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. MONAI Label enables application developers to build labeling apps in a serverless way, where custom labeling apps are exposed as a service through the MONAI Label Server.

MONAI Label reduces the time and effort of annotating new datasets and enables the adaptation of AI to the task at hand by continuously learning from user interactions and data.

• MONAI Label allows researchers and developers to make continuous improvements to their apps by allowing them to interact with their apps as the user would.
• End-users (clinicians, technologists, and annotators in general) benefit from AI continuously learning and becoming better at understanding what the end-user is trying to annotate.

MONAI Label aims to fill the gap between developers creating new annotation applications, and the end-users who want to benefit from these innovations.

To start using MONAI Label please visit the Quick Installation page. For detailed information on the project, use cases, annotation paradigms please see below.

• Project overview
• Annotation Paradigms
• API
• Use-cases
• Additional Interaction in Slicer
• FAQ

• Website
• API documentation
• Source code
• Issue tracker
• Wiki