medcog-dicom-anonymizer 1.0.8
Program to anonymize dicom files with default and custom rules.
License: MIT
Requires Python: >=3.10

# DicomAnonymizer

Python package to anonymize DICOM files.
The anonymization answer to the standard . More information about dicom fields for anonymization can be found [here](http://dicom.nema.org/dicom/2013/output/chtml/part15/chapter_E.html#table_E.1-1).

The default behaviour of this package is to anonymize DICOM fields referenced in [dicomfields](dicomanonymizer/dicomfields.py).

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

| Group | Action | Action definition |
| --- | --- | --- |
| D_TAGS | replace | Replace with a non-zero length value that may be a dummy value and consistent with the VR** |
| Z_TAGS | empty | Replace with a zero length value, or a non-zero length value that may be a dummy value and consistent with the VR** |
| X_TAGS | delete | Completely remove the tag |
| U_TAGS | replace_UID | Replace all UID's number with a random one in order to keep consistent. Same UID will have the same replaced value |
| Z_D_TAGS | empty_or_replace | Replace with a non-zero length value that may be a dummy value and consistent with the VR** |
| X_Z_TAGS | delete_or_empty | Replace with a zero length value, or a non-zero length value that may be a dummy value and consistent with the VR** |
| X_D_TAGS | delete_or_replace | Replace with a non-zero length value that may be a dummy value and consistent with the VR** |
| X_Z_D_TAGS | delete_or_empty_or_replace | Replace with a non-zero length value that may be a dummy value and consistent with the VR** |
| X_Z_U_STAR_TAGS | delete_or_empty_or_replace_UID | If it's a UID, then all numbers are randomly replaced. Else, replace with a zero length value, or a non-zero length value that may be a dummy value and consistent with the VR**|
| ALL_TAGS | | Contains all previous defined tags


# 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.

```python
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](#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**:
```python
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](#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
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
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` :
```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](#actions-list).

```python
dicom-anonymizer InputFilePath OutputFilePath --dictionary dictionary.json
```

If you want to use the **regexp** action in a dictionary:
```json
{
    "(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.
```python
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:
```python
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](https://github.com/pydicom/pydicom/blob/995ac6493188313f6a2e6355477baba9f543447b/pydicom/dataset.py).
You can also add a dictionnary as previously :
```python
    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

| Action | Action definition |
| --- | --- |
| empty | Replace with a zero length value, or a non-zero length value that may be a dummy value and consistent with the VR** |
| delete | Completely remove the tag |
| keep | Do nothing on the tag |
| clean | Don't use it for now. This is not implemented |
| replace_UID | Replace all UID's number with a random one in order to keep consistent. Same UID will have the same replaced value |
| empty_or_replace | Replace with a non-zero length value that may be a dummy value and consistent with the VR** |
| delete_or_empty | Replace with a zero length value, or a non-zero length value that may be a dummy value and consistent with the VR** |
| delete_or_replace | Replace with a non-zero length value that may be a dummy value and consistent with the VR** |
| deleteOrEmplyOrReplace | Replace with a non-zero length value that may be a dummy value and consistent with the VR** |
| delete_or_empty_or_replace_UID | If it's a UID, then all numbers are randomly replaced. Else, replace with a zero length value, or a non-zero length value that may be a dummy value and consistent with the VR** |
|regexp| These action is not a common action. It allows to use regexp to modify values|


** VR: Value Representation

Work originally done by Edern Haumont