Medical Open Network
for Artificial Intelligence

New Releases:

MONAI is

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.

Project MONAI also includes MONAI Label, an intelligent open source image labeling and learning tool that helps researchers and clinicians collaborate, create annotated datasets, and build AI models in a standardized MONAI paradigm.

Open Source Design

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.

Medical AI Workflow

When dealing with Medical AI, it's important to have tools that cover the end-to-end workflow. MONAI provides those tools for the entire Medical AI Model development workflow, from Research to Clinical Production.

MONAI Label

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 Core

MONAI Core is a PyTorch-based, open-source framework for deep learning in healthcare imaging, part of PyTorch Ecosystem.

MONAI Deploy

MONAI Deploy aims to become the de-facto standard for developing, packaging, testing, deploying and running medical AI applications in clinical production.

Roadmap

April 2021

  • MONAI Core v0.5.0

July 2021

  • MONAI Core v0.6.0
  • MONAI Label v0.1.0

September 2021

  • MONAI Core v0.7.0
  • MONAI Label v0.2.0
  • MONAI Deploy App SDK v0.1.0

November 2021

  • MONAI Core v0.8.0
  • MONAI Label v0.3.0
  • MONAI Deploy App SDK v0.2.0
  • MONAI Deploy MIS v0.1.0

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.

News

  • MONAI Bootcamp 2021

    MONAI hosted a Bootcamp from September 22nd - September 24th, 2021. Find all of the material from the day and links to recordings for the first two days of the event.

  • Image Registration now in MONAI

    MONAI has been working closely with DeepReg on learning-based medical image registration using PyTorch. We are delighted to provide a set of essential tools for developing registration pipelines.

  • MONAI Label v0.1

    MONAI Label is an intelligent image labeling and learning tool that enables users to create annotated datasets and build AI annotation models quickly.