Automated Ultrasound Analysis Transforms Patient Care

Advanced automated tools enable quick, accurate, and reproducible ultrasound imaging analysis, accessible anywhere and anytime via Google Cloud.

A collaboration between Google (Mountain View, CA, USA) and DiA Imaging Analysis (DiA; Be’er Sheva, Israel) will provide users with access to advanced cognitive image processing software, pattern recognition technology, and proprietary sophisticated machine learning algorithms that automatically imitate the way the human eye identifies borders and motion, producing accurate and reliable data. The image quantification and analysis tools enhance decision support for both immediate and remote evaluations, starting with automated echocardiography.

Tools currently available include LVIVO EF, a quick and accurate, fully automated analysis of ejection Fraction (EF) by effectively tracking left ventricular (LV) images, including all frames and beats, thus saving up to 30% of EF evaluation time; LVIVO SWM, an automatic solution to analyze true segmental wall motion (SWM), providing wall motion score, segmental score index, and motion information from 17 LV segments; and LVIVO Strain, a fully automated tool that quickly and accurately produces both segmental and global strain analysis (GLS).

“One of DiA's obvious advantages is its ability to operate cross platforms. Our automated tools can be easily implemented into any ultrasound device and any healthcare IT system, including cloud based platforms, all as part of the physician's workflow,” said Hila Goldman Aslan, CEO of DiA. “Once Google Cloud announced its engagement with the medical imaging industry, it was natural that we join forces to offer our quick and accurate auto ultrasound analysis, together with Google's cloud-enabled capabilities, in order to improve patient outcome.”

Google Cloud Platform is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search and YouTube. Alongside a set of management tools, it provides a series of modular cloud services including software as a service (SaaS) computing, data storage, data analytics, and machine learning.

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