projectmonai/monai repository overview

Medical Open Network for AI

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

• developing a community of academic, industrial and clinical researchers collaborating on a common foundation;
• creating state-of-the-art, end-to-end training workflows for healthcare imaging;
• providing researchers with the optimized and standardized way to create and evaluate deep learning models.

⁠Features

• flexible pre-processing for multi-dimensional medical imaging data;
• compositional & portable APIs for ease of integration in existing workflows;
• domain-specific implementations for networks, losses, evaluation metrics and more;
• customizable design for varying user expertise;
• multi-GPU multi-node data parallelism support.

⁠Installation

To install the current release⁠, you can simply run:

pip install monai

Please refer to the installation guide⁠ for other installation options.

⁠Getting Started

MedNIST demo⁠ and MONAI for PyTorch Users⁠ are available on Colab.

Examples and notebook tutorials are located at Project-MONAI/tutorials⁠.

Technical documentation is available at docs.monai.io⁠.

⁠Citation

If you have used MONAI in your research, please cite us! The citation can be exported from: https://arxiv.org/abs/2211.02701⁠.

⁠Model Zoo

The MONAI Model Zoo⁠ is a place for researchers and data scientists to share the latest and great models from the community. Utilizing the MONAI Bundle format⁠ makes it easy to get started⁠ building workflows with MONAI.

⁠Contributing

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

⁠Community

Join the conversation on Twitter @ProjectMONAI⁠ or join our Slack channel⁠.

Ask and answer questions over on MONAI's GitHub Discussions tab⁠.

⁠Links

• Website: https://monai.io/⁠
• API documentation (milestone): https://docs.monai.io/⁠
• API documentation (latest dev): https://docs.monai.io/en/latest/⁠
• Code: https://github.com/Project-MONAI/MONAI⁠
• Project tracker: https://github.com/Project-MONAI/MONAI/projects⁠
• Issue tracker: https://github.com/Project-MONAI/MONAI/issues⁠
• Wiki: https://github.com/Project-MONAI/MONAI/wiki⁠
• Test status: https://github.com/Project-MONAI/MONAI/actions⁠
• PyPI package: https://pypi.org/project/monai/⁠
• conda-forge: https://anaconda.org/conda-forge/monai⁠
• Weekly previews: https://pypi.org/project/monai-weekly/⁠
• Docker Hub: https://hub.docker.com/r/projectmonai/monai⁠