News | Artificial Intelligence | October 10, 2017

Compiled from scans of more than 30,000 patients, datasets are intended to help train artificial intelligence algorithms to aid radiologists in diagnosis

NIH Clinical Center Releases 100,000-Plus Chest X-ray Datasets to Scientific Community

October 10, 2017 — The National Institutes of Health (NIH) Clinical Center recently released over 100,000 anonymized chest X-ray images and their corresponding data to the scientific community. The release will allow researchers across the country and around the world to freely access the datasets and increase their ability to teach computers how to detect and diagnose disease. Ultimately, this artificial intelligence mechanism can lead to clinicians making better diagnostic decisions for patients. 

NIH compiled the dataset of scans from more than 30,000 patients, including many with advanced lung disease. Patients at the NIH Clinical Center, the nation’s largest hospital devoted entirely to clinical research, are partners in research and voluntarily enroll to participate in clinical trials. With patient privacy being paramount, the dataset was rigorously screened to remove all personally identifiable information before release.

Reading and diagnosing chest X-ray images may be a relatively simple task for radiologists but, in fact, it is a complex reasoning problem that often requires careful observation and knowledge of anatomical principles, physiology and pathology. Such factors increase the difficulty of developing a consistent and automated technique for reading chest X-ray images while simultaneously considering all common thoracic diseases.

By using this free dataset, the hope is that academic and research institutions across the country will be able to teach a computer to read and process extremely large amounts of scans, to confirm the results radiologists have found and potentially identify other findings that may have been overlooked.

In addition, this advanced computer technology may also be able to:

  • Help identify slow changes occurring over the course of multiple chest X-rays that might otherwise be overlooked;
  • Benefit patients in developing countries that do not have access to radiologists to read their chest X-rays; and 
  • Create a virtual radiology resident that can later be taught to read more complex images like computed tomography (CT) and magnetic resonance imaging (MRI) in the future.

The NIH research hospital anticipates adding a large dataset of CT scans to be made available as well in the coming months.

For more information: www.clinicalcenter.nih.gov

 

Related Content on Artificial Intelligence in Radiology

Artificial Intelligence Could Learn From the Medical Imaging Goldmine of the NHS Archives

VIDEO: Machine Learning and the Future of Radiology

How Artificial Intelligence Will Change Medical Imaging

Must Radiologists Be Prepared To Delegate ... To Smart Machines?


Related Content

News | Magnetic Resonance Imaging (MRI)

March 25, 2026 A Penn Medicine–led team has developed a first‑of‑its‑kind artificial intelligence system that interprets ...

Time March 26, 2026
arrow
News | FDA

March 24, 2026 — MARS Bioimaging, a New Zealand–headquartered medical device company, has received U.S. Food and Drug ...

Time March 25, 2026
arrow
News | Cybersecurity

March 23, 2026 —Sacumen has launched ConnectX, a unified AI platform that gives cybersecurity product companies full ...

Time March 25, 2026
arrow
News | Pediatric Imaging

March 17, 2026 – OXOS Medical recently announced that its MC2 portable X-ray system is now cleared for pediatric imaging ...

Time March 23, 2026
arrow
News | Magnetic Resonance Imaging (MRI)

March 18, 2026 — GE HealthCare and Springbok Analytics have entered a development agreement that will aim to leverage ...

Time March 18, 2026
arrow
News | Radiology Business

March 12, 2026 — DelveInsight's has released its latest Diagnostic Imaging Equipment Market Insights report. The in ...

Time March 13, 2026
arrow
News | Stroke

March 11, 2026 — Brainomix, a provider of AI-powered imaging tools for stroke and lung fibrosis, has announced the ...

Time March 11, 2026
arrow
News | HIMSS

March 9, 2026 — Fujifilm Healthcare Americas Corp. is showcasing how its latest AI-powered enterprise imaging solutions ...

Time March 10, 2026
arrow
News | HIMSS

March 5, 2026 — At the Health Information and Management Systems Society (HIMSS) Conference & Exhibition 2026 in Las ...

Time March 06, 2026
arrow
News | Radiation Oncology

March 4, 2026 — Lunit has announced that 21 studies featuring its AI solutions will be presented at the European ...

Time March 05, 2026
arrow
Subscribe Now