github_url:	https://github.com/Project-MONAI/MONAI

Project MONAI

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.

The codebase is currently under active development

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 data parallelism support.

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

Technical documentation is available at docs.monai.io.

.. toctree::
   :maxdepth: 1
   :caption: Feature highlights

   whatsnew
   highlights.md

.. toctree::
   :maxdepth: 1
   :caption: API Reference

   api

.. toctree::
  :maxdepth: 1
  :caption: Installation

  installation

.. toctree::
  :maxdepth: 1
  :caption: Contributing

  contrib

Website: https://monai.io/
API documentation: https://docs.monai.io
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
Changelog: https://github.com/Project-MONAI/MONAI/blob/dev/CHANGELOG.md
Wiki: https://github.com/Project-MONAI/MONAI/wiki
FAQ: https://github.com/Project-MONAI/MONAI/wiki/Frequently-asked-questions-and-answers
Test status: https://github.com/Project-MONAI/MONAI/actions
PyPI package: https://pypi.org/project/monai/
Weekly previews: https://pypi.org/project/monai-weekly/
Docker Hub: https://hub.docker.com/r/projectmonai/monai

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