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DiA Imaging Analysis' AI-Powered LVivo EF Cardiac Tool Now Available for the GE Healthcare Vscan Extend™ Handheld Mobile Ultrasound

DiA Imaging Analysis' AI-Powered LVivo EF Cardiac Tool Now Available for the GE Healthcare Vscan Extend™ Handheld Mobile Ultrasound First-ever automated EF analysis solution on mobile ultrasound supports efficient, real-time clinical decision-making in point-of-care settings

PR Newswire

BE'ER SHEVA, Israel, and HARTFORD, Conn., Sept. 18, 2018

BE'ER SHEVA, Israel, and HARTFORD, Conn., Sept. 18, 2018 /PRNewswire/ -- DiA Imaging Analysis Ltd. (DiA), a provider of artificial intelligence (AI)-powered ultrasound analysis tools, announced today that its LVivo EF cardiac decision-support software is now available for purchase for GE's new Vscan Extend™ handheld, pocket-sized ultrasound. This collaboration is an outgrowth of work between DiA and GE Healthcare that began last year.

LVivo EF is the first AI-powered, ejection fraction automated app able to operate in the low-memory and processing-power environments of mobile ultrasound. (Watch a short preview here:

Ejection fraction (EF) evaluation is a key diagnostic criterion driving various treatment strategies in point-of-care (POC) settings—particularly in emergency medicine, intensive care and anesthesia.

"As handheld, point-of-care ultrasound procedures expand across the industry, and AI plays a growing role in ultrasound analysis, working with GE Healthcare is the beginning of transforming point-of-care ultrasound to a more consistent and patient-centered process," said DiA CEO and co-founder Hila Goldman-Aslan. "As the first automated EF software tool on a handheld ultrasound, we are confident that clinicians across emergency, primary care, ICU and other point-of-care settings will immediately recognize how LVivo EF empowers their real-time decision-making and enhances efficiency."

Traditionally, most EF interpretation at POC is conducted through visual estimation, with clinician experience levels varying across POC settings. This means that achieving an accurate EF result in POC settings can be challenging. LVivo EF addresses this challenge by quickly and efficiently providing clinicians with left ventricle EF scoring and volume measurements via DiA's  advanced, proprietary AI technology and advanced pattern recognition algorithms that imitate the way the human eye identifies borders and motion.

"Offering the LVivo EF app underscores GE Healthcare's continued commitment to supporting clinicians with improved productivity," said Rob Walton, general manager of GE Healthcare Primary Care Ultrasound. "By collaborating with third-party developers and experienced Vscan Extend users, GE Healthcare has been able to offer apps that give users the option to customize their Vscan Extend according to their unique needs."

LVivo EF is part of the DiA cardiac toolbox. The company offers additional cardiac ultrasound decision-support apps—which, like LVivo EF—are U.S. FDA-cleared and CE Marked in the European Union.

DiA is exhibiting at the innovatED Exhibit Hall (#1543) at the American College of Emergency Physicians (ACEP) Scientific Assembly October 1−3 in San Diego, where both DiA and GE Healthcare will demo the LVivo EF app on the GE Healthcare Vscan Extend™. Goldman-Aslan will explain more about LVivo EF and DiA's other AI-powered, automated decision support tools at the digital health pitch event starting at 11:45 a.m. Pacific Time on Wednesday, Oct. 3.

About DiA Imaging Analysis Ltd.
DiA Imaging Analysis Ltd. is an AI medical imaging analysis software company providing fully automated, implementable tools that enable quick, objective and accurate imaging evaluations, with an initial focus on cardiac ultrasound. DiA's cognitive image processing technology is based on advanced pattern recognition and machine learning algorithms that automatically imitate the way the human eye identifies borders and motion, producing accurate and reliable data for the use of clinicians. The company, based in Israel with U.S. offices in Hartford, Conn., was founded by Hila Goldman Aslan, Michal Yaacobi and Arnon Toussia-Cohen. Learn more at:

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SOURCE DiA Imaging Analysis

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Last Updated: 18-Sep-2018