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The VinDr Lab is a Data Platform for Medical AI that enables building high-quality datasets and algorithms with the lean process and advanced annotation features. The software is provided by the Medical Imaging team at Vingroup Big Data Institute (VinBigdata).

Gitter MIT License



VinDr Lab is an open-source platform for medical image annotation. It has been developed to remove the ground-truth barrier AI teams met to build meaningful medical AI applications. VinDr Lab provides a high-level web interface equipped with advanced annotation tools and project management features.


The following features have been implemented:

  • Manage full medical data cycle at they study level
  • Track project progress and status of each task
  • Create and share label groups
  • Organize labels by order and hierarchy
  • Annotation tools: Bounding box, Polygon, Brush, Notes, Comments
  • Control versions of exported labels

This project is still in active development, so some options may not be fully implemented yet.

Future features

  • Annotation in MPR view
  • AI itergration

You can read more about the platform on

What's here

This repo is the "master" repo for all VinDr Lab-related projects. It hosts the documentation and other misc. resources for VinDr Lab. Code for other projects, like backend and frontend, is hosted in other repositories.

Project Index

All VinDr Lab projects and repositories underneath the VinBigdata Medical GitHub organization are listed here. To learn more about each project, see the README in each repository.

Repository Description Maintainers
vinbigdata-medical/vindr-lab Documentation and other general resources related to VinDr Lab @lego1st, @fuzzysource
vinbigdata-medical/vindr-lab-deployment Getting started with VinDr Lab. We support Kubernetes or Docker deployments. @iamatsundere
vinbigdata-medical/vindr-lab-api Middleware layer between the user interface and backend systems @iamatsundere
vinbigdata-medical/vindr-lab-id-generator For each study or task of a project, this service generates a new integer value based on the key as a string. @iamatsundere
vinbigdata-medical/vindr-lab-uploader Uploader modifies and transfers the DICOM files to the database. @iamatsundere
vinbigdata-medical/vindr-lab-viewer Frontend: Viewer allows the manipulation, annotation, and serialization of observations and many more features. @HoAnhVan
vinbigdata-medical/vindr-lab-dashboard Frontend: Dashboard support data management and labeling administration @HoAnhVan

Note: Another way to find all VinDrLab-related repositories is to go to Vinbigdata Medical GitHub main page and enter the search term "vindr-lab", like here.

Get started

Our project requires at least 4GB of RAM system for the best performance and experiment. We support both Kubernetes and Docker deployments. Please visit VinDr Lab Deployment to start !


Project documentation is hosted on our Github page. We are hoping to establish a more user-friendly version soon.


For quick questions, there's no need to open an issue as you can reach us on Gitter.

If you're an experienced dev and interested in contributing to VinDr Lab:


To acknowledge VinDr Lab in an academic publication, please cite

@misc{VinDr Lab,
  author =       {Nghia T. Nguyen, Phuc T. Truong, Van T. Ho, Trung V. Nguyen, Hieu T. Pham, Mi T. Nguyen, Long T. Dam, Ha Q. Nguyen},
  title =        {{VinDr Lab: A Data Platform for Medical AI}},
  howpublished = {\url{}},
  year =         {2021}

Note: If you use or find this repository helpful, please take the time to star this repository on Github. This is an easy way for us to assess the adoption and it can help us obtain future funding for the project.

This work is supported primarily by Vingroup Big Data Institute

Team members

Lego1st fuzzysource iamatsundere HoAnhVan trung1704ptit EdwardPham1615 minguyenn
Lego1st fuzzysource iamatsundere HoAnhVan trung1704ptit EdwardPham1615 minguyenn


MIT License


A Data Platform for Medical AI that enables building high-quality datasets and algorithms with lean process and advanced annotation features.







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