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

For other installation methods (using the default GitHub branch, using Docker, etc.), please refer to the installation guide.

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 0.9.dev2216

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 0.9.dev2216
File Size Uploaded
monai-weekly-0.9.dev2216.tar.gz 599.6 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for monai-weekly 0.9.dev2216
File Interpreter ABI Platform
monai_weekly-0.9.dev2216-py3-none-any.whl Python 3 none any Details

Total release size: 1.4 MB

Release files / monai-weekly-0.9.dev2216.tar.gz

Download URL monai-weekly-0.9.dev2216.tar.gz
Size 599.6 kB
Tags Source
SHA-256 checksum
How to use checksums
1d0252bf5f17fe8b588d572a384c65fd7a06d1b4fda369a896d7bd498f388913
BLAKE2b-256 checksum
How to use checksums
3759ddb0508da4a21e71028cf31983e4ebc5ac035646e652426cfdc126f016b8
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.0 CPython/3.9.12

Release files / monai_weekly-0.9.dev2216-py3-none-any.whl

Download URL monai_weekly-0.9.dev2216-py3-none-any.whl
Size 786.3 kB
Tags Python 3
SHA-256 checksum
How to use checksums
b167075cf683d0224ee523536ef93534dac09084d29f908695e653c416ec816f
BLAKE2b-256 checksum
How to use checksums
2f45de1934e4605f05581892cc5fd6f875b84929b773c143a1506834c41f41ff
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.0 CPython/3.9.12

Release history Release notifications | RSS feed

This release

0.9.dev2216 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