Mercurial > hg > orthanc
annotate OrthancServer/Resources/Samples/Python/MicroCTDicomization.py @ 5240:c9e2c6d1cd62
added two Python samples: DicomizeImage.py and MicroCTDicomization.py
author | Sebastien Jodogne <s.jodogne@gmail.com> |
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date | Wed, 05 Apr 2023 17:54:21 +0200 |
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children | 48b8dae6dc77 |
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5240
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1 #!/usr/bin/python3 |
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2 # -*- coding: utf-8 -*- |
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3 |
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4 # Orthanc - A Lightweight, RESTful DICOM Store |
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5 # Copyright (C) 2012-2016 Sebastien Jodogne, Medical Physics |
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6 # Department, University Hospital of Liege, Belgium |
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7 # Copyright (C) 2017-2023 Osimis S.A., Belgium |
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8 # Copyright (C) 2021-2023 Sebastien Jodogne, ICTEAM UCLouvain, Belgium |
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9 # |
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10 # This program is free software: you can redistribute it and/or |
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11 # modify it under the terms of the GNU General Public License as |
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12 # published by the Free Software Foundation, either version 3 of the |
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13 # License, or (at your option) any later version. |
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14 # |
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15 # This program is distributed in the hope that it will be useful, but |
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16 # WITHOUT ANY WARRANTY; without even the implied warranty of |
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17 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU |
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18 # General Public License for more details. |
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19 # |
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20 # You should have received a copy of the GNU General Public License |
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21 # along with this program. If not, see <http://www.gnu.org/licenses/>. |
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22 |
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23 |
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24 # |
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25 # This sample Python script illustrates how to DICOM-ize a micro-CT |
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26 # acquisition, then to upload it to Orthanc. |
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27 # |
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28 # This sample assumes that the slices of the micro-CT are encoded as |
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29 # TIFF files, that are all stored inside the same ZIP archive. Make |
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30 # sure to adapt the parameters of the DICOM-ization below. |
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31 # |
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32 # The following command-line will install the required libraries: |
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33 # |
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34 # $ sudo pip3 install libtiff numpy pydicom requests |
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35 # |
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36 |
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37 import datetime |
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38 import io |
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39 import os |
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40 import tempfile |
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41 import zipfile |
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42 |
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43 import libtiff |
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44 import numpy |
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45 import pydicom |
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46 import pydicom._storage_sopclass_uids |
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47 import pydicom.datadict |
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48 import pydicom.tag |
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49 import requests |
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50 import requests.auth |
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51 |
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52 |
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53 ######################################## |
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54 ## Parameters for the DICOM-ization ## |
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55 ######################################## |
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56 |
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57 ZIP = os.path.join(os.getenv('HOME'), 'Downloads', 'SpyII_mb.zip') |
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58 |
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59 URL = 'http://localhost:8042/' |
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60 USERNAME = 'orthanc' |
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61 PASSWORD = 'orthanc' |
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62 |
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63 VOXEL_WIDTH = 1 |
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64 VOXEL_HEIGHT = 1 |
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65 VOXEL_DEPTH = 1 |
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66 |
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67 TAGS = { |
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68 'PatientID' : 'Test', |
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69 'PatientName' : 'Hello^World', |
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70 'StudyDate' : datetime.datetime.now().strftime('%Y%m%d'), |
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71 'StudyTime' : datetime.datetime.now().strftime('%H%M%S'), |
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72 |
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73 'AccessionNumber' : None, |
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74 'AcquisitionNumber' : None, |
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75 'KVP' : None, |
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76 'Laterality' : None, |
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77 'Manufacturer' : None, |
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78 'PatientBirthDate' : '', |
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79 'PatientPosition' : None, |
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80 'PatientSex' : 'O', |
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81 'PositionReferenceIndicator' : None, |
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82 'ReferringPhysicianName' : None, |
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83 'SeriesNumber' : 1, |
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84 'StudyID' : 'Test', |
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85 } |
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86 |
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87 |
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88 |
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89 ######################################## |
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90 ## Application of the DICOM-ization ## |
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91 ######################################## |
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92 |
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93 # Add the DICOM unique identifiers |
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94 for tag in [ 'StudyInstanceUID', |
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95 'SeriesInstanceUID', |
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96 'FrameOfReferenceUID' ]: |
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97 if not tag in TAGS: |
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98 TAGS[tag] = pydicom.uid.generate_uid() |
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99 |
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100 |
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101 def CreateDicomDataset(tif, sliceIndex): |
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102 image = tif.read_image().astype(numpy.uint16) |
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103 |
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104 meta = pydicom.Dataset() |
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105 meta.MediaStorageSOPClassUID = pydicom._storage_sopclass_uids.CTImageStorage |
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106 meta.MediaStorageSOPInstanceUID = pydicom.uid.generate_uid() |
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107 meta.TransferSyntaxUID = pydicom.uid.ImplicitVRLittleEndian |
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108 |
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109 dataset = pydicom.Dataset() |
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110 dataset.file_meta = meta |
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111 |
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112 dataset.is_little_endian = True |
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113 dataset.is_implicit_VR = True |
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114 dataset.SOPClassUID = meta.MediaStorageSOPClassUID |
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115 dataset.SOPInstanceUID = meta.MediaStorageSOPInstanceUID |
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116 dataset.Modality = 'CT' |
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117 |
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118 for (key, value) in TAGS.items(): |
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119 tag = pydicom.tag.Tag(key) |
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120 vr = pydicom.datadict.dictionary_VR(tag) |
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121 dataset.add_new(tag, vr, value) |
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122 |
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123 assert(image.dtype == numpy.uint16) |
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124 dataset.BitsStored = 16 |
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125 dataset.BitsAllocated = 16 |
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126 dataset.SamplesPerPixel = 1 |
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127 dataset.HighBit = 15 |
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128 |
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129 dataset.Rows = image.shape[0] |
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130 dataset.Columns = image.shape[1] |
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131 dataset.InstanceNumber = (sliceIndex + 1) |
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132 dataset.ImagePositionPatient = r'0\0\%f' % (-float(sliceIndex) * VOXEL_DEPTH) |
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133 dataset.ImageOrientationPatient = r'1\0\0\0\-1\0' |
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134 dataset.SliceThickness = VOXEL_DEPTH |
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135 dataset.ImageType = r'ORIGINAL\PRIMARY\AXIAL' |
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136 dataset.RescaleIntercept = '0' |
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137 dataset.RescaleSlope = '1' |
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138 dataset.PixelSpacing = r'%f\%f' % (VOXEL_HEIGHT, VOXEL_WIDTH) |
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139 dataset.PhotometricInterpretation = 'MONOCHROME2' |
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140 dataset.PixelRepresentation = 1 |
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141 |
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142 minValue = numpy.min(image) |
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143 maxValue = numpy.max(image) |
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144 dataset.WindowWidth = maxValue - minValue |
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145 dataset.WindowCenter = (minValue + maxValue) / 2.0 |
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146 |
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147 pydicom.dataset.validate_file_meta(dataset.file_meta, enforce_standard=True) |
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148 dataset.PixelData = image.tobytes() |
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149 |
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150 return dataset |
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151 |
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152 |
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153 # Create a temporary file, as libtiff is not able to read from BytesIO() |
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154 with tempfile.NamedTemporaryFile() as tmp: |
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155 sliceIndex = 0 |
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156 |
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157 # Loop over the files in the ZIP archive, after having sorted them |
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158 with zipfile.ZipFile(ZIP, 'r') as z: |
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159 for path in sorted(z.namelist()): |
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160 |
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161 # Ignore folders in the ZIP archive |
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162 info = z.getinfo(path) |
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163 if info.is_dir(): |
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164 continue |
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165 |
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166 # Extract the current file from the ZIP archive, into the temporary file |
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167 print('DICOM-izing: %s' % path) |
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168 data = z.read(path) |
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169 |
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170 with open(tmp.name, 'wb') as f: |
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171 f.write(data) |
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172 |
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173 # Try and decode the TIFF file |
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174 try: |
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175 tif = libtiff.TIFF.open(tmp.name) |
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176 except: |
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177 # Not a TIFF file, ignore |
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178 continue |
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179 |
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180 # Create a DICOM dataset from the TIFF |
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181 dataset = CreateDicomDataset(tif, sliceIndex) |
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182 b = io.BytesIO() |
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183 dataset.save_as(b, False) |
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184 |
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185 # Upload the DICOM dataset to Orthanc |
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186 r = requests.post('%s/instances' % URL, b.getvalue(), |
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187 auth = requests.auth.HTTPBasicAuth(USERNAME, PASSWORD)) |
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188 r.raise_for_status() |
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189 |
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190 sliceIndex += 1 |