RadNet : Experts Discuss the AI Revolution in Applied Radiology
January 21, 2021 at 11:44 pm IST
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21 January, 2021
The coming year brings a revolution in the application of artificial intelligence to computed tomography (CT) and magnetic resonance (MR) procedures. AI products have been refined to such an extent that the advantages-lower radiation dose, higher image quality, more efficient scanning, and streamlined workflows-are clear. Lawrence Tanenbaum, MD, FACR, and Suzie Bash, MD, discuss how deep learning reconstruction (DLR) tools are leveraged in CT and MR and the possibilities for the future of imaging.
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21 January, 2021
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RadNet Inc. published this content on 21 January 2021 and is solely responsible for the information contained therein. Distributed by Public, unedited and unaltered, on 21 January 2021 18:13:03 UTC
RadNet, Inc. is a national provider of fixed-site diagnostic imaging services and related information technology solutions (including artificial intelligence) in the United States. It has a network of 366 owned and/or operated outpatient imaging centers. The Companyâs Imaging Center segment provides physicians with imaging capabilities to facilitate the diagnosis and treatment of diseases and disorders. Its services include magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), nuclear medicine, mammography, ultrasound, diagnostic radiology (X-ray), fluoroscopy and other related procedures. The Companyâs Artificial Intelligence (AI) segment develops and deploys clinical applications to enhance interpretation of medical images and improve patient outcomes with an emphasis on brain, breast, prostate and pulmonary diagnostics. The Company, through its joint ventured Arizona Diagnostic Radiology Group, LLC, owns seven outpatient imaging centers.