monai.io
An open-source framework designed to accelerate healthcare imaging AI development and deployment.
About monai.io
MONAI (Medical Open Network for AI) is an open-source platform dedicated to advancing healthcare imaging AI. It offers robust tools for developing, training, and deploying medical AI applications. MONAI bridges research innovation with clinical practice, providing scalable solutions for healthcare technology advancement.
How to Use
Utilize MONAI’s core frameworks—Core for training models, Label for image annotation, and Deploy for clinical deployment. Access the extensive model zoo and join the community for support, collaboration, and contributions to healthcare AI projects.
Features
Specialized transforms for medical imaging
AI-powered image annotation tools
Seamless integration into clinical workflows
Access to pre-trained models via model zoo
Supports DICOM and FHIR standards
Use Cases
Integrating AI into Siemens Healthineers digital marketplace
Rapid deployment of medical imaging solutions with Mercure DICOM
Implementing AI-driven diagnostics at Mayo Clinic Florida
Best For
Medical imaging specialistsData scientistsAI research professionalsHealthcare providersSoftware developers in healthcare
Pros
Supports the full lifecycle of medical AI development
Integrates smoothly with PyTorch for model training
Offers a comprehensive suite of medical imaging AI tools
Supported by a global community of AI experts
Open-source license (Apache 2.0) for flexible use
Cons
Clinical deployment requires validation and regulatory approval
Demands familiarity with medical imaging and AI concepts
Training models may need substantial computational resources
Frequently Asked Questions
Find answers to common questions about monai.io
What is MONAI?
MONAI is an open-source framework that accelerates the development, training, and deployment of AI solutions for healthcare imaging.
What are the core components of MONAI?
The main components include MONAI Core for training, MONAI Label for image annotation, and MONAI Deploy for clinical model deployment.
How can I contribute to MONAI?
Contribute by joining the community, participating in discussions, reporting issues, suggesting features, and submitting code contributions.
Is MONAI suitable for clinical use?
Yes, but deploying in clinical settings requires validation, regulatory compliance, and thorough testing.
What standards does MONAI support?
MONAI supports DICOM for medical images and FHIR for healthcare data interoperability.