Science Score: 54.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
    Found CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
  • Academic publication links
    Links to: arxiv.org
  • Academic email domains
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (18.5%) to scientific vocabulary
Last synced: 6 months ago · JSON representation ·

Repository

Basic Info
  • Host: GitHub
  • Owner: ramkotirk
  • License: apache-2.0
  • Language: Python
  • Default Branch: dev
  • Size: 322 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 1
  • Releases: 0
Created over 1 year ago · Last pushed about 1 year ago
Metadata Files
Readme Changelog Contributing License Code of conduct Citation

README.md

project-monai

Medical Open Network for AI

Supported Python versions License PyPI version docker conda

premerge postmerge Documentation Status codecov monai Downloads Last Month

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

Please see the technical highlights and What's New 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.

Installation

To install the current release, you can simply run:

bash 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.

Citation

If you have used MONAI in your research, please cite us! The citation can be exported from: https://arxiv.org/abs/2211.02701.

Model Zoo

The 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 makes it easy to get started building workflows with MONAI.

Contributing

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

Community

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

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

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
  • Wiki: https://github.com/Project-MONAI/MONAI/wiki
  • 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

Owner

  • Name: RK
  • Login: ramkotirk
  • Kind: user
  • Location: Andhra Pradesh
  • Company: GNR MART

Highly motivated and detail-oriented developer and designer with expertise in web and application development, AI, machine learning, deep learning, SQL.

Citation (CITATION.cff)

# YAML 1.2
# Metadata for citation of this software according to the CFF format (https://citation-file-format.github.io/)
#
---
title: "MONAI: Medical Open Network for AI"
abstract: "AI Toolkit for Healthcare Imaging"
authors:
  - name: "MONAI Consortium"
date-released: 2024-06-26
version: "1.3.2"
identifiers:
  - description: "This DOI represents all versions of MONAI, and will always resolve to the latest one."
    type: doi
    value: "10.5281/zenodo.4323058"
license: "Apache-2.0"
repository-code: "https://github.com/Project-MONAI/MONAI"
url: "https://monai.io"
cff-version: "1.2.0"
message: "If you use this software, please cite it using these metadata."
preferred-citation:
  type: article
  authors:
  - given-names: "M. Jorge"
    family-names: "Cardoso"
  - given-names: "Wenqi"
    family-names: "Li"
  - given-names: "Richard"
    family-names: "Brown"
  - given-names: "Nic"
    family-names: "Ma"
  - given-names: "Eric"
    family-names: "Kerfoot"
  - given-names: "Yiheng"
    family-names: "Wang"
  - given-names: "Benjamin"
    family-names: "Murray"
  - given-names: "Andriy"
    family-names: "Myronenko"
  - given-names: "Can"
    family-names: "Zhao"
  - given-names: "Dong"
    family-names: "Yang"
  - given-names: "Vishwesh"
    family-names: "Nath"
  - given-names: "Yufan"
    family-names: "He"
  - given-names: "Ziyue"
    family-names: "Xu"
  - given-names: "Ali"
    family-names: "Hatamizadeh"
  - given-names: "Wentao"
    family-names: "Zhu"
  - given-names: "Yun"
    family-names: "Liu"
  - given-names: "Mingxin"
    family-names: "Zheng"
  - given-names: "Yucheng"
    family-names: "Tang"
  - given-names: "Isaac"
    family-names: "Yang"
  - given-names: "Michael"
    family-names: "Zephyr"
  - given-names: "Behrooz"
    family-names: "Hashemian"
  - given-names: "Sachidanand"
    family-names: "Alle"
  - given-names: "Mohammad"
    family-names: "Zalbagi Darestani"
  - given-names: "Charlie"
    family-names: "Budd"
  - given-names: "Marc"
    family-names: "Modat"
  - given-names: "Tom"
    family-names: "Vercauteren"
  - given-names: "Guotai"
    family-names: "Wang"
  - given-names: "Yiwen"
    family-names: "Li"
  - given-names: "Yipeng"
    family-names: "Hu"
  - given-names: "Yunguan"
    family-names: "Fu"
  - given-names: "Benjamin"
    family-names: "Gorman"
  - given-names: "Hans"
    family-names: "Johnson"
  - given-names: "Brad"
    family-names: "Genereaux"
  - given-names: "Barbaros S."
    family-names: "Erdal"
  - given-names: "Vikash"
    family-names: "Gupta"
  - given-names: "Andres"
    family-names: "Diaz-Pinto"
  - given-names: "Andre"
    family-names: "Dourson"
  - given-names: "Lena"
    family-names: "Maier-Hein"
  - given-names: "Paul F."
    family-names: "Jaeger"
  - given-names: "Michael"
    family-names: "Baumgartner"
  - given-names: "Jayashree"
    family-names: "Kalpathy-Cramer"
  - given-names: "Mona"
    family-names: "Flores"
  - given-names: "Justin"
    family-names: "Kirby"
  - given-names: "Lee A.D."
    family-names: "Cooper"
  - given-names: "Holger R."
    family-names: "Roth"
  - given-names: "Daguang"
    family-names: "Xu"
  - given-names: "David"
    family-names: "Bericat"
  - given-names: "Ralf"
    family-names: "Floca"
  - given-names: "S. Kevin"
    family-names: "Zhou"
  - given-names: "Haris"
    family-names: "Shuaib"
  - given-names: "Keyvan"
    family-names: "Farahani"
  - given-names: "Klaus H."
    family-names: "Maier-Hein"
  - given-names: "Stephen"
    family-names: "Aylward"
  - given-names: "Prerna"
    family-names: "Dogra"
  - given-names: "Sebastien"
    family-names: "Ourselin"
  - given-names: "Andrew"
    family-names: "Feng"
  doi: "https://doi.org/10.48550/arXiv.2211.02701"
  month: 11
  year: 2022
  title: "MONAI: An open-source framework for deep learning in healthcare"
...

GitHub Events

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