Skip to main content

Active Learning Toolkit for Healthcare Imaging

Project description

MONAI Label

License CI Build Documentation Status codecov PyPI version

MONAI Label is a server-client system that facilitates interactive medical image annotation by using AI. It is an open-source and easy-to-install ecosystem that can run locally on a machine with one or two GPUs. Both server and client work on the same/different machine. However, initial support for multiple users is restricted. It shares the same principles with MONAI.

Brief Demo

Features

The codebase is currently under active development.

  • framework for developing and deploying MONAI Label Apps to train and infer AI models
  • compositional & portable APIs for ease of integration in existing workflows
  • customizable design for varying user expertise
  • 3DSlicer support

Installation

MONAI Label supports following OS with GPU/CUDA enabled.

To install the current release, you can simply run:

  pip install monailabel
  
  # download sample apps/dataset
  monailabel apps --download --name deepedit_left_atrium --output apps
  monailabel datasets --download --name Task02_Heart --output datasets
  
  # run server
  monailabel start_server --app apps\deepedit_left_atrium --studies datasets\Task02_Heart\imagesTr
  

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

Once you start the MONAI Label Server, by default it will be up and serving at http://127.0.0.1:8000/. Open the serving URL in browser. It will provide you the list of Rest APIs available.

3D Slicer

Download Preview Release from https://download.slicer.org/ and install MONAI Label plugin from Slicer Extension Manager.

Refer 3D Slicer plugin for other options to install and run MONAI Label plugin in 3D Slicer.

Contributing

For guidance on making a contribution to MONAI Label, see the contributing guidelines.

Community

Join the conversation on Twitter @ProjectMONAI or join our Slack channel.

Ask and answer questions over on MONAI Label's GitHub Discussions tab.

Links

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

monailabel-weekly-0.2.dev2130.tar.gz (1.2 MB view details)

Uploaded Source

Built Distribution

monailabel_weekly-0.2.dev2130-py3-none-any.whl (1.3 MB view details)

Uploaded Python 3

File details

Details for the file monailabel-weekly-0.2.dev2130.tar.gz.

File metadata

  • Download URL: monailabel-weekly-0.2.dev2130.tar.gz
  • Upload date:
  • Size: 1.2 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6

File hashes

Hashes for monailabel-weekly-0.2.dev2130.tar.gz
Algorithm Hash digest
SHA256 1b56da3f1748b798ec9ea10c68916131a5ae53ca6bac8608f3a352558a6f5f6d
MD5 0d84aa8f9a93580be0be3423e6b45cfe
BLAKE2b-256 648675fb4ff96989133d32eb84ee6c20f9f52efac3c67b42ba0980d342d4e126

See more details on using hashes here.

File details

Details for the file monailabel_weekly-0.2.dev2130-py3-none-any.whl.

File metadata

  • Download URL: monailabel_weekly-0.2.dev2130-py3-none-any.whl
  • Upload date:
  • Size: 1.3 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.2 importlib_metadata/4.6.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.9.6

File hashes

Hashes for monailabel_weekly-0.2.dev2130-py3-none-any.whl
Algorithm Hash digest
SHA256 370f7493294e856f78067f393347bf1fb25bd2651dd32674b720974f19ef3610
MD5 b15b1ebaf3a8352ac83883d5dafa152f
BLAKE2b-256 d0958b0b6afb14ceb511f86ff9b23d1206ebe2d0cdad48c8165226ddd0be6b96

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page