# ds.ManufacturersModelName = 'Pinnacle3'
ds = self.modifyPatientInfo(ds, planData)
# [0008,1110]
ds.ReferencedStudySequence = Sequence()
ReferencedStudy1 = Dataset()
ds.ReferencedStudySequence.append(ReferencedStudy1)
# Study Component Management SOP Class (chosen from template)
ds.ReferencedStudySequence[
0].ReferencedSOPClassUID = '1.2.840.10008.3.1.2.3.2'
ds.ReferencedStudySequence[
0].ReferencedSOPInstanceUID = structStudyInstanceUID
# ds.StudyInstanceUID = StudyInstanceUID
print("Setting structure file study instance: " +
str(structStudyInstanceUID))
# [0020,000d]
ds.StudyInstanceUID = structStudyInstanceUID
# [0020,000e]
ds.SeriesInstanceUID = structSeriesInstanceUID
# [3006,0010]
ds.ReferencedFrameOfReferenceSequence = Sequence()
ReferencedFrameofReference1 = Dataset()
ds.ReferencedFrameOfReferenceSequence.append(
ReferencedFrameofReference1)
ds.ReferencedFrameOfReferenceSequence[
0].FrameofReferenceUID = structFrameUID
# [3006,0012]
ds.ReferencedFrameOfReferenceSequence[
0].RTReferencedStudySequence = Sequence()
RTReferencedStudy1 = Dataset()
ds.ReferencedFrameOfReferenceSequence[
0].RTReferencedStudySequence.append(RTReferencedStudy1)
ds.ReferencedFrameOfReferenceSequence[0].RTReferencedStudySequence[
0].ReferencedSOPClassUID = '1.2.840.10008.3.1.2.3.2'
ds.ReferencedFrameOfReferenceSequence[0].RTReferencedStudySequence[
0].ReferencedSOPInstanceUID = structStudyInstanceUID
# ds.StudyInstanceUID = StudyInstanceUID
# [3006,0014]
ds.ReferencedFrameOfReferenceSequence[0].RTReferencedStudySequence[
0].RTReferencedSeriesSequence = Sequence()
RTReferencedSeries1 = Dataset()
ds.ReferencedFrameOfReferenceSequence[0].RTReferencedStudySequence[
0].RTReferencedSeriesSequence.append(RTReferencedSeries1)
ds.ReferencedFrameOfReferenceSequence[0].RTReferencedStudySequence[
0].RTReferencedSeriesSequence[
0].SeriesInstanceUID = structSeriesUID
# [3006,0016]
ds.ReferencedFrameOfReferenceSequence[0].RTReferencedStudySequence[
0].RTReferencedSeriesSequence[0].ContourImageSequence = Sequence()
# [fffe,e000]
for i, value in enumerate(ImageInfoUIDs.ImageInfoList, 1):
exec("ContourImage%d = Dataset()" % i)
exec(
"ds.ReferencedFrameOfReferenceSequence[0].RTReferencedStudySequence[0].RTReferencedSeriesSequence[0].ContourImageSequence.append(ContourImage%d)"
% i)
ds.ReferencedFrameOfReferenceSequence[0].RTReferencedStudySequence[
0].RTReferencedSeriesSequence[0].ContourImageSequence[
i - 1].ReferencedSOPClassUID = value.ClassUID
ds.ReferencedFrameOfReferenceSequence[0].RTReferencedStudySequence[
0].RTReferencedSeriesSequence[0].ContourImageSequence[
i - 1].ReferencedSOPInstanceUID = value.InstanceUID
# exec("del ContourImage%d" % i)
# [3006,0020]
roiListData = planData.planROIsRawData.roiList
ds.StructureSetROISequence = Sequence()
for i, value in enumerate(roiListData, 1):
exec("ROISet%d = Dataset()" % i)
exec("ds.StructureSetROISequence.append(ROISet%d)" % i)
ds.StructureSetROISequence[i - 1].ROIName = value.name
ds.StructureSetROISequence[i - 1].ROINumber = i
ds.StructureSetROISequence[
i - 1].ReferencedFrameOfReferenceUID = structFrameUID
if 'volume' in value:
ds.StructureSetROISequence[i - 1].ROIVolume = value.volume
ds.StructureSetROISequence[
i - 1].ROIGenerationAlgorithm = value.roiinterpretedtype
# [3006,0039]get each ROI
ds.ROIContourSequence = Sequence()
for i, value in enumerate(roiListData, 1):
exec("ContourSequence%d = Dataset()" % i)
exec("ds.ROIContourSequence.append(ContourSequence%d)" % i)
ds.ROIContourSequence[i - 1].ROIDisplayColor = [0, 255, 0]
ds.ROIContourSequence[i - 1].ReferencedROINumber = i
# get all curves in current ROI
ds.ROIContourSequence[i - 1].ContourSequence = Sequence()
planROIsCurvesList = value.num_curve
# get each ROI_Curvers
for j, data in enumerate(planROIsCurvesList, 1):
exec("CurvesPoint%d = Dataset()" % j)
exec(
"ds.ROIContourSequence[i - 1].ContourSequence.append(CurvesPoint%d)"
% j)
# [3006,0040]
ds.ROIContourSequence[i - 1].ContourSequence[
j - 1].ContourImageSequence = Sequence()
coutourImage1 = Dataset()
ds.ROIContourSequence[i - 1].ContourSequence[
j - 1].ContourImageSequence.append(coutourImage1)
ds.ROIContourSequence[i - 1].ContourSequence[
j - 1].ContourImageSequence[
0].ReferencedSOPClassUID = structClassUID
ds.ROIContourSequence[i - 1].ContourSequence[
j - 1].ContourImageSequence[
0].ReferencedSOPInstanceUID = self.getCTInstanceUID(
data.Points[0], setupPosition, ImageInfoUIDs)
# [3006,0042]
ds.ROIContourSequence[i - 1].ContourSequence[
j - 1].ContourGeometricType = "CLOSED_PLANAR"
ds.ROIContourSequence[i - 1].ContourSequence[
j - 1].NumberOfContourPoints = data.num_points
# get each ROI_Curves_Points, using data.Points
ds.ROIContourSequence[i - 1].ContourSequence[
j - 1].ContourData = self.getContourCurvePoints(
data.Points, setupPosition, roiShiftVector)
# [3006,0080]
ds.RTROIObservationsSequence = Sequence()
for i, current_roi in enumerate(ds.StructureSetROISequence, 1):
exec("Observation%d = Dataset()" % i)
exec("ds.RTROIObservationsSequence.append(Observation%d)" % i)
ds.RTROIObservationsSequence[
i - 1].ObservationNumber = current_roi.ROINumber
ds.RTROIObservationsSequence[
i - 1].ReferencedROINumber = current_roi.ROINumber
ds.RTROIObservationsSequence[i - 1].RTROIInterpretedType = 'ORGAN'
ds.RTROIObservationsSequence[i - 1].ROIInterpreter = ""
# find out where to get if its been approved or not
ds.ApprovalStatus = 'UNAPPROVED'
# Set the transfer syntax
ds.is_little_endian = True
ds.is_implicit_VR = True
# # Create the FileDataset instance (initially no data elements, but file_meta supplied)
# structds = FileDataset(structfilename, {},
# file_meta=ds, preamble=b'\x00' * 128)
# structfilepath=outputfolder + patientfolder + "/" + structfilename
# structds.save_as("structfilepath")
# print("Structure file being saved\n")
ds.save_as(os.getenv('HOME') + '/PinnWork/' + structfilename)
#
# dcmds = pydicom.dcmread(ds)
# print(dcmds)
return ds
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
