def write_header_cbct(ct, cbct, mid_slice, nSlices_wrong, path, output_prefix):
# resample ct to cbct resolution
new_volume = resample(ct, cbct)
# new_z = resample_z( ct, cbct)
new_cbct_images = cbct.images.copy()
if not os.path.exists(path):
os.mkdir(path)
# CT_len = len( ct.images)
#find the start slice in resample CT volume and cut from theree
#due to resample
new_mid_slice = mid_slice * len(new_volume) // len(ct.images)
#number of slices in syth CBCT must be equal to CBCT
nSlices = len(cbct.images)
offset = new_mid_slice - nSlices // 2
# copy from ct to cbct
startUID = random.randint(1, 1000)
incUID = random.randint(1, 1000)
#get current date
today = date.today()
dd = today.strftime('%Y%m%d')
for i in range(nSlices):
new_cbct_image = new_cbct_images[i]
# new_cbct_image.pixel_array[:] = ct.images[i + offset].pixel_array[:]
new_cbct_image.pixel_array[:] = new_volume[i + offset]
new_cbct_image.PixelData = new_cbct_image.pixel_array.tobytes()
# change UID
# the matter here is the '2.' to make Aria think this is a new study of new patient
# Aria still can locate to the exist patient but also have the option of create a new one
new_cbct_image.SOPInstanceUID = str(
startUID) + new_cbct_image.SOPInstanceUID
new_cbct_image.StudyInstanceUID = str(
startUID + incUID) + new_cbct_image.StudyInstanceUID
new_cbct_image.SeriesInstanceUID = str(
startUID) + new_cbct_image.SeriesInstanceUID
# new_cbct_image.PatientID = "Pydicom2"
#change the Date of creation so that it's display on Eclipse
new_cbct_image.SeriesDate = dd
new_cbct_image.AcquisitionDate = dd
new_cbct_image.ContentDate = dd
# change slope and intercept
new_cbct_image.RescaleIntercept = ct.images[0].RescaleIntercept
new_cbct_image.RescaleSlope = ct.images[0].RescaleSlope
new_cbct_image.HighBit = ct.images[0].HighBit
# write
dicom.dcmwrite(os.path.join(path, output_prefix + str(i) + '.dcm'),
new_cbct_image)
return new_cbct_images
def datasetToBinary(ds: Dataset):
fix_meta_info(ds)
with DicomBytesIO() as dcmfile:
dcmwrite(dcmfile, ds, write_like_original=False)
dcmfile.seek(0)
return dcmfile.read()
def test_retrieve_series(client, httpserver, cache_dir):
cache_filename = str(cache_dir.joinpath('file.dcm'))
with open(cache_filename, 'rb') as f:
payload = f.read()
content = b''
for i in range(3):
content += b'\r\n--boundary\r\n'
content += b'Content-Type: application/dicom\r\n\r\n'
content += payload
content += b'\r\n--boundary--'
headers = {
'content-type': ('multipart/related; '
'type="application/dicom"; '
'boundary="boundary" '),
}
httpserver.serve_content(content=content, code=200, headers=headers)
study_instance_uid = '1.2.3'
series_instance_uid = '1.2.4'
sop_instance_uid = '1.2.5'
results = client.retrieve_series(study_instance_uid, series_instance_uid)
results = list(results)
assert len(results) == 3
for result in results:
with BytesIO() as fp:
pydicom.dcmwrite(fp, result)
raw_result = fp.getvalue()
assert raw_result == payload
request = httpserver.requests[0]
expected_path = (
'/studies/{study_instance_uid}/series/{series_instance_uid}'.format(
**locals()))
assert request.path == expected_path
assert request.accept_mimetypes[0][0][:43] == headers['content-type'][:43]
def test_retrieve_instance(httpserver, client, cache_dir):
cache_filename = str(cache_dir.joinpath('file.dcm'))
with open(cache_filename, 'rb') as f:
data = f.read()
media_type = 'application/dicom'
boundary = 'boundary'
headers = {
'content-type': ('multipart/related; '
f'type="{media_type}"; '
f'boundary="{boundary}"'),
}
message = DICOMwebClient._encode_multipart_message(
content=[data], content_type=headers['content-type'])
httpserver.serve_content(content=message, code=200, headers=headers)
study_instance_uid = '1.2.3'
series_instance_uid = '1.2.4'
sop_instance_uid = '1.2.5'
response = client.retrieve_instance(study_instance_uid,
series_instance_uid, sop_instance_uid)
with BytesIO() as fp:
pydicom.dcmwrite(fp, response)
raw_result = fp.getvalue()
assert raw_result == data
request = httpserver.requests[0]
expected_path = (f'/studies/{study_instance_uid}'
f'/series/{series_instance_uid}'
f'/instances/{sop_instance_uid}')
assert request.path == expected_path
assert request.accept_mimetypes[0][0][:43] == headers['content-type'][:43]
def test_retrieve_instance(httpserver, client, cache_dir):
cache_filename = str(cache_dir.joinpath('file.dcm'))
with open(cache_filename, 'rb') as f:
content = f.read()
headers = {
'content-type': (
'multipart/related; '
'type="application/dicom"'
),
}
httpserver.serve_content(content=content, code=200, headers=headers)
study_instance_uid = '1.2.3'
series_instance_uid = '1.2.4'
sop_instance_uid = '1.2.5'
result = client.retrieve_instance(
study_instance_uid, series_instance_uid, sop_instance_uid
)
with BytesIO() as fp:
pydicom.dcmwrite(fp, result)
raw_result = fp.getvalue()
assert raw_result == content
request = httpserver.requests[0]
expected_path = (
'/studies/{study_instance_uid}/series/{series_instance_uid}/instances'
'/{sop_instance_uid}'.format(**locals())
)
assert request.path == expected_path
assert request.accept_mimetypes[0][0][:43] == headers['content-type'][:43]
def add_tag(image, tag):
# add tag and save in another folder (target)
#print(image, 'from add tag')
img = pyd.dcmread(image)
img.AccessionNumber = tag
img.ImageComments = tag
img.StudyID = tag
pyd.dcmwrite(image, img)
def bufferize_instance(instance: Dataset,
force=True,
write_like_original=True):
"""Makes a copy of the ``instance``. Faster than deepcopy."""
with BytesIO() as buffer:
dcmwrite(buffer, instance, write_like_original=write_like_original)
buffer.seek(0)
return dcmread(buffer, force=force)
def image_downsampling(im, work_dir='C:\\Users\\Haimin\\Dicom\\01'):
# os.chdir(work_dir)
ds = pyd.dcmread(im)
data = ds.pixel_array
data_downsampling = data[::8, ::8]
ds.PixelData = data_downsampling.tostring()
ds.Rows, ds.Columns = data_downsampling.shape
pyd.dcmwrite(im, ds)
print('convert from {} to {}'.format(data.shape, data_downsampling.shape))
def restruct(src, dest):
"""
Puts all data directly under dest folder
src: source folder. All data will be searched recursively in it
dest: destination folder
"""
for fn in src.glob('**/*dcm'):
ds = pydicom.dcmread(str(fn))
pydicom.dcmwrite(str(dest / fn.name), ds)
def write_header_ct(ct, mid_slice, nSlices, path, output_prefix):
offset = mid_slice - nSlices // 2
new_cbct_images = []
for i in range(nSlices):
new_cbct_image = ct.images[i + offset]
new_cbct_images.append(new_cbct_image)
dicom.dcmwrite(os.path.join(path, output_prefix + str(i) + '.dcm'),
new_cbct_image)
return new_cbct_images
def write_dataset_to_bytes(dataset):
# 버퍼 생성
with BytesIO() as buffer:
# DicomFileLike 오브젝트 생성
memory_dataset = DicomFileLike(buffer)
dcmwrite(memory_dataset, dataset)
memory_dataset.seek(0)
return memory_dataset.read()
def preprocessing(self):
os.chdir(self.workdir)
for name in os.listdir(self.workdir):
ds = pyd.dcmread(name)
data = ds.pixel_array
data_downsampling = data[::8, ::8] # downsize in 8 times
ds.PixelData = data_downsampling.tostring()
ds.Rows, ds.Columns = data_downsampling.shape
ds.AccessionNumber = '01'
pyd.dcmwrite(name, ds)
print('tag added and reshaped to', name)
def write_dataset_to_bytes(dataset):
# create a buffer
with BytesIO() as buffer:
# create a DicomFileLike object that has some properties of DataSet
memory_dataset = DicomFileLike(buffer)
# write the dataset to the DicomFileLike object
dcmwrite(memory_dataset, dataset)
# to read from the object, you have to rewind it
memory_dataset.seek(0)
# read the contents as bytes
return memory_dataset.read()
def write_dataset_to_bytes(dataset):
# 버퍼를 생성한다.
with BytesIO() as buffer:
# Dataset의 속성들을 담을 DicomFileLike 객체를 만든다.
memory_dataset = DicomFileLike(buffer)
# Dataset을 DicomFileLike 객체에 write 한다.
dcmwrite(memory_dataset, dataset)
# 객체에서 읽어오기 위해 rewind 한다.
memory_dataset.seek(0)
# 바이트로 읽어서 리턴한다.
return memory_dataset.read()
def create_rs(self ):
'''
contours: structure need to be stored in dicom
:param dc:
:param generic_rs:
:param contours:
:return:
'''
self.copy_info( )
self.copy_contours( )
# self.copy_from_rs()
dicom.dcmwrite( self.rs.rs_file, self.rs.structure)
def to_bytes(dcm: pydicom.dataset.FileDataset):
"""Converts dicom object to byte sequence,
source https://pydicom.github.io/pydicom/dev/auto_examples/memory_dataset.html"""
with BytesIO() as buffer:
memory_dataset = DicomFileLike(
buffer
) # create a DicomFileLike object that has some properties of DataSet
dcmwrite(memory_dataset,
dcm) # write the dataset to the DicomFileLike object
memory_dataset.seek(
0) # to read from the object, you have to rewind it
return memory_dataset.read() # read the contents as bytes
def generate_images_for_single_image_masks(dicom_images, inference_results,
response_json, output_folder):
""" This function will save images to disk to preview how a mask looks on the input images.
It saves one image for each input DICOM file with the corresponding `inference_results` mask
applied as overlay.
- dicom_images: Array of DCM_Image or path to a folder with images
- inference_results: Array with mask buffers (one for each image)
- response_json: The JSON response from the inference server
- output_folder: Where the output images will be saved
The difference with `generate_images_with_masks` is that `generate_images_with_masks` applies each mask to the whole
volume while this functions applies each mask to one image.
"""
images, masks = _get_images_and_masks(dicom_images, inference_results)
create_folder(output_folder)
# Filter out secondary capture outputs
all_mask_parts = filter_mask_parts(response_json)
binary_masks, secondary_captures = filter_masks_by_binary_type(
masks, all_mask_parts, response_json)
# Create DICOM files for secondary capture outputs
for index, sc in enumerate(secondary_captures):
dcm = pydicom.read_file(BytesIO(sc.tobytes()))
file_path = os.path.join(output_folder, 'sc_' + str(index) + '.dcm')
pydicom.dcmwrite(file_path, dcm)
for index, (image, mask, json_part) in enumerate(
zip(images, binary_masks, all_mask_parts)):
dcm = pydicom.dcmread(image.path)
pixels = get_pixels(dcm)
# Reshape and add alpha
pixels = np.reshape(pixels, (-1, 3))
pixels = np.hstack(
(pixels,
np.reshape(np.full(pixels.shape[0], 255, dtype=np.uint8),
(-1, 1))))
# get mask for this image
pixels = _draw_mask_on_image(pixels, mask, json_part, response_json,
index, 0)
# write image to output folder
output_filename = os.path.join(
output_folder,
str(index) + '_' + os.path.basename(os.path.normpath(image.path)))
output_filename += '.png'
pixels = np.reshape(pixels, (dcm.Rows, dcm.Columns, 4))
plt.imsave(output_filename, pixels)
def _send_c_move(self, move_dataset, output_dir):
if self.process.returncode is not None:
msg = 'dcmrecv is not running, rc {self.process.returncode}'
logger.error(msg)
raise Exception(msg)
with tempfile.TemporaryDirectory() as tmpdirname:
move_dataset_path = os.path.join(tmpdirname, 'move_dataset.dcm')
os.makedirs(output_dir, exist_ok=True)
move_dataset.is_little_endian = True
move_dataset.is_implicit_VR = True
pydicom.dcmwrite(move_dataset_path, move_dataset)
# even though storescp has `--fork`, the move lock is needed to tell datasets
# apart in the `dicom_tmp_dir`
with move_lock:
movescu_args = [
'movescu',
'--aetitle',
self.client_ae,
'--call',
self.remote_ae,
'--move',
self.client_ae,
'-S', # study query level
*self.timeout_args,
*self.logger_args,
*self.movescu_extra_args,
self.pacs_url,
self.pacs_port,
move_dataset_path
]
result = subprocess.run(movescu_args,
stdout=PIPE,
stderr=PIPE,
universal_newlines=True)
logger.debug(result.args)
logger.debug(result.stdout)
logger.debug(result.stderr)
for result_item in os.listdir(self.dicom_tmp_dir):
# fully specify move destination to allow overwrites
shutil.move(os.path.join(self.dicom_tmp_dir, result_item),
os.path.join(output_dir, result_item))
if result.returncode != 0:
logger.error(
f'C-MOVE failure for query: rc {result.returncode}')
return False
return True
def create_rs(new_rs_file, structure, contours):
#update structure
#update structure name
distort_contour_names = contours.keys()
for i in range(len(structure.ROIContourSequence)):
contour_name = structure.StructureSetROISequence[i].ROIName
if contour_name in distort_contour_names:
S = structure.ROIContourSequence[i].ContourSequence
for slice_index in range( len(contours[contour_name]['contour'])):
S[slice_index].ContourData = list( contours[contour_name]['contour'][slice_index])
pydicom.dcmwrite( new_rs_file, structure)
def save_segmentation(self):
images, filenames, raw_data = self.dicom_reader.get_dataset()
path = "segmented_images"
if os.path.isdir('./' + path):
shutil.rmtree('./' + path)
os.mkdir(path)
os.chdir('./' + path)
for image, filename, raw in zip(images, filenames, raw_data):
raw.PixelData = image #self.dicom_processing.segmentation(image)
pydicom.dcmwrite(filename, raw)
os.chdir('../')
return path
def convert2ugly(src_path, ugly_path_fn, src_type_list=False):
"""
Converts contents of folder (if all dicom) to jpeg or PNG
and saves to specified destination.
input args:
src_path = Specify the .dcm folder path
dst_path = Specify the output folder path
"""
if src_type_list == True:
images_path = src_path
else:
images_path = os.listdir(src_path)
bar = ProgBar('Converting', max=len(images_path))
make_ugly = uglifier()
for n, image in enumerate(images_path):
if src_type_list == True:
src_path_img = image
src_path = os.path.dirname(image)
image = os.path.basename(image)
else:
src_path_img = os.path.join(src_path, image)
try:
ds = pydicom.dcmread(str(src_path_img), force=True)
data = ds.pixel_array
original_type = data.dtype
#pixel_array_numpy = rescale_array(data)
#ugly_array_numpy = make_ugly.apply_transforms(pixel_array_numpy)
ugly_array_numpy = make_ugly.apply_transforms(data)
if src_type_list == True:
ugly_path = ugly_path_fn(src_path_img)
else:
ugly_path = os.path.join(ugly_path_fn, image)
ugly_img_src = os.path.dirname(ugly_path)
if not os.path.exists(ugly_img_src):
os.makedirs(ugly_img_src)
ds.PixelData = ugly_array_numpy.astype(original_type).tobytes()
ds.Rows, ds.Columns = ugly_array_numpy.shape
pydicom.dcmwrite(ugly_path, ds, write_like_original=True)
except:
print(image)
bar.next()
bar.finish()
def create_train(full_size_path, path, size):
"""
Create size-specific train folder with resized images
full_size_path: path to train folder with full size images
path: path to destination folder
size: size to which images are to be resize
"""
for fn in full_size_path.glob('**/*dcm'):
ds = pydicom.dcmread(str(fn))
img = ds.pixel_array
img = cv2.resize(img, (size, size), interpolation=cv2.INTER_AREA)
ds.decompress()
ds.PixelData = img.tobytes()
ds.Rows, ds.Columns = img.shape
pydicom.dcmwrite(str(path / fn.name), ds)
def create_rs_very_limited(new_rs_file, structure, contours):
#update structure
#update structure name
structure.StructureSetLabel = "BladderandRectum"
structure.StructureSetName = 'BladderandRectum'
structure.SOPInstanceUID = '1.2.826.0.1.3680043.8.498.67063073255766457385690235251075316643'
distort_contour_names = distort_params.keys()
for i in range(len(structure.ROIContourSequence)):
contour_name = structure.StructureSetROISequence[i].ROIName
if contour_name in distort_contour_names:
S = structure.ROIContourSequence[i].ContourSequence
for slice_index in range( len(contours[contour_name]['contour'])):
S[slice_index].ContourData = list( contours[contour_name]['contour'][slice_index])
pydicom.dcmwrite( new_rs_file, structure)
def test_retrieve_instance_singlepart(httpserver, client, cache_dir):
cache_filename = str(cache_dir.joinpath('file.dcm'))
with open(cache_filename, 'rb') as f:
data = f.read()
headers = {'content-type': 'application/dicom'}
httpserver.serve_content(content=data, code=200, headers=headers)
study_instance_uid = '1.2.3'
series_instance_uid = '1.2.4'
sop_instance_uid = '1.2.5'
response = client.retrieve_instance(study_instance_uid,
series_instance_uid, sop_instance_uid)
with BytesIO() as fp:
pydicom.dcmwrite(fp, response)
raw_result = fp.getvalue()
assert raw_result == data
request = httpserver.requests[0]
assert request.accept_mimetypes[0][0].startswith('multipart/related')
def test_iter_series(client, httpserver, cache_dir):
cache_filename = str(cache_dir.joinpath('file.dcm'))
with open(cache_filename, 'rb') as f:
data = f.read()
n_resources = 3
chunk_size = 10**3
media_type = 'application/dicom'
boundary = 'boundary'
headers = {
'content-type': (
'multipart/related; '
f'type="{media_type}"; '
f'boundary="{boundary}"'
),
'transfer-encoding': 'chunked'
}
message = DICOMwebClient._encode_multipart_message(
content=[data for _ in range(n_resources)],
content_type=headers['content-type']
)
chunked_message = _chunk_message(message, chunk_size)
httpserver.serve_content(content=chunked_message, code=200, headers=headers)
study_instance_uid = '1.2.3'
series_instance_uid = '1.2.4'
iterator = client.iter_series(
study_instance_uid, series_instance_uid
)
assert isinstance(iterator, Generator)
response = list(iterator)
for instance in response:
with BytesIO() as fp:
pydicom.dcmwrite(fp, instance)
raw_result = fp.getvalue()
assert raw_result == data
request = httpserver.requests[0]
expected_path = (
f'/studies/{study_instance_uid}'
f'/series/{series_instance_uid}'
)
assert request.path == expected_path
assert request.accept_mimetypes[0][0][:43] == headers['content-type'][:43]
assert len(response) == n_resources
def write_dicom():
# load results
str = '2019-07-22-14h,post'
output_image = np.load(
os.path.join(os.getcwd(), 'npy', str + ',output.npy'))
# convert results into int16
output_image -= np.min(output_image)
output_image /= np.max(output_image)
output_image *= 255
output_image = output_image.astype('uint16')
# write dicoms
dicom_dir = '/Volumes/MRIClinical/Ricardo/BRAVO-newcases'
exam_dir = '38069839/33224249/D2019_07_22/MR'
series_dir = 'S0011_Axial BRAVO x4 acc'
utils.makedirs(os.path.join(dicom_dir, exam_dir, series_dir))
for i in range(output_image.shape[2]):
file = 'ax-2,sl-{:03d}.dcm'.format(i)
write_dicom(output_image[:, :, i],
os.path.join(dicom_dir, exam_dir, series_dir, file))
return
# load one dicom
dicom_dir = '/Volumes/MRIClinical/Ricardo/BRAVO-newcases'
exam_dir = '38069839/33224249/D2019_07_22/MR'
series_dir = 'S0011_Axial BRAVO'
file = 'img_0001_2.789.dcm'
ds = pydicom.dcmread(os.path.join(dicom_dir, exam_dir, series_dir, file))
# modify metadata
ds.Columns = output_image.shape[0]
ds.Rows = output_image.shape[1]
ds.SeriesDescription = u'Axial BRAVO x4 acc'
# write new dicoms
series_dir = 'S0012_Axial BRAVO 4x-acc'
utils.makedirs(os.path.join(dicom_dir, exam_dir, series_dir))
for i in range(output_image.shape[2]):
ds.PixelData = output_image[:, :, i].tostring()
file = 'ax-2,sl-{:03d}.dcm'.format(i)
pydicom.dcmwrite(os.path.join(dicom_dir, exam_dir, series_dir, file),
ds,
write_like_original=False)
async def dcmhandler(channel, ds, uri, routing_key):
if not Tag(
"ImageType"
) in ds or not "RESAMPLED" in ds.ImageType: #only convert resampled data
print(
f"dicom2nii: {uri} ({ds.SeriesDescription}) is not a resampled image"
)
return
print(f"nii2dicom: converting {uri}")
ni = nb.load(uri)
dicoms = nii2dicom(ni, ds)
refds = dicoms[0]
outdir = f"{os.environ['HOME']}/.dcmq/derived/{refds.StudyInstanceUID}/{refds.SeriesInstanceUID}"
pathlib.Path(outdir).mkdir(parents=True, exist_ok=True)
for dcm in dicoms:
filepath = outdir + "/" + dcm.SOPInstanceUID
dcmwrite(filepath, dcm, write_like_original=False)
await publish(channel, "stored.instance", dcm, uri=filepath)
await publish(channel, "stored.series", refds, uri=outdir)
def __filter_dcm_anonym(self, ds, old_path):
ds.PatientName = ""
ds.PatientBirthDate = ""
ds.PatientSex = ""
ds.PatientAddress = ""
ds.ReferringPhysicianName = ""
ds.InstitutionName = ""
ds.OperatorsName = ""
ds.InstitutionalDepartmentName = ""
ds.StudyDate = ""
ds.SeriesDate = ""
ds.ContentDate = ""
ds.AcquisitionDate = ""
ds.InstanceCreationDate = ""
ds.AccessionNumber = ""
ds.StudyID = ""
ds.ScheduledProcedureStepID = ""
ds.RequestedProcedureID = ""
ds.PatientID = ""
dicom.dcmwrite(old_path, ds)
def FilterDicom(dicomPath, stlfilepath, savepath, orderdir):
new_path = savepath
# 读取dicom文件
dicomImageData, m_Origin = ReadDicomFile(dicomPath)
# 读取stl
stlmapImageData = processStlToImageData(dicomImageData, m_Origin,
stlfilepath)
# 处理文件夹
checkAndMakeDir(new_path)
# 获取stl和dicom的array数据
count, dicomArray, stlmapArray = getResharpedAryFromImageData(
dicomImageData, stlmapImageData)
# count等于0代表读取image文件存在问题
if count == 0:
print("folder " + orderdir + " image size error!")
return
dicomshape = dicomArray.shape
dicomfiles = os.listdir(dicomPath)
# 操作numpy数据
for i in range(dicomshape[0]):
train = stlmapArray[i, :, :]
# 上下镜像翻转
train = train[::-1]
train = np.where(train > 135, 1, 0)
if np.any(train > 0):
ori = dicomArray[i, :, :]
ori = ori[::-1]
dicom_full_path = os.path.join(dicomPath, dicomfiles[i])
ds = pydicom.dcmread(dicom_full_path)
# 还原回无符号的正整数
new = (ori - ds.RescaleIntercept) / ds.RescaleSlope
# 与label相乘
ori = ori * train.astype(np.uint16)
new = new * train.astype(np.uint16)
new = new.astype(np.uint16)
ds.PixelData = new.tostring()
pydicom.dcmwrite(dicom_full_path.replace(dicomPath, savepath), ds)
io.imsave(new_path + orderdir + '-' + addPadding(str(i)) + '.png',
winchange(ori, 0, 1000))
print("folder " + orderdir + " done!")
async def get(channel, ds):
with tempfile.TemporaryDirectory() as tmpdirname:
dcmpath = str(join(tmpdirname, "tmp.dcm"))
pydicom.dcmwrite(dcmpath, ds)
print(ds)
if dimse_mode == "MOVE":
cmd = f"movescu -v -aet {calling_ae} -aec {server_ae} -S -od {tmpdirname} --port {move_dest_port} {server_ip} {server_port} {dcmpath}"
else:
cmd = f"getscu -v -aet {calling_ae} -aec {server_ae} -S -od {tmpdirname} {server_ip} {server_port} {dcmpath}"
print(cmd)
os.system(cmd)
onlyfiles = [
f for f in listdir(tmpdirname) if isfile(join(tmpdirname, f))
]
for f in onlyfiles:
if f == "tmp.dcm":
continue
tmpfilepath = str(join(tmpdirname, f))
newds = pydicom.dcmread(tmpfilepath, stop_before_pixels=True)
filepath = getFilename(newds)
movefile(tmpfilepath, filepath)
await publish(channel, "stored.instance", newds, uri=filepath)
def save_as(self, filename, write_like_original=True):
"""Write the Dataset to `filename`.
Saving a Dataset requires that the Dataset.is_implicit_VR and
Dataset.is_little_endian attributes exist and are set appropriately. If
Dataset.file_meta.TransferSyntaxUID is present then it should be set to
a consistent value to ensure conformance.
Conformance with DICOM File Format
----------------------------------
If `write_like_original` is False, the Dataset will be stored in the
DICOM File Format in accordance with DICOM Standard Part 10 Section 7.
To do so requires that the `Dataset.file_meta` attribute exists and
contains a Dataset with the required (Type 1) File Meta Information
Group elements (see pydicom.filewriter.dcmwrite and
pydicom.filewriter.write_file_meta_info for more information).
If `write_like_original` is True then the Dataset will be written as is
(after minimal validation checking) and may or may not contain all or
parts of the File Meta Information (and hence may or may not be
conformant with the DICOM File Format).
Parameters
----------
filename : str or file-like
Name of file or the file-like to write the new DICOM file to.
write_like_original : bool
If True (default), preserves the following information from
the Dataset (and may result in a non-conformant file):
- preamble -- if the original file has no preamble then none will
be written.
- file_meta -- if the original file was missing any required File
Meta Information Group elements then they will not be added or
written.
If (0002,0000) 'File Meta Information Group Length' is present
then it may have its value updated.
- seq.is_undefined_length -- if original had delimiters, write them
now too, instead of the more sensible length characters
- is_undefined_length_sequence_item -- for datasets that belong to
a sequence, write the undefined length delimiters if that is
what the original had.
If False, produces a file conformant with the DICOM File Format,
with explicit lengths for all elements.
See Also
--------
pydicom.filewriter.write_dataset
Write a DICOM Dataset to a file.
pydicom.filewriter.write_file_meta_info
Write the DICOM File Meta Information Group elements to a file.
pydicom.filewriter.dcmwrite
Write a DICOM file from a FileDataset instance.
"""
# Ensure is_little_endian and is_implicit_VR exist
if not (hasattr(self, 'is_little_endian') and
hasattr(self, 'is_implicit_VR')):
raise AttributeError("'{0}.is_little_endian' and "
"'{0}.is_implicit_VR' must exist and be "
"set appropriately before "
"saving.".format(self.__class__.__name__))
pydicom.dcmwrite(filename, self, write_like_original)