At Agfa’s Radiological Society of North America’s (RSNA) 2019 booth, radiology professionals will discover intelligent radiography powered by the MUSICA Acquisition Workstation, the digital nerve center of every Agfa digital radiography (DR) system, including the launch of a new, groundbreaking DR unit. A comprehensive direct radiography portfolio ranging from entry-level mobile units to more advanced, multi-purpose, automated rooms, offers MUSICA-powered productivity, superb image quality and low radiation dose for healthcare facilities of every size and budget.
Visitors can discover how Agfa’s smart tools and the latest MUSICA functionalities improve staff and patient experiences. With MUSICA, imaging workflows reflect the real needs of technologists, radiologists and healthcare facilities; automatic and intelligent image processing delivers exquisite details and allows lower patient dose. In addition data is transformed into quality and performance insights. MUSICA consultancy services supply real time insights and a clear understanding of the system’s performance.
Customer-driven innovations from Agfa will be demonstrated by technologists from real hospitals, who will show how they use the DR solutions in their healthcare environments.
The MUSICA Digital Nerve Center: intelligent tools for workflow efficiency
Driven by AI and deep learning, the MUSICA Nerve Center provides operational efficiency and intelligence, with a single, intuitive interface for smooth DR general radiography, fluoroscopy, mammography and full leg/full spine (FLFS) imaging. Smart, customer-driven innovations facilitate flexibility and customization to meet the needs and tasks of technologists, radiologists and imaging facilities.
Recent MUSICA functionalities will also be highlighted, including:
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MUSICA Analytics which uses data to enhance performance and quality of care, teaming up with the users along the lifecycle of Agfa solutions.
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MUSICA 3+ solves imaging issues under the most demanding clinical requirements such as bariatric patient radiography
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Digital Tomosynthesis for multi-slice image reconstruction,
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Deep learning algorithm which automatically rotates the image as it should be presented to the radiologist,
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Advanced Dose Management through Diagnostic Reference Levels (DRL) and Extended Dose Reporting
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Full Leg Full Spine (FLFS): New Anatomic Stitching algorithm increases success rates dramatically
MUSICA supports prevention in disruptions to patient care
Agfa’s MUSICA workstation uses managed coding programming frameworks to support a more secure software and offers the latest network protocol supporting built-in security features. This allows for smoother operations and more protection throughout the equipment lifecycle. SSL protocol is replaced by the Transport Layer Security (TLS) protocol to provide the highest security over computer networks for more patient record safety.
Digital imaging for various types of facilities and budgets
Along with the MUSICA Nerve Center, Agfa’s comprehensive range of DR solutions comes with MUSICA intelligent image processing, for “first time right imaging”, and a choice of fixed, wireless and tethered detectors with Cesium Iodide (CsI) or Gadolinium Oxy-Sulphide (GOS) technology. The combined use of CsI with MUSICA image processing offers the potential for significant dose reduction.
“AI* and deep learning are changing all aspects of life, and most definitely healthcare. At RSNA 2019, we will show how we are using them to deliver customer-driven imaging solutions that put efficiency, intelligence and operational excellence to work improving the delivery of patient care,” commented Louis Kuitenbrouwer, vice president of the Radiology Solutions Division at Agfa. “With our scalable, comprehensive portfolio, the benefits of DR are within the reach of any healthcare enterprise. And all our DR solutions are powered by MUSICA – including our new, groundbreaking DR, which we are excited to launch at RSNA 2019!”
*AI is work in progress, not commercially released yet
For more information: www.agfa.com
July 25, 2024 
