Medical Open Network for AI

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.

Open Source

MONAI is an open-source project. It is built on top of PyTorch and is released under the Apache 2.0 license.

Standardized

Aiming to capture best practices of AI development for healthcare researchers, with an immediate focus on medical imaging.

User Friendly

Providing user-comprehensible error messages and easy to program API interfaces.

Reproducible

Provides reproducibility of research experiments for comparisons against state-of-the-art implementations.

Easy Integration

Designed to be compatible with existing efforts and ease of 3rd party integration for various components.

High Quality

Delivering high-quality software with enterprise-grade development, tutorials for getting started and robust validation & documentation.

Getting Started

Workflows

Training and evaluation - classification
Brain MRI classification examples

Training and evaluation - segmentation
Volumetric image segmentation examples

Training and evaluation - MONAI workflows
Image segmentation examples with engine and event-handlers

Learn more

View a list of all
MONAI tutorials and examples

New Features in v0.2.0

Customizable

Customizable and Composable Image Transforms with Third-party Integration Support.

Ready-to-use

Ready-to-use Dataset and Loader APIs for the Standard Public Datasets.

Optimized

Various Domain-optimized Implementations for Network, Losses, Validation Metrics.

Modules

MONAI Research modules.

New Examples

Various New Tutorials and Examples.

New Workflow APIs

Various Deep Learning Workflow APIs.

User Value Proposition

Entry Level Researcher

Provides ready-to-use deep learning models, walk-through tutorials and examples to get kick-started for AI development on a common foundation.

Advanced Researcher

For advanced academic and translational researchers, MONAI provides modular domain optimized components that can be easily integrated into existing workflows and enables reproducibility of research experiments for comparison.

Repository and Roadmap

Project MONAI

GitHub Repository
Go to repository

Contributing Guidelines
Go to guide

Licensing Guide
Go to Apache 2.0 license

Bug reports and feature requests
Go to issues

Initial Roadmap Schedule

Release Roadmap APR 2020 JUL 2020 OCT 2020 0.1.0 0.2.0 0.3.0

Contributors

Project MONAI is an initiative originally started by NVIDIA & King’s College London to establish an inclusive community of AI researchers for the development and exchange of best practices for AI in healthcare imaging across academia and enterprise researchers.

Join Project MONAI