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
- Download source code
git clone https://github.com/Epiconcept-Paris/deidcm.git
cd deidcm
- Create and activate a virtual environment
python3 -m venv env
. env/bin/activate
- 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