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MONAI Label is the Gym for medical image annotation. It is an Annotation-as-a-Service (AaaS) tool that allows researchers to develop and deploy AI-based annotation apps and make them available for use to clinicians and other researchers alike. MONAI Label application developers build labeling apps in a serverless way, and their 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 at 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 which want to benefit from these innovations.
For a quickstart on MONAI Label please visit the README file. For detailed information on the project, use cases, annotation paradigms please see below.