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

.. MONAI documentation main file, created by
   sphinx-quickstart on Wed Feb  5 09:40:29 2020.
   You can adapt this file completely to your liking, but it should at least
   contain the root `toctree` directive.

Project MONAI
=============


*Medical Open Network for AI*

MONAI is a `PyTorch <https://pytorch.org/>`_-based, `open-source <https://github.com/Project-MONAI/MONAI/blob/dev/LICENSE>`_ framework
for deep learning in healthcare imaging, part of the `PyTorch Ecosystem <https://pytorch.org/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 an optimized and standardized way to create and evaluate deep learning models.

.. image:: ../images/MONAI_arch.png
    :alt: MONAI Architecture
    :align: center

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.


Getting started
---------------

`MedNIST demo <https://colab.research.google.com/github/Project-MONAI/tutorials/blob/main/2d_classification/mednist_tutorial.ipynb>`_ and `MONAI for PyTorch Users <https://colab.research.google.com/github/Project-MONAI/tutorials/blob/main/modules/developer_guide.ipynb>`_ are available on Colab.

Examples and notebook tutorials are located at `Project-MONAI/tutorials <https://github.com/Project-MONAI/tutorials>`_.

Technical documentation is available at `docs.monai.io <https://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: Precision and Accelerating

  precision_accelerating

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

  contrib

.. toctree::
  :maxdepth: 1
  :caption: Specifications

  bundle_intro
  lazy_resampling

Model Zoo
---------

`The MONAI Model Zoo <https://github.com/Project-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 <https://docs.monai.io/en/latest/bundle_intro.html>`_ makes it easy to `get started <https://github.com/Project-MONAI/tutorials/tree/main/model_zoo>`_ building workflows with MONAI.


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
- 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/
- 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


Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`