# MONAI **Repository Path**: Heconnor/MONAI ## Basic Information - **Project Name**: MONAI - **Description**: No description available - **Primary Language**: Unknown - **License**: Apache-2.0 - **Default Branch**: dev - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2025-04-08 - **Last Updated**: 2025-08-08 ## Categories & Tags **Categories**: Uncategorized **Tags**: tool, tutorial ## README

project-monai

**M**edical **O**pen **N**etwork for **AI** ![Supported Python versions](https://raw.githubusercontent.com/Project-MONAI/MONAI/dev/docs/images/python.svg) [![License](https://img.shields.io/badge/license-Apache%202.0-green.svg)](https://opensource.org/licenses/Apache-2.0) [![auto-commit-msg](https://img.shields.io/badge/dynamic/json?label=citations&query=%24.citationCount&url=https%3A%2F%2Fapi.semanticscholar.org%2Fgraph%2Fv1%2Fpaper%2FDOI%3A10.48550%2FarXiv.2211.02701%3Ffields%3DcitationCount)](https://arxiv.org/abs/2211.02701) [![PyPI version](https://badge.fury.io/py/monai.svg)](https://badge.fury.io/py/monai) [![docker](https://img.shields.io/badge/docker-pull-green.svg?logo=docker&logoColor=white)](https://hub.docker.com/r/projectmonai/monai) [![conda](https://img.shields.io/conda/vn/conda-forge/monai?color=green)](https://anaconda.org/conda-forge/monai) [![premerge](https://github.com/Project-MONAI/MONAI/actions/workflows/pythonapp.yml/badge.svg?branch=dev)](https://github.com/Project-MONAI/MONAI/actions/workflows/pythonapp.yml) [![postmerge](https://img.shields.io/github/checks-status/project-monai/monai/dev?label=postmerge)](https://github.com/Project-MONAI/MONAI/actions?query=branch%3Adev) [![Documentation Status](https://readthedocs.org/projects/monai/badge/?version=latest)](https://docs.monai.io/en/latest/) [![codecov](https://codecov.io/gh/Project-MONAI/MONAI/branch/dev/graph/badge.svg?token=6FTC7U1JJ4)](https://codecov.io/gh/Project-MONAI/MONAI) [![monai Downloads Last Month](https://assets.piptrends.com/get-last-month-downloads-badge/monai.svg 'monai Downloads Last Month by pip Trends')](https://piptrends.com/package/monai) 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 as follows: - 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 > _Please see [the technical highlights](https://docs.monai.io/en/latest/highlights.html) and [What's New](https://docs.monai.io/en/latest/whatsnew.html) of the milestone releases._ - 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. ## Requirements MONAI works with the [currently supported versions of Python](https://devguide.python.org/versions), and depends directly on NumPy and PyTorch with many optional dependencies. * Major releases of MONAI will have dependency versions stated for them. The current state of the `dev` branch in this repository is the unreleased development version of MONAI which typically will support current versions of dependencies and include updates and bug fixes to do so. * PyTorch support covers [the current version](https://github.com/pytorch/pytorch/releases) plus three previous minor versions. If compatibility issues with a PyTorch version and other dependencies arise, support for a version may be delayed until a major release. * Our support policy for other dependencies adheres for the most part to [SPEC0](https://scientific-python.org/specs/spec-0000), where dependency versions are supported where possible for up to two years. Discovered vulnerabilities or defects may require certain versions to be explicitly not supported. * See the `requirements*.txt` files for dependency version information. ## Installation To install [the current release](https://pypi.org/project/monai/), you can simply run: ```bash pip install monai ``` Please refer to [the installation guide](https://docs.monai.io/en/latest/installation.html) for other installation options. ## 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). ## Citation If you have used MONAI in your research, please cite us! The citation can be exported from: . ## 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. ## Contributing For guidance on making a contribution to MONAI, see the [contributing guidelines](https://github.com/Project-MONAI/MONAI/blob/dev/CONTRIBUTING.md). ## Community Join the conversation on Twitter/X [@ProjectMONAI](https://twitter.com/ProjectMONAI), [LinkedIn](https://www.linkedin.com/company/projectmonai), or join our [Slack channel](https://forms.gle/QTxJq3hFictp31UM9). Ask and answer questions over on [MONAI's GitHub Discussions tab](https://github.com/Project-MONAI/MONAI/discussions). ## Links - Website: - API documentation (milestone): - API documentation (latest dev): - Code: - Project tracker: - Issue tracker: - Wiki: - Test status: - PyPI package: - conda-forge: - Weekly previews: - Docker Hub: