MONAI Label

Medical Open Network for AI

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 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.

Table of Contents

• What’s New
• Installation
• Quickstart
• Modules Overview
• Application Deployment
• API Reference

Contributing

For guidance on making a contribution to MONAI, see the contributing guidelines.

Links

• Website: https://monai.io/

• API documentation: https://docs.monai.io/projects/label

• Code: https://github.com/Project-MONAI/MONAILabel

• Project tracker: https://github.com/Project-MONAI/MONAILabel/projects

• Issue tracker: https://github.com/Project-MONAI/MONAILabel/issues

• Changelog: https://github.com/Project-MONAI/MONAILabel/blob/master/CHANGELOG.md

• Wiki: https://github.com/Project-MONAI/MONAILabel/wiki

• Test status: https://github.com/Project-MONAI/MONAILabel/actions

• PyPI package: https://pypi.org/project/monailabel/

• Weekly previews: https://pypi.org/project/monailabel-weekly/

Indices and tables

• Index

• Module Index

• Search Page

What’s New