DicomAnonymizer

Python package to anonymize DICOM files. The anonymization answer to the standard . More information about dicom fields for anonymization can be found here.

The default behaviour of this package is to anonymize DICOM fields referenced in dicomfields.

Dicom fields are separated into different groups. Each groups will be anonymized in a different way.

How to build it ?

The sources files can be packaged by using: python ./setup.py bdist_wheel

This command will generate a wheel package in dist folder which can be then installed as a python package using pip install ./dist/dicom_anonymizer-1.0.7-py2.py3-none-any.whl

Installing this package will also install an executable named dicom-anonymizer. In order to use it, please refer to the next section.

How to use it ?

This package allows to anonymize a selection of DICOM field (defined or overrided). The way on how the DICOM fields are anonymized can also be overrided.

• [required] InputPath = Full path to a single DICOM image or to a folder which contains dicom files
• [required] OutputPath = Full path to the anonymized DICOM image or to a folder. This folder has to exist.
• [optional] ActionName = Defined an action name that will be applied to the DICOM tag.
• [optional] Dictionary = Path to a JSON file which defines actions that will be applied on specific dicom tags (see below)

Default behaviour

You can use the default anonymization behaviour describe above.

dicom-anonymizer Input Output

Private tags

Default behavior of the dicom anonymizer is to delete private tags. But you can bypass it:

• Solution 1: Use regexp to define which private tag you want to keep/update (cf custom rules)
• Solution 2: Use dicom-anonymizer.exe option to keep all private tags : --keepPrivateTags

Custom rules

You can manually add new rules in order to have different behaviors with certain tags. This will allow you to override default rules:

Executable:

dicom-anonymizer InputFilePath OutputFilePath -t '(0x0001, 0x0001)' ActionName -t '(0x0001, 0x0005)' ActionName2

This will apply the ActionName to the tag '(0x0001, 0x0001)' and ActionName2 to '(0x0001, 0x0005)'

Note: ActionName has to be defined in actions list

Example 1: The default behavior of the patient's ID is to be replaced by an empty or null value. If you want to keep this value, then you'll have to run :

python anonymizer.py InputFilePath OutputFilePath -t '(0x0010, 0x0020)' keep

This command will override the default behavior executed on this tag and the patient's ID will be kept.

Example 2: We just want to change the study date from 20080701 to 20080000, then we'll use the regexp

python anonymizer.py InputFilePath OutputFilePath -t '(0x0008, 0x0020)' 'regexp' '0701$' '0000'

Custom rules with dictionary file

Instead of having a big command line with several new actions, you can create your own dictionary by creating a json file dictionary.json :

{
    "(0x0002, 0x0002)": "ActionName",
    "(0x0003, 0x0003)": "ActionName",
    "(0x0004, 0x0004)": "ActionName",
    "(0x0005, 0x0005)": "ActionName"
}

Same as before, the ActionName has to be defined in the actions list.

dicom-anonymizer InputFilePath OutputFilePath --dictionary dictionary.json

If you want to use the regexp action in a dictionary:

{
    "(0x0002, 0x0002)": "ActionName",
    "(0x0008, 0x0020)": {
        "action": "regexp",
        "find": "0701$",
        "replace": "0000"
    }
}

Custom/overrides actions

Here is a small example which keeps all metadata but updates the series description by adding a suffix passed as a parameter.

import argparse
from dicomanonymizer import *

def main():
    parser = argparse.ArgumentParser(add_help=True)
    parser.add_argument('input', help='Path to the input dicom file or input directory which contains dicom files')
    parser.add_argument('output', help='Path to the output dicom file or output directory which will contains dicom files')
    parser.add_argument('--suffix', action='store', help='Suffix that will be added at the end of series description')
    args = parser.parse_args()

    input_dicom_path = args.input
    output_dicom_path = args.output

    extraAnonymizationRules = {}

    def setupSeriesDescription(dataset, tag):
        element = dataset.get(tag)
        if element is not None:
            element.value = element.value + '-' + args.suffix

    # ALL_TAGS variable is defined on file dicomfields.py
    # the 'keep' method is already defined into the dicom-anonymizer
    # It will overrides the default behaviour
    for i in allTags:
        extraAnonymizationRules[i] = keep

    if args.suffix:
        extraAnonymizationRules[(0x0008, 0x103E)] = setupSeriesDescription

    # Launch the anonymization
    anonymize(input_dicom_path, output_dicom_path, extraAnonymizationRules)

if __name__ == "__main__":
    main()

In your own file, you'll have to define:

• Your custom functions. Be careful, your functions always have in inputs a dataset and a tag
• A dictionary which map your functions to a tag

Anonymize dicom tags without dicom file

If for some reason, you need to anonymize dicom fields without initial dicom file (extracted from a database for example). Here is how you can do it:

from dicomanonymizer import *

def main():

  # Create a list of tags object that should contains id, type and value
  fields = [
    { # Replaced by Anonymized
      'id': (0x0040, 0xA123),
      'type': 'LO',
      'value': 'Annie de la Fontaine',
    },
    { # Replaced with empty value
      'id': (0x0008, 0x0050),
      'type': 'TM',
      'value': 'bar',
    },
    { # Deleted
      'id': (0x0018, 0x4000),
      'type': 'VR',
      'value': 'foo',
    }
  ]

  # Create a readable dataset for pydicom
  data = pydicom.Dataset()

  # Add each field into the dataset
  for field in fields:
    data.add_new(field['id'], field['type'], field['value'])

  anonymize_dataset(data)

if __name__ == "__main__":
    main()

For more information about the pydicom's Dataset, please refer here. You can also add a dictionnary as previously :

    dictionary = {}

    def newMethod(dataset, tag):
        element = dataset.get(tag)
        if element is not None:
            element.value = element.value + '- generated with new method'

    dictionary[(0x0008, 0x103E)] = newMethod
    anonymize_dataset(data, dictionary)

Actions list

** VR: Value Representation

Work originally done by Edern Haumont