我最近开始使用 SimpleITK 来修改一些 Dicom 图像。但是，我无法修改元数据。事实上，我什至无法访问它。
我知道感谢我在这里找到的脚本：https ://github.com/SimpleITK/SimpleITK/pull/262/files?diff= split 默认情况下不加载元数据，因为它减慢了进程。我也知道要加载元数据，我应该使用阅读器的以下方法：“.LoadPrivateTagsOn()”。
但是，每当我在图像对象上使用“.GetMetaDataKeys()”方法时，它都会返回一个空元组。我希望下面的代码能给我一些键，但它没有。
#=========================================================================
#
# Copyright Insight Software Consortium
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0.txt
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
#=========================================================================
from __future__ import print_function
import SimpleITK as sitk
import sys, time, os
import numpy as np
# if len( sys.argv ) < 2:
# print( "Usage: python " + __file__ + "<output_directory>" )
# sys.exit ( 1 )
# Create a new series from a numpy array
new_arr = np.random.uniform(-10, 10, size = (3,4,5)).astype(np.int16)
new_img = sitk.GetImageFromArray(new_arr)
new_img.SetSpacing([2.5,3.5,4.5])
directory = r"C:\Users\jeroen\Documents\2eMaster\Reconstruction3D\Projet Femur\Dicom\test"
# Write the 3D image as a series
# IMPORTANT: There are many DICOM tags that need to be updated when you modify an
# original image. This is a delicate opration and requires knowlege of
# the DICOM standard. This example only modifies some. For a more complete
# list of tags that need to be modified see:
# http://gdcm.sourceforge.net/wiki/index.php/Writing_DICOM
writer = sitk.ImageFileWriter()
# Use the study/series/frame of reference information given in the meta-data
# dictionary and not the automatically generated information from the file IO
writer.KeepOriginalImageUIDOn()
# Copy relevant tags from the original meta-data dictionary (private tags are also
# accessible).
tags_to_copy = ["0010|0010", # Patient Name
"0010|0020", # Patient ID
"0010|0030", # Patient Birth Date
"0020|000D", # Study Instance UID, for machine consumption
"0020|0010", # Study ID, for human consumption
"0008|0020", # Study Date
"0008|0030", # Study Time
"0008|0050", # Accession Number
"0008|0060" # Modality
]
modification_time = time.strftime("%H%M%S")
modification_date = time.strftime("%Y%m%d")
# Copy some of the tags and add the relevant tags indicating the change.
# For the series instance UID (0020|000e), each of the components is a number, cannot start
# with zero, and separated by a '.' We create a unique series ID using the date and time.
# tags of interest:
direction = new_img.GetDirection()
print(new_img.HasMetaDataKey("0008|0021"))
series_tag_values = [(k, new_img.GetMetaData(k)) for k in tags_to_copy if new_img.HasMetaDataKey(k)] + \
[("0008|0031",modification_time), # Series Time
("0008|0021",modification_date), # Series Date
("0008|0008","DERIVED\\SECONDARY"), # Image Type
("0020|000e", "1.2.826.0.1.3680043.2.1125."+modification_date+".1"+modification_time), # Series Instance UID
("0020|0037", '\\'.join(map(str, (direction[0], direction[3], direction[6],# Image Orientation (Patient)
direction[1],direction[4],direction[7])))),
("0008|103e", "Created-SimpleITK")] # Series Description
print(new_img.GetMetaDataKeys())
for i in range(new_img.GetDepth()):
image_slice = new_img[:,:,i]
# Tags shared by the series.
for tag, value in series_tag_values:
image_slice.SetMetaData(tag, value)
# Slice specific tags.
image_slice.SetMetaData("0008|0012", time.strftime("%Y%m%d")) # Instance Creation Date
image_slice.SetMetaData("0008|0013", time.strftime("%H%M%S")) # Instance Creation Time
image_slice.SetMetaData("0008|0060", "CT") # set the type to CT so the thickness is carried over
image_slice.SetMetaData("0020|0032", '\\'.join(map(str,new_img.TransformIndexToPhysicalPoint((0,0,i))))) # Image Position (Patient)
image_slice.SetMetaData("0020,0013", str(i)) # Instance Number
# Write to the output directory and add the extension dcm, to force writing in DICOM format.
writer.SetFileName(os.path.join(directory,str(i)+'.dcm'))
writer.Execute(image_slice)
print(new_img.GetMetaDataKeys())
# Re-read the series
# Read the original series. First obtain the series file names using the
# image series reader.
data_directory = directory
series_IDs = sitk.ImageSeriesReader.GetGDCMSeriesIDs(data_directory)
if not series_IDs:
print("ERROR: given directory \""+data_directory+"\" does not contain a DICOM series.")
sys.exit(1)
series_file_names = sitk.ImageSeriesReader.GetGDCMSeriesFileNames(data_directory, series_IDs[0])
series_reader = sitk.ImageSeriesReader()
series_reader.SetFileNames(series_file_names)
# Configure the reader to load all of the DICOM tags (publicprivate):
# By default tags are not loaded (saves time).
# By default if tags are loaded, the private tags are not loaded.
# We explicitly configure the reader to load tags, including the
# private ones.
series_reader.LoadPrivateTagsOn()
image3D = series_reader.Execute()
print(image3D.GetMetaDataKeys())
sys.exit( 0 )任何帮助是极大的赞赏！
编辑：看来我还需要在我的阅读器上运行“.MetaDataDictionaryArrayUpdateOn()”模块。但是，如果我尝试这样做，他总是告诉我“ImageSeriesReaderClass”没有这样的方法，即使文档中提到了它。有什么建议么？