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

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

pip install deidcm

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 .

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

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"
)

pip install -e .[quality-tools]

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

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

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

pytest --cov --cov-report=term

Run development server

mkdocs serve

Deploy documentation to GitHub Pages

mkdocs gh-deploy