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. Project MONAI also includes MONAI Label, an intelligent open source image labeling and learning tool that helps researchers and clinicians collaborate, create annotated datasets, and build AI models in a standardized MONAI paradigm. 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.
Features
- MONAI Core is a PyTorch-based, open-source framework for deep learning in healthcare imaging, part of PyTorch Ecosystem
- Released under the Apache 2.0 license
- Provides reproducibility of research experiments
- Designed to be compatible with existing efforts and ease of 3rd party integration
- Delivering high-quality software with enterprise-grade development
- MONAI Label is an intelligent open source image labeling and learning tool that enables users to create annotated datasets and build AI annotation models for clinical evaluation