News | Artificial Intelligence | October 10, 2017

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

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

Machine Learning IDs Markers to Help Predict Alzheimer's

Neurologists use structural and diffusion magnetic resonance imaging (MRI) to identify changes in brain tissue (both gray and white matter) that are characteristic of Alzheimer's disease and other forms of dementia. The MRI images are analyzed using morphometry and tractography techniques, which detect changes in the shape and dimensions of the brain and in the tissue microstructure, respectively. In this example, the images show the normal brain of an elderly patient. Image courtesy of Jiook Cha.

News | Neuro Imaging | September 20, 2018
New research has shown a combination of two different modes of magnetic resonance imaging (MRI), computer-based...
LVivo EF Cardiac Tool Now Available for GE Vscan Extend Handheld Mobile Ultrasound
Technology | Cardiovascular Ultrasound | September 19, 2018
DiA Imaging Analysis Ltd. (DiA), a provider of artificial intelligence (AI)-powered ultrasound analysis tools,...
Exact Imaging Partners to Improve Prostate Cancer Detection With Artificial Intelligence
News | Prostate Cancer | September 19, 2018
Exact Imaging, makers of the ExactVu micro-ultrasound platform, has partnered with U.K.-based Cambridge Consultants to...
SimonMed Deploys ClearRead CT Enterprise Wide
News | Computer-Aided Detection Software | September 17, 2018
September 17, 2018 — National outpatient physician radiology group SimonMed Imaging has selected Riverain Technologie
Agfa Brings Intelligent Radiography to RSNA 2018
News | Digital Radiography (DR) | September 17, 2018
September 17, 2018 — At the 2018 Radiological Society of North America (RSNA) annual meeting, Nov.
The DRX-Transportable System/Lite
News | X-Ray | September 12, 2018
Columbus Regional Health (Columbus, Ind.) has deployed a Carestream ...
Veye Chest version 2
News | Lung Cancer | September 11, 2018
Aidence, an Amsterdam-based medical AI company, announced that Veye Chest version 2, a class IIa medical device, has
Mount Sinai Serves as Official Medical Services Provider for 2018 U.S. Open
News | Orthopedic Imaging | September 06, 2018
For the sixth consecutive year, Mount Sinai will serve as the official medical services provider for the 2018 U.S. Open...
GlobalData: Amazon Poised to Make Huge Strides in Healthcare
News | Radiology Business | August 31, 2018
A new report from data and analytics company GlobalData suggests that Amazon is poised to make huge strides in...
Videos | Treatment Planning | August 28, 2018
A discussion with...