Release of X-Ray Database to Boost AI Research
By MedImaging International staff writers Posted on 16 Oct 2017 |

Image: A normal chest x-ray (Photo courtesy of Wikipedia).
The U.S. National Institutes of Health (NIH) (Bethesda, MD, USA) recently made available a massive database of chest X-rays, marking a huge step toward integrating artificial intelligence (AI) mechanisms into clinical practice.
The release of over 100,000 anonymized chest X-ray images and their corresponding data to the scientific community by the NIH Clinical Center will allow researchers across the world to freely access the datasets and improve their ability to teach computers how to detect and diagnose disease. The AI mechanism can ultimately allow clinicians to make better diagnostic decisions for their patients.
Reading and diagnosing chest X-ray images is a complex reasoning problem which usually careful observation and knowledge of anatomical principles, physiology and pathology. This makes it more difficult to develop a consistent and automated technique for reading chest X-ray images while simultaneously considering all common thoracic diseases. The NIH has compiled the dataset of scans from over 30,000 patients, including several with advanced lung disease, after rigorous screening to remove all personally identifiable information. Academic and research institutions will be able to use this free dataset to teach a computer to read and process extremely large amounts of scans, for confirming the results found by radiologists and potentially identify other findings which may have been overlooked.
Additionally, the 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 who 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 such as CT and MRI in the future.
In line with its ongoing commitment to data sharing, the NIH research hospital expects to continue adding a large dataset of CT scans to be made available over the coming months.
Related Links:
U.S. National Institutes of Health
The release of over 100,000 anonymized chest X-ray images and their corresponding data to the scientific community by the NIH Clinical Center will allow researchers across the world to freely access the datasets and improve their ability to teach computers how to detect and diagnose disease. The AI mechanism can ultimately allow clinicians to make better diagnostic decisions for their patients.
Reading and diagnosing chest X-ray images is a complex reasoning problem which usually careful observation and knowledge of anatomical principles, physiology and pathology. This makes it more difficult to develop a consistent and automated technique for reading chest X-ray images while simultaneously considering all common thoracic diseases. The NIH has compiled the dataset of scans from over 30,000 patients, including several with advanced lung disease, after rigorous screening to remove all personally identifiable information. Academic and research institutions will be able to use this free dataset to teach a computer to read and process extremely large amounts of scans, for confirming the results found by radiologists and potentially identify other findings which may have been overlooked.
Additionally, the 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 who 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 such as CT and MRI in the future.
In line with its ongoing commitment to data sharing, the NIH research hospital expects to continue adding a large dataset of CT scans to be made available over the coming months.
Related Links:
U.S. National Institutes of Health
Latest Industry News News
- GE HealthCare and NVIDIA Collaboration to Reimagine Diagnostic Imaging
- Patient-Specific 3D-Printed Phantoms Transform CT Imaging
- Siemens and Sectra Collaborate on Enhancing Radiology Workflows
- Bracco Diagnostics and ColoWatch Partner to Expand Availability CRC Screening Tests Using Virtual Colonoscopy
- Mindray Partners with TeleRay to Streamline Ultrasound Delivery
- Philips and Medtronic Partner on Stroke Care
- Siemens and Medtronic Enter into Global Partnership for Advancing Spine Care Imaging Technologies
- RSNA 2024 Technical Exhibits to Showcase Latest Advances in Radiology
- Bracco Collaborates with Arrayus on Microbubble-Assisted Focused Ultrasound Therapy for Pancreatic Cancer
- Innovative Collaboration to Enhance Ischemic Stroke Detection and Elevate Standards in Diagnostic Imaging
- RSNA 2024 Registration Opens
- Microsoft collaborates with Leading Academic Medical Systems to Advance AI in Medical Imaging
- GE HealthCare Acquires Intelligent Ultrasound Group’s Clinical Artificial Intelligence Business
- Bayer and Rad AI Collaborate on Expanding Use of Cutting Edge AI Radiology Operational Solutions
- Polish Med-Tech Company BrainScan to Expand Extensively into Foreign Markets
- Hologic Acquires UK-Based Breast Surgical Guidance Company Endomagnetics Ltd.
Channels
Radiography
view channel
World's Largest Class Single Crystal Diamond Radiation Detector Opens New Possibilities for Diagnostic Imaging
Diamonds possess ideal physical properties for radiation detection, such as exceptional thermal and chemical stability along with a quick response time. Made of carbon with an atomic number of six, diamonds... Read more
AI-Powered Imaging Technique Shows Promise in Evaluating Patients for PCI
Percutaneous coronary intervention (PCI), also known as coronary angioplasty, is a minimally invasive procedure where small metal tubes called stents are inserted into partially blocked coronary arteries... Read moreMRI
view channel
New MRI Technique Reveals True Heart Age to Prevent Attacks and Strokes
Heart disease remains one of the leading causes of death worldwide. Individuals with conditions such as diabetes or obesity often experience accelerated aging of their hearts, sometimes by decades.... Read more
AI Tool Predicts Relapse of Pediatric Brain Cancer from Brain MRI Scans
Many pediatric gliomas are treatable with surgery alone, but relapses can be catastrophic. Predicting which patients are at risk for recurrence remains challenging, leading to frequent follow-ups with... Read more
AI Tool Tracks Effectiveness of Multiple Sclerosis Treatments Using Brain MRI Scans
Multiple sclerosis (MS) is a condition in which the immune system attacks the brain and spinal cord, leading to impairments in movement, sensation, and cognition. Magnetic Resonance Imaging (MRI) markers... Read more
Ultra-Powerful MRI Scans Enable Life-Changing Surgery in Treatment-Resistant Epileptic Patients
Approximately 360,000 individuals in the UK suffer from focal epilepsy, a condition in which seizures spread from one part of the brain. Around a third of these patients experience persistent seizures... Read moreUltrasound
view channel.jpeg)
AI-Powered Lung Ultrasound Outperforms Human Experts in Tuberculosis Diagnosis
Despite global declines in tuberculosis (TB) rates in previous years, the incidence of TB rose by 4.6% from 2020 to 2023. Early screening and rapid diagnosis are essential elements of the World Health... Read more
AI Identifies Heart Valve Disease from Common Imaging Test
Tricuspid regurgitation is a condition where the heart's tricuspid valve does not close completely during contraction, leading to backward blood flow, which can result in heart failure. A new artificial... Read moreNuclear Medicine
view channel
Novel Radiolabeled Antibody Improves Diagnosis and Treatment of Solid Tumors
Interleukin-13 receptor α-2 (IL13Rα2) is a cell surface receptor commonly found in solid tumors such as glioblastoma, melanoma, and breast cancer. It is minimally expressed in normal tissues, making it... Read more
Novel PET Imaging Approach Offers Never-Before-Seen View of Neuroinflammation
COX-2, an enzyme that plays a key role in brain inflammation, can be significantly upregulated by inflammatory stimuli and neuroexcitation. Researchers suggest that COX-2 density in the brain could serve... Read moreGeneral/Advanced Imaging
view channel
AI-Powered Imaging System Improves Lung Cancer Diagnosis
Given the need to detect lung cancer at earlier stages, there is an increasing need for a definitive diagnostic pathway for patients with suspicious pulmonary nodules. However, obtaining tissue samples... Read more
AI Model Significantly Enhances Low-Dose CT Capabilities
Lung cancer remains one of the most challenging diseases, making early diagnosis vital for effective treatment. Fortunately, advancements in artificial intelligence (AI) are revolutionizing lung cancer... Read moreImaging IT
view channel
New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible
Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more