Explore more about: Computed Tomography (CT)

August 10, 2022
News
One team helped develop the first photon-counting detector (PCD)-CT system, which is superior to current CT technology. Another team has also been using artificial intelligence to lower the dose of radiation given to a patient when they are undergoing a conventional CT brain scan.
June 3, 2022
News

After less than two years of data collection and processing, RSNA has successfully delivered over 30,000 de-identified imaging studies to the Medical Imaging and Data Resource Center (MIDRC) project, an open-access platform which publishes data to be used for research. MIDRC is funded by NIBIB. Source: RSNA News

November 2, 2021
News
Researchers have demonstrated the first experimental cross-sectional medical image that doesn't require tomography, a mathematical process used to reconstruct images in CT and PET scans. The work could lead to cheaper, easier and more accurate medical imaging.
May 24, 2022
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The Medical Imaging and Data Resource Center (MIDRC), a collaboration of leading medical imaging organizations funded by NIBIB, has launched a repository of imaging data to facilitate medical imaging research on COVID-19.
May 18, 2022
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Every year thousands of Americans, mostly over age 75, require replacement of their aortic valve. Now 3D printed patient-specific models of the aorta can aid presurgical planning and improve outcomes of minimally invasive valve replacement.
September 8, 2021
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A team of engineers has demonstrated how a new algorithm they developed was able to successfully predict whether or not a COVID-19 patient would need ICU intervention. This artificial intelligence-based approach could be a valuable tool in determining a proper course of treatment for individual patients.
October 21, 2020
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Engineers have demonstrated how a deep learning algorithm can be applied to a conventional computerized tomography (CT) scan in order to produce images that would typically require a higher level of imaging technology known as dual-energy CT.
February 8, 2022
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A new article looks at the use of virtual imaging trials in effective assessment and optimization of CT and radiography acquisitions and analysis tools to help manage the coronavirus disease (COVID-19) pandemic.
March 25, 2022
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The National Institutes of Health has launched an ambitious effort to use artificial intelligence, computation, and medical imaging to enable early disease detection, inform successful treatment strategies, and predict individual disease outcomes of COVID-19.
August 6, 2021
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NIBIB-funded researchers at Stanford University have created an artificial neural network that analyzes lung CT scans to provide information about lung cancer severity that can guide treatment options.