deidcm 0.0.3

Reusable toolset for deidentifiying images and metadata contained inside DICOM files

deidcm module

Functionality for cancer screening data pipeline including DICOM image importing and processing.

Initially conceived for french breast cancer screening program during the execution of deep.piste study

Documentation

deidcm documentation can be found at: https://epiconcept-paris.github.io/deidcm/

Installation

pip install deidcm

Installation for contributors

1. Download source code

git clone https://github.com/Epiconcept-Paris/deidcm.git
cd deidcm

2. Create and activate a virtual environment

python3 -m venv env
. env/bin/activate

3. Install deidcm

pip install -e .

How to contribute

Please send a PR for small bugs/improvements. For bigger ones, open an issue first.

Checking installation

Open a python interpreter and try to deidentify a dicom file:

from deidcm_deid.dicom.deid_mammogram import deidentify_image_png

deidentify_image_png(
    "/path/to/mammogram.dcm",
    "/path/to/processed/output-folder",
    "output-filename"
)

Tools for developers

Installation

pip install -e .[quality-tools]

Usage

Format your files with python3 -m autopep8 --in-place file/to/format

Lint your files with python3 -m pylint file/to/lint

Run Tests

Run all tests

pytest

Run a specific test file

pytest test/test_df2dicom.py

Run all except OCR tests

pytest --ignore=test/test_ocr_deidentification.py --ignore=test/test_df2dicom

Show full error message

pytest test/test_df2dicom.py --showlocals

Calculate Tests Coverage

pytest --cov --cov-report=term

Documentation

Run development server

mkdocs serve

Deploy documentation to GitHub Pages

mkdocs gh-deploy