Split documentation in several files

Also add financing and state of library in README

Author: pchoisel

README.md

@@ -25,313 +25,17 @@ Dicom fields are separated into different groups. Each groups will be anonymized
 
 `dicom-anonymizer` is designed to retain date information within DICOM files, and will anonymize them rather than removing them entirely. This approach is taken to prevent potential crashes in certain applications that rely on these dates to work. This behavior complies with the DICOM standard, as mentioned in section [E.3.6](https://dicom.nema.org/medical/dicom/current/output/html/part15.html#sect_E.3.6).
 
-# How to install it?
+## Documentation
 
-Installation can be done via pip `pip install dicom-anonymizer` or conda `conda install -c conda-forge dicom-anonymizer`.
+ - [Installation](./doc/Setup_build_test.md)
+ - [Usage](./doc/Usage)
 
+## State of the library
 
-# Local Development Setup
+At this present time, Kitware has no plan to implement new features in dicom-anonymizer.  
+If you have funding to further develop this tool, feel free to reach out to Kitware.  
+Whenever possible, Kitware will try to fix bugs that affect the use of the project and merge requests from the community will be considered, feel free to [open an issue](https://github.com/KitwareMedical/dicom-anonymizer/issues?q=is%3Aissue%20state%3Aopen%20label%3Aenhancement) to suggest new features.
 
-To get started with local development, follow these steps:
+## Financing
 
-1. Create a Virtual Environment:
-   - On Windows:
-     ```sh
-     virtualenv env
-     .\env\Scripts\activate.bat
-     ```
-   - On MacOS/Linux:
-     ```sh
-     python -m venv env
-     source env/bin/activate
-     ```
-
-2. Install Dependencies:
-   - Install an editable version of the package and the development requirements:
-     ```sh
-     pip install -e .[dev]
-     ```
-
-3. Set Up Pre-Commit Hooks:
-   - Install the pre-commit hooks to ensure code quality:
-     ```sh
-     pre-commit install
-     ```
-
-
-## How to test it?
-
-To run the unit tests, use the following command:
-
-```sh
-pytest
-```
-
-
-# How to build it?
-These instructions rely on wheel build-package format. Install it if you have not done it already using:
-`pip install wheel`
-
-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-1.0.13-1-py2.py3-none-any.whl`
-
-On Windows, if you see a warning message
-`'./dist/dicom_anonymizer-1.0.13-1-py2.py3-none-any.whl' looks like a filename, but the file does not exist`,
-this could be due to pip not being able to handle relative path (See issue https://github.com/pypa/pip/issues/10808). As a work-around, change directory to `dist` and then install it using
-`pip install dicom_anonymizer-1.0.13-1-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 overridden).
-The way on how the DICOM fields are anonymized can also be overridden.
-
-- **[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$' '0000'
-```
-
-Example 3: Change the tag value with an arbitrary value
-```python
-python anonymizer.py InputFilePath OutputFilePath -t '(0x0010, 0x0010)' 'replace_with_value' 'new_value'
-```
-
-### DICOMDIR
-
-> DICOMDIR anonymization is not specified. It is therefore discouraged and it is recommended to regenerate new DICOMDIR files after anonymizing the original DICOM files.
-
-DICOMDIR files can have a `(0x0004, 0x1220)  Directory Record Sequence` tag that can contain patient information.  
-However, this tag is not part of the standard tag to anonymize set. If you still want dicom-anonymizer to anonymize it, you have to instruct it explicitly:
-
-```python
-python anonymizer.py InputFilePath OutputFilePath -t '(0x0004, 0x1220)' replace
-```
-
-## Custom rules with dictionary file
-
-Instead of having a big command line with several new actions, you can create your own dictionary by creating a json file `dictionary.json` :
-```json
-{
-    "(0x0002, 0x0002)": "ActionName",
-    "(0x0003, 0x0003)": "ActionName",
-    "(0x0004, 0x0004)": "ActionName",
-    "(0x0005, 0x0005)": "ActionName"
-}
-```
-Same as before, the `ActionName` has to be defined in the [actions list](#actions-list).
-
-```python
-dicom-anonymizer InputFilePath OutputFilePath --dictionary dictionary.json
-```
-
-If you want to use the **regexp** action in a dictionary:
-```json
-{
-    "(0x0002, 0x0002)": "ActionName",
-    "(0x0008, 0x0020)": {
-        "action": "regexp",
-        "find": "0701$",
-        "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 ALL_TAGS, anonymize, keep
-
-
-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",
-    )
-    args = parser.parse_args()
-
-    deletePrivateTags = False
-
-    input_dicom_path = args.input
-    output_dicom_path = args.output
-
-    extra_anonymization_rules = {}
-
-    # Per https://www.hhs.gov/hipaa/for-professionals/privacy/special-topics/de-identification/index.html
-    # it is all right to retain only the year part of the birth date for
-    # de-identification purposes.
-    def set_date_to_year(dataset, tag):
-        element = dataset.get(tag)
-        if element is not None:
-            element.value = f"{element.value[:4]}0101" # YYYYMMDD format
-
-    # 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 ALL_TAGS:
-        extra_anonymization_rules[i] = keep
-
-    extra_anonymization_rules[(0x0010, 0x0030)] = set_date_to_year # Patient's Birth Date
-
-    # Launch the anonymization
-    anonymize(
-        input_dicom_path,
-        output_dicom_path,
-        extra_anonymization_rules,
-        delete_private_tags=False,
-    )
-
-
-if __name__ == "__main__":
-    main()
-```
-
-See the full application in the `examples` folder.
-
-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 for a dataset
-
-You can also anonymize dicom fields in-place for pydicom's DataSet using `anonymize_dataset`. See this example:
-```python
-import pydicom
-
-from dicomanonymizer import anonymize_dataset
-
-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()
-```
-
-See the full application in the `examples` folder.
-
-For more information about the pydicom's Dataset, please refer [here](https://pydicom.github.io/pydicom/stable/reference/generated/pydicom.dataset.Dataset.html).
-
-You can also add `extra_anonymization_rules` as above:
-```python
-    anonymize_dataset(data_ds, extra_anonymization_rules, delete_private_tags=True)
-```
-
-# 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 |
-| 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** |
-| deleteOrEmptyOrReplace | 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| Find a value in the tag using a regexp and replace it with an arbitrary value. See the examples in this file to learn how to use.|
-|replace_with_value| Replace the tag value with an arbitrary value. See the examples in this file to learn how to use.
-
-
-** VR: Value Representation
-
-Work originally done by Edern Haumont
-
-# Change the DICOM anonymization standard
-
-You can customize the DICOM standard that will be used to anonymize the dataset by giving an argument `base_rules_gen` to the function `anonymize_dicom_file` or `anonymize_dataset`.  
-The value should be a function returning a dict of anonymization rules. Use the function `initialize_actions` to create such dict from a anonymization database from the folder `dicomanonymizer/dicom_anonymization_databases`.
-
-Example:
-```python
-from dicomanonymizer.simpledicomanonymizer import anonymize_dataset, initialize_actions
-
-anonymize_dataset(
-    dataset, base_rules_gen=lambda: initialize_actions("dicomfields_2024b")
-)
-```
+If you want a new feature in dicom-anonymizer or help manipulating DICOM files, feel free to reach out to us at contact@kitware.fr.

doc/Setup_build_test.md

@@ -0,0 +1,63 @@
+# Installation
+
+### Binary installation
+
+Installation can be done via pip `pip install dicom-anonymizer` or conda `conda install -c conda-forge dicom-anonymizer`.
+
+
+### Local Development Setup
+
+To get started with local development, follow these steps:
+
+1. Create a Virtual Environment:
+   - On Windows:
+     ```sh
+     virtualenv env
+     .\env\Scripts\activate.bat
+     ```
+   - On MacOS/Linux:
+     ```sh
+     python -m venv env
+     source env/bin/activate
+     ```
+
+2. Install Dependencies:
+   - Install an editable version of the package and the development requirements:
+     ```sh
+     pip install -e .[dev]
+     ```
+
+3. Set Up Pre-Commit Hooks:
+   - Install the pre-commit hooks to ensure code quality:
+     ```sh
+     pre-commit install
+     ```
+
+
+## Testing
+
+To run the unit tests, use the following command:
+
+```sh
+pytest
+```
+
+
+## Building
+
+These instructions rely on wheel build-package format. Install it if you have not done it already using:
+`pip install wheel`
+
+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-1.0.13-1-py2.py3-none-any.whl`
+
+On Windows, if you see a warning message
+`'./dist/dicom_anonymizer-1.0.13-1-py2.py3-none-any.whl' looks like a filename, but the file does not exist`,
+this could be due to pip not being able to handle relative path (See issue https://github.com/pypa/pip/issues/10808). As a work-around, change directory to `dist` and then install it using
+`pip install dicom_anonymizer-1.0.13-1-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.