Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

project-monai

Medical Open Network for AI

License CI Build Documentation Status codecov PyPI version

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

The codebase is currently under active development. Please see the technical highlights and What's New of the current milestone release.

  • 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.

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.

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.

Release files for monai-weekly 0.10.dev2237

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for monai-weekly 0.10.dev2237
File Size Uploaded
monai-weekly-0.10.dev2237.tar.gz 830.9 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for monai-weekly 0.10.dev2237
File Interpreter ABI Platform
monai_weekly-0.10.dev2237-py3-none-any.whl Python 3 none any Details

Total release size: 1.9 MB

Release files / monai-weekly-0.10.dev2237.tar.gz

Download URL monai-weekly-0.10.dev2237.tar.gz
Size 830.9 kB
Tags Source
SHA-256 checksum
How to use checksums
eede23dda6ead40dcc410dc6b0ddbbcd5e1b60f9e7223e7d323e751224b21ef1
BLAKE2b-256 checksum
How to use checksums
e27cab3bf78d0a51161493034e79a8578ab0625431f5eb4a8488662e930e812e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.14

Release files / monai_weekly-0.10.dev2237-py3-none-any.whl

Download URL monai_weekly-0.10.dev2237-py3-none-any.whl
Size 1.1 MB
Tags Python 3
SHA-256 checksum
How to use checksums
6bd91e58a53eb4e560488cddc9536a94f2885b56eaeb9517b98790f6c70a059e
BLAKE2b-256 checksum
How to use checksums
20c174d0b6a34b72cb2f8051b20784c8b79d5af0ddacdd4f06336cff4cc9d0b7
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.1 CPython/3.9.14

Release history Release notifications | RSS feed

This release

0.10.dev2237 This release

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page