Kartezio is a modular Cartesian Genetic Programming framework that generates fully transparent and easily interpretable image processing pipelines. This package contains the main scripts used to publish the article.
Link to main Python Package: Kartezio
Link to retated datasets and trained models: Datasets & Trained Models
Link to include the cellpose dataset: Cellpose Dataset
Link to publication: Evolutionary design of explainable algorithms for biomedical image segmentation
Link to official website: kartezio.com
python3 -m pip install virtualenv
python3 -m venv <path/to/venv/venv_name>
source <path/to/venv/venv_name>/bin/activate
pip install --upgrade pip
pip install kartezio==1.0.0a1@article{cortacero2023evolutionary,
title={Evolutionary design of explainable algorithms for biomedical image segmentation},
author={Cortacero, K{\'e}vin and McKenzie, Brienne and M{\"u}ller, Sabina and Khazen, Roxana and Lafouresse, Fanny and Corsaut, Ga{\"e}lle and Van Acker, Nathalie and Frenois, Fran{\c{c}}ois-Xavier and Lamant, Laurence and Meyer, Nicolas and others},
journal={Nature Communications},
volume={14},
number={1},
pages={7112},
year={2023},
publisher={Nature Publishing Group UK London}
}
For any question or suggestion, please don't hesitate to contact us at this e-mail address: kartezio.contact@gmail.com.