Medical image analysis using deep learning frameworks has advanced healthcare by automating complex tasks, but many existing frameworks lack flexibility, modularity, and user-friendliness. To address these challenges, we introduce Yucca, an open-source AI framework available at https://github.com/Sllambias/yucca, designed specifically for medical imaging applications and built on PyTorch and PyTorch Lightning. Yucca features a three-tiered architecture: Functional, Modules, and Pipeline, providing a comprehensive and customizable solution. Evaluated across diverse tasks such as cerebral microbleeds detection, white matter hyperintensity segmentation, and hippocampus segmentation, Yucca achieves state-of-the-art results, demonstrating its robustness and versatility. Yucca offers a powerful, flexible, and user-friendly platform for medical image analysis, inviting community contributions to advance its capabilities and impact.
@article{arxiv.2407.19888,
title = {Yucca: A Deep Learning Framework For Medical Image Analysis},
author = {Sebastian Nørgaard Llambias and Julia Machnio and Asbjørn Munk and Jakob Ambsdorf and Mads Nielsen and Mostafa Mehdipour Ghazi},
journal= {arXiv preprint arXiv:2407.19888},
year = {2024}
}