Radiological investigations have a high sensitivity for diagnosing COVID-19. We are a pro bono public health research initiative building the COVID-19 RADS and your contribution with scans and observations can help us build AI assisted reporting and data standards. We welcome Physicians, Public Health researchers and practitioners, Policy Makers, AI model builders and data science researchers, Pro bono initiatives, organizations and individuals dedicated to use the datasets and engineer scalable rapid screening solutions.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The World Health Organization (WHO) declared the 2019–20 coronavirus outbreak a Public Health Emergency of International Concern (PHEIC) on 30 January 2020 and a pandemic on 11 March 2020.

COVID-19 RADS is a community intellect contribution driven Radiology Reporting and Data Standards for clinical management of COVID-19 symptomatic cases.

I would like to contribute. I am a

You can contribute scans or annotate cases in our library of X-Ray, CT and Ultrasound scans of suspicious COVID-19 cases, pneumonia and associated co-morbidities.Enroll and start contributing to build COVID-19 RADS.

You can contribute COVID-19 scans to our dataport and contribute to building the patient handling and clinical management protocol for Radiological scanning. Any other views are also welcome. Enroll and start contributing to build COVID-19 RADS.

You can contribute to whitepapers and discussion groups on building COVID-19 RADS with inclusion of public health concerns in the overall management of suspicious subjects. Enroll and start contributing to build COVID-19 RADS.

You can contribute by analysing the data, relating Radiologists’ observations to diagnostic outcomes and algorithmically accelerate development of the COVID-19 RADS as well as build AI models to scale up Radiological rapid screen of symptomatic subjects.Enroll

You can contribute to the COVID-19 management strategy by making use of our whitepapers and listing of related literatures. You can also contribute a policy document which shall be of relevance to COVID-19 RADS. Enroll and start contributing to build COVID-19 RADS.

You can contribute with your ideas to the action group beyond our usual comprehension listed here. Enroll and share your views to strengthen this action group and the cause.

As a professional association of Engineers, Physicians, Scientists, Teachers and all, you have the ability to collectively create the knowledge base for COVID-19 RADS. Enroll and tell us how you wish to join us and contribute to the cause.

You can partner with us, exchanging anonymized data of relevance to building the COVID-19 RADS and list your initiative as a supporter to pool in our mutual strengths. Enroll and collaborate to co-build COVID-19 RADS.

You can extend physical resources like storage, cloud, compute, radiological scanners, PCR reports and intellectual potential to help us build COVID-19 RADS and AI models for screening radiology. Enroll and tell us how you wish to join us.

Join Our Mission

Access COVID-19 RADS and Whitepapers

Access the COVID-19 RADS sheets for reporting of X-Ray, CT and Ultrasound scans. Read more about how we are building the COVID-19 RADS with AI assistance, published case report and clinical literature, and your crowdsourced knowledge contribution.

Access Dataset to build AI Models

As an AI model builder and data science researcher, you can gain access to X-Ray, CT and Ultrasound scans, annotations of observations in COVID-19 RADS, shared anonymously under Creative Commons License for building image based screening models and to refine the COVID-19 RADS.

Contribute to the Dataport

As a Radiologist you can contribute scans of suspicious cases and PCR if available to build a crowdsourced repository of case reports. Share anonymously under Creative Commons License and these will be used for rapidly building AI driven radiology reporting and data standards.

Browse Case Reports

See example scans annotated using the COVID-19 RADS to learn about observations in suspicious patients which indicate their differential diagnosis. All images and consolidated annotations are shared anonymously under Creative Commons License

Contribute Annotations to COVID-19 RADS

As a Radiologist you can contribute by annotating our existing library of cases with your observations. These crowdsourced annotations will be used for associating observations to diagnostic outcomes indicative of COVID-19, assisted by AI models to accelerate this process. Share anonymously under Creative Commons License

Contribute to the AI Model Zoo

Share your AI models for COVID-19 RADS improvisation and image classification on our model zoo, which can be accessed by others in the community for accelerating and scaling up radiological screening for COVID-19. Share your code base under Apache-2.0 and trained models under Creative Commons License.

and Contribute



  • 26 March 2020

    Launch of the portal and enrolment started.

  • 27 March 2020

    COVID-19 RADS and whitepaper released.

  • 27 April 2020

    Dataset access for AI Model builders

  • (TBA)

    Data port open for contributions

  • (TBA)

    Case reports available for browsing

  • (TBA)

    AI Model Zoo launched

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Ethics and Data Protection

Contributor identity is anonymized and shall not be shared with anyone unless waived off by the contributor. All other information as indicated in the license file are shared under Creative Commons License or Apache-2.0. Read detailed Disclaimer


Debdoot Sheet, PhD

Tandra Sarkar, Radiologist

Nishant Chakravorty, PhD

Arunava Chakravarty, PhD

Manjira Sinha, PhD

Rachana Sathish

Rakshith Sathish

Manoj Sharma

Ronnie Rajan, MBBS

Velmurugan Balasubramanian, MBBS

Aditya Raj

Vikas Kumar

Atul Singhal

Gowtham Reddy

Rajiv Kumar

Abhishek Kumar