Virtual reality (VR) and its less immersive kin, augmented reality (AR), are gaining traction in some medical applications. But a new entrant, “mixed reality,” may have the inside track in the interventional suite or operating room.
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Machine learning is already having an enormous impact on cardiology, automatically calculating measurements in echocardiograpy.
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Debate About Coronary Testing Highlights ACC Session
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How smart algorithms might reduce the burden of modern practice
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Computed tomography (CT) and magnetic resonance imaging (MRI) scans are chock full of information that might be used to personalize treatment. Unfortunately, this information is not readily available.
Jennifer N. A. Silva, M.D., a pediatric cardiologist at Washington University School of Medicine in Saint Louis, Mo., describes “mixed reality” at ACC19 Future Hub.
Feature | Cardiac Imaging | March 17, 2019 | By Greg Freiherr
Virtual reality (VR) and its less immersive kin, augmented reality (AR), are gaining traction in some medical...
WVU cardiology chief Partho Sengupta, M.D., describes at ACC 2019 how artificial intelligence already helps cardiologists in echocardiography. Photo by Greg Freiherr
Feature | Cardiac Imaging | March 16, 2019 | By Greg Freiherr
Machine learning is already having an enormous impact on cardiology, automatically calculating measurements in...
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News | PET-CT | February 06, 2019
Technological advancements in positron emission tomography/computed tomography (PET/CT) offer both clinicians and...
News | Magnetic Resonance Imaging (MRI) | March 15, 2019
March 15, 2019 — Calcium is a critical signaling molecule for most cells, and it is especially important in neurons...
Technology | Mammography | March 15, 2019
March 15, 2019 — Fujifilm Medical Systems USA announced it has fulfilled all U.S. Food and Drug Administration (FDA...
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The KDR-UA shows positioning for an ankle radiograph. (Photo courtesy of Konica Minolta.)
Blog | X-Ray | January 09, 2019
The pressure to be efficient and effective when imaging outpatients may be rising due to imaging’s increased...
News | Computed Tomography (CT) | March 14, 2019
March 14, 2019 — Canon Medical Systems Europe B.V. introduced the all-new Aquilion Start...
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A 90-second brain acquisition with FDG radiotracer — comparison of digital (Vereos, left, 1 mm) and conventional (Gemini TF, 4 mm) images.
Blog | PET Imaging | December 11, 2018
Digital technology is opening remarkable opportunities for clinical...
News | Endoscopes | March 14, 2019
March 14, 2019 — Hologic Inc. announced it has received a CE mark in Europe for its Omni...
Prototype fluidic system for zirconium-89 purification. Image taken through a hot cell window at the Department of Radiology, University of Washington. Image courtesy of Matthew O’Hara, Pacific Northwest National Laboratory
News | Radiopharmaceuticals and Tracers | March 14, 2019
March 14, 2019 — A team of researchers at the University of Washington announced they developed a new automated...
News | Computed Tomography (CT) | March 14, 2019
March 14, 2019 — Siemens Healthineers will introduced the Somatom go.Top Cardiovascular Edition, a new version of...
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There were more than 150 companies showing some version of artificial intelligence at RSNA, but very few have FDA cleared products for sale. One of the trends seen on the floor was a movement toward AI app stores where these start-up companies can offer their wares through a larger vendor and provide a single point of contracts and IT integration for hospitals.
Blog | RSNA | November 29, 2018
Artificial intelligence (AI) and enterprise imaging were among the top trends at the Radiological Society of North...
News | Proton Therapy | March 13, 2019
March 13, 2019 — The number of new particle therapy rooms ordered worldwide dropped by almost 20 percent in 2018,...
News | Ultrasound Imaging | March 13, 2019
March 13, 2019 – Esaote announced the launch of MyLab X8, a high-performance, versatile...
Sponsored Content | Videos | Artificial Intelligence | March 13, 2019
At RSNA 2018, iCad showed how its...
Pseudocolor accentuated CT scan image of a liver tumor. Image courtesy of Lucence Diagnostics.
News | Oncology Diagnostics | March 12, 2019
March 12, 2019 — Genomic medicine company Lucence Diagnostics announced a new project to develop...
Images show illustrative examples of visual R2? modifications within substantia nigra (SN) at baseline (24-72 h) and follow-up (1 y) in striatum (participants 1 and 2) and control groups (participants 3 and 4). Image courtesy of the Radiological Society of North America (RSNA).
News | Stroke | March 12, 2019
March 12, 2019 — A simple...
Podcast | Cardiac Imaging | March 12, 2019
Smart algorithms could make cardiology “more fun and less burdensome,” said...
Collage depicts broad applications in machine learning or deep learning (DL) that can be applied to advanced medical imaging technologies. Size of the liver and its fat fraction — 22 percent — (top middle in collage) can be quantified automatically using an algorithm developed by Dr. Albert Hsiao and his team at the University of California San Diego. This and other information that might be mined by DL algorithms from CT and MR images could help personalize patients’ treatment. Collage provided by Albert Hsiao
Feature | Cardiac Imaging | March 11, 2019 | By Greg Freiherr
Computed tomography (CT) and magnetic resonance imaging (MRI) scans are chock full of information that might be used...
