🔘 Laboratory page: github.com/Project-MONAI
The MONAI framework is the open-source foundation being created by Project MONAI. MONAI is a freely available, community-supported, PyTorch-based framework for deep learning in healthcare imaging. It provides domain-optimized foundational capabilities for developing healthcare imaging training workflows in a native PyTorch paradigm. It 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”. “Provides reproducibility of research experiments for comparisons against state-of-the-art implementations”. “Delivering high-quality software with enterprise-grade development, tutorials for getting started and robust validation & documentation”. (Source: monai.io).
Project MONAI. Is an initiative originally started by NVIDIA & King’s College London to establish an inclusive community of AI researchers for the development and exchange of best practices for AI in healthcare imaging across academia and enterprise researchers. Part of PyTorch Ecosystem. Its ambitions are: developing a community of academic, industrial and clinical researchers collaborating on a common foundation; creating state-of-the-art, end-to-end training workflows for healthcare imaging; providing researchers with the optimized and standardized way to create and evaluate deep learning models.