MONAI is a set of open-source, freely available collaborative frameworks built for accelerating research and clinical collaboration in Medical Imaging. The goal is to accelerate the pace of innovation and clinical translation by building a robust software framework that benefits nearly every level of medical imaging, deep learning research, and deployment.
Open Source Design
MONAI is an open-source project. It is built on top of PyTorch and is released under the Apache 2.0 license.
Aiming to capture best practices of AI development for healthcare researchers, with an immediate focus on medical imaging.
Providing user-comprehensible error messages and easy to program API interfaces.
Provides reproducibility of research experiments for comparisons against state-of-the-art implementations.
Designed to be compatible with existing efforts and ease of 3rd party integration for various components.
Delivering high-quality software with enterprise-grade development, tutorials for getting started and robust validation & documentation.
Goal for this Hackweek
The goal is to learn MONAI and understand the different deploy alternatives.
Anyone with interest on Medical applications based on Artificial Intelligence and MLOps in general is welcome to join. No previous knowledge is required.
This project is part of:
Hack Week 22