def create_attribute_list(attrs):
ds = Dataset()
ds.PatientID = '12345'
ds.PatientName = 'Test^User'
for attr in attrs:
print('(VR, VM, Name, Retired, Keyword)\n', DicomDictionary.get(attr)) #
didic = DicomDictionary.get(attr)
elem = DataElement(attr, didic[0], '')
ds.add(elem)
return ds
def fix_VM1_callback(dataset, data_element):
r"""Update the data element fixing VM based on public tag definition
This addresses the following none conformance for element with string VR having
a `\` in the their value which gets interpret as array by pydicom.
This function re-join string and is aimed to be used as callback.
From the DICOM Standard, Part 5, Section 6.2, for elements with a VR of LO, such as
Series Description: A character string that may be padded with leading and/or
spaces. The character code 5CH (the BACKSLASH "\" in ISO-IR 6) shall not be
present, as it is used as the delimiter between values in multi-valued data
elements. The string shall not have Control Characters except for ESC.
Args:
dataset (pydicom.DataSet): A pydicom DataSet
data_element (pydicom.DataElement): A pydicom DataElement from the DataSet
Returns:
pydicom.DataElement: An updated pydicom DataElement
"""
vr, vm, _, _, _ = DicomDictionary.get(data_element.tag)
# Check if it is a VR string
if vr not in ['UT', 'ST', 'LT', 'FL', 'FD', 'AT', 'OB', 'OW', 'OF', 'SL', 'SQ',
'SS', 'UL', 'OB/OW', 'OW/OB', 'OB or OW', 'OW or OB', 'UN'] \
and 'US' not in vr:
if vm == '1' and hasattr(data_element, 'VM') and data_element.VM > 1:
data_element._value = '\\'.join(data_element.value)
def fix_type_based_on_dicom_vm(header):
exc_keys = []
for key, val in header.items():
try:
vr, vm, _, _, _ = DicomDictionary.get(tag_for_keyword(key))
except (ValueError, TypeError):
exc_keys.append(key)
continue
if vr != "SQ":
if vm != "1" and not isinstance(val, list): # anything else is a list
header[key] = [val]
elif vm == "1" and isinstance(val, list):
if len(val) == 1:
header[key] = val[0]
else:
if (
vr
not in [
"UT",
"ST",
"LT",
"FL",
"FD",
"AT",
"OB",
"OW",
"OF",
"SL",
"SQ",
"SS",
"UL",
"OB/OW",
"OW/OB",
"OB or OW",
"OW or OB",
"UN",
]
and "US" not in vr
):
val = cast_castable_floats(val)
header[key] = "\\".join([str(item) for item in val])
else:
for dataset in val:
if isinstance(dataset, dict):
fix_type_based_on_dicom_vm(dataset)
else:
log.warning(
"%s SQ list item is not a dictionary - value = %s", key, dataset
)
if len(exc_keys) > 0:
log.warning(
"%s Dicom data elements were not type fixed based on VM", len(exc_keys)
)
def __init__(self, file_name, IsCreate=False):
## This code block was taken from the output of a MATLAB secondary
## capture. I do not know what the long dotted UIDs mean, but
## this code works.
# Define items as (VR, VM, description, is_retired flag, keyword)
# Leave is_retired flag blank.
# Update the dictionary itself
DicomDictionary.update(self.AI_ANLAYSIS_ITEM)
if IsCreate:
self.__file_name__ = file_name
file_meta = Dataset()
# Ultrasound Multiframe Image Storage - https://www.dicomlibrary.com/dicom/sop/
file_meta.MediaStorageSOPClassUID = '1.2.840.10008.5.1.4.1.1.3.1'
file_meta.MediaStorageSOPInstanceUID = '999.999.2.19941105.134500.2.101'
file_meta.ImplementationClassUID = '999.999'
# Transfer Syntax - https://www.dicomlibrary.com/dicom/transfer-syntax/
file_meta.TransferSyntaxUID = '1.2.840.10008.1.2'
ds = FileDataset(file_name, {},
file_meta=file_meta,
preamble=b"\0" * 128)
# DICOM modality, that represents DICOM file type - https://www.dicomlibrary.com/dicom/modality/
ds.Modality = 'US' # Ultrasound
ds.ContentDate = str(datetime.date.today()).replace('-', '')
ds.ContentTime = str(time.time()) # milliseconds since the epoch
ds.StudyInstanceUID = '999.999.2.19941105.134500'
ds.SeriesInstanceUID = '999.999.2.19941105.134500.2'
ds.SOPInstanceUID = '999.999.2.19941105.134500.2.101'
# https://searchcode.com/codesearch/view/13929148/
ds.SOPClassUID = '1.2.840.10008.5.1.4.1.1.3.1' # 'Ultrasound Multi-frame Image Storage' - 1.2.840.10008.5.1.4.1.1.3.1
# ds.SecondaryCaptureDeviceManufctur = 'Python 2.7.3'
self.Dataset = ds
else:
self.Dataset = dicom.read_file(file_name)
def write(path: Path) -> None:
# read methods up to start of tag enum values
lines: List[str] = []
with open(path, "r") as f:
for line in f.readlines():
lines.append(line)
if line.strip() == MARKER:
break
# write tag enum values
with open(path, "w") as f:
f.writelines(lines)
for tag, v in DicomDictionary.items():
keyword = v[-1]
if keyword:
f.write(f" {keyword} = {tag}\n")
def fix_type_based_on_dicom_vm(header):
exc_keys = []
for key, val in header.items():
try:
vr, vm, _, _, _ = DicomDictionary.get(tag_for_keyword(key))
except (ValueError, TypeError):
exc_keys.append(key)
continue
if vr != 'SQ':
if vm != '1' and not isinstance(val,
list): # anything else is a list
header[key] = [val]
else:
for dataset in val:
fix_type_based_on_dicom_vm(dataset)
if len(exc_keys) > 0:
log.warning('%s Dicom data elements were not type fixed based on VM',
len(exc_keys))
def fix_type_based_on_dicom_vm(header):
exc_keys = []
for key, val in header.items():
try:
vr, vm, _, _, _ = DicomDictionary.get(tag_for_keyword(key))
except (ValueError, TypeError):
exc_keys.append(key)
continue
if vr != 'SQ':
if vm != '1' and not isinstance(val, list): # anything else is a list
header[key] = [val]
elif not isinstance(val, list):
# To deal with DataElement that pydicom did not read as sequence
# (e.g. stored as OB and pydicom parsing them as binary string)
exc_keys.append(key)
else:
for dataset in val:
fix_type_based_on_dicom_vm(dataset)
if len(exc_keys) > 0:
log.warning('%s Dicom data elements were not type fixed based on VM', len(exc_keys))
Add dictionary items in the standard DICOM dictionary
본 예제는 DICOM 표준 Dictionary에 어떻게 동적으로 Python Dictionary를 추가하는지 보여준다.
"""
from __future__ import print_function
from pydicom.datadict import DicomDictionary, keyword_dict
from pydicom.dataset import Dataset
print(__doc__)
new_dict_items = {
0x10011001: ('UL', '1', 'Test One', '', 'TestOne'),
0x10011002: ('OB', '1', 'Test Two', '', 'TestTwo'),
0x10011003: ('UI', '1', 'Test Three', '', 'TestThree')
}
DicomDictionary.update(new_dict_items)
new_names_dict = dict([(val[4], tag) for tag, val in new_dict_items.items()])
print(new_names_dict)
keyword_dict.update(new_names_dict)
ds = Dataset()
ds.TestOne = 42
ds.TestTwo = '12345'
ds.TestThree = '1.2.3.4.5'
print(ds.top())
""" Add DICOM Attributes not yet part of DICOM
This is from CP-1570, and should be removed once the CP becomes part of
the main standard. Note that tags may differ.
"""
from pydicom.datadict import DicomDictionary, keyword_dict
# Define items as (VR, VM, description, is_retired flag, keyword)
# Leave is_retired flag blank.
dental_acquisition_context = {
0x10011001: ('SQ', '1', "Acquisition View", '', 'AcquisitionView'),
0x10011002: ('SQ', '1', "Image View", '', 'ImageView'),
0x10011003: ('SQ', '1', "Functional condition present during"
"acquisition", '', 'FunctionalCondition'),
0x10011004:
('SQ', '1', "Occlusal Relationship", '', 'OcclusalRelationship'),
}
# Update the dictionary itself
DicomDictionary.update(dental_acquisition_context)
# Update the reverse mapping from name to tag
keyword_dict.update(
dict([(val[4], tag) for tag, val in dental_acquisition_context.items()]))
# mean the AGPL-3.0+.
# You should have received a copy of the Apache-2.0 along with this
# program. If not, see <http://www.apache.org/licenses/LICENSE-2.0>.
from copy import deepcopy
import numpy as np
from pydicom import Dataset
from pydicom.datadict import DicomDictionary
from ...libutils import get_imports
IMPORTS = get_imports(globals())
DICOM_NAMES = [item[-1] for _, item in DicomDictionary.items()]
def convert_nparray_and_set_key_value_in_dataset(dataset, key, value):
if isinstance(value, np.ndarray):
value = value.tolist()
setattr(dataset, key, value)
def dicom_dataset_from_dict(input_dict: dict, template_ds=None):
"""Create a pydicom DICOM object from a dictionary"""
if template_ds is None:
dataset = Dataset()
else:
dataset = deepcopy(template_ds)
from pydicom.datadict import DicomDictionary, keyword_dict
from pydicom.dataset import Dataset
print(__doc__)
# Define items as (VR, VM, description, is_retired flag, keyword)
# Leave is_retired flag blank.
new_dict_items = {
0x10011001: ('UL', '1', "Test One", '', 'TestOne'),
0x10011002: ('OB', '1', "Test Two", '', 'TestTwo'),
0x10011003: ('UI', '1', "Test Three", '', 'TestThree'),
}
# Update the dictionary itself
DicomDictionary.update(new_dict_items)
# Update the reverse mapping from name to tag
new_names_dict = dict([(val[4], tag) for tag, val in
new_dict_items.items()])
keyword_dict.update(new_names_dict)
# Test that it is working
ds = Dataset() # or could get one from dcmread, etc
ds.TestOne = 42
ds.TestTwo = '12345'
ds.TestThree = '1.2.3.4.5'
print(ds.top())
#!/usr/bin/python3
# Gets a list of tags from the pyDicom dictionary
import csv
import pydicom
from pydicom.datadict import DicomDictionary
keyList = list(DicomDictionary.keys())
keyList.sort()
tagsAndKeywords = len(keyList) * [None]
for i in range(len(keyList)):
hexKey = '%08X' % keyList[i]
tag = '(' + hexKey[0:4] + ',' + hexKey[4:] + ')'
tagsAndKeywords[i] = [tag, DicomDictionary[keyList[i]][4]]
# Add header
tagsAndKeywords.insert(0, ['Tag', 'Keyword'])
with open('pydicomTags.csv', 'w') as csvFile:
writer = csv.writer(csvFile)
writer.writerows(tagsAndKeywords)
csvFile.close()
def table_dicom_data(dicom_tree):
if VERBOSE > 1:
print_this(currLog,
st.RESET_ALL + fg.GREEN + '* VISITING' + st.RESET_ALL)
new_dict_items = {
0x0021105e:
('DS', '1', "FloatSlopRTIATimer", '', 'FloatSlopRTIATimer'),
0x00181060: ('DS', '1', "TriggerTime", '', 'TriggerTime'),
}
DicomDictionary.update(new_dict_items)
new_names_dict = dict([(val[4], tag)
for tag, val in new_dict_items.items()])
keyword_dict.update(new_names_dict)
props = [
'Path',
'NumFiles',
'StudyID',
'StudyDate',
'StudyTime',
'PatientID',
'PatientName',
'ProtocolName',
'SeriesDescription',
'SeriesNumber',
'SeriesTime',
'ImagesInAcquisition',
'InStackPositionNumber',
'InstanceNumber',
'SliceLocation',
'TriggerTime',
'FloatSlopRTIATimer',
]
db = OrderedDict([(ii, []) for ii in props])
if isinstance(dicom_tree, dict):
for dicom in dicom_tree:
if isinstance(dicom_tree[dicom], dict):
for patient in dicom_tree[dicom]:
if isinstance(dicom_tree[dicom][patient], dict):
for exam in dicom_tree[dicom][patient]:
if isinstance(dicom_tree[dicom][patient][exam],
dict):
for serie in dicom_tree[dicom][patient][exam]:
if isinstance(
dicom_tree[dicom][patient][exam]
[serie], dict):
for fn in dicom_tree[dicom][patient][
exam][serie]:
if VERBOSE > 1:
print_this(
currLog, fg.CYAN + ' ' +
fn + st.RESET_ALL)
ds = pydicom.dcmread(
fn, stop_before_pixels=True)
ds.decode()
for prop in props:
if prop == 'Path':
db[prop] += [
os.path.dirname(fn)
]
elif prop == 'NumFiles':
db[prop] += [
len(
glob.glob(
os.path.
dirname(fn) +
'/*'))
]
else:
db[prop] += [
''
] if not hasattr(
ds, prop) else [
getattr(ds, prop)
]
if False:
print_this(currLog, str(db))
if False:
print_this(currLog, str(ds))
df = pd.DataFrame(db)
df = df.sort_values(by=['StudyID', 'SeriesNumber', 'InstanceNumber'],
axis=0)
if not args.include_stacked_screen_saves:
df = df[df.SeriesDescription.str.contains("Stacked Screen Save") ==
False]
df = df[df.SeriesDescription.str.contains("Screen Save") == False]
if not args.keep_sequence_information:
# Trim path.
df.Path = df.Path.apply(lambda xx: os.path.dirname(xx))
# Remove duplicates (must be done AFTER path trimming).
df = df.drop_duplicates(subset='Path', keep="last").reset_index()
if not args.more_info:
# df = df.drop(labels='index', axis='columns')
df = df.drop(labels='SeriesDescription', axis='columns')
df = df.drop(labels='SeriesNumber', axis='columns')
df = df.drop(labels='SeriesTime', axis='columns')
df = df.drop(labels='NumFiles', axis='columns')
if not args.report_files:
df = df.drop(labels='ImagesInAcquisition', axis='columns')
df = df.drop(labels='InStackPositionNumber', axis='columns')
df = df.drop(labels='InstanceNumber', axis='columns')
df = df.drop(labels='SliceLocation', axis='columns')
df = df.drop(labels='FloatSlopRTIATimer', axis='columns')
df = df.drop(labels='TriggerTime', axis='columns')
print_this(currLog, st.RESET_ALL + fg.GREEN + '* TABLE' + st.RESET_ALL)
print_this(currLog, tabulate(df, headers='keys', tablefmt="orgtbl"))
if args.write_csv:
fn = args.log_file
df.to_csv(path_or_buf=rchop(fn, '.org') + '.csv', sep=',')