SILICON VALLEY, Calif., June 22, 2020 /PRNewswire/ -- RSIP Vision, a global leader in artificial intelligence (AI) and computer vision technology, announced today a new set of AI-based medical ultrasound modules. These advanced modules will serve as AI-based building blocks for a variety of applications, ranging from automated diagnosis, measurement, and volume estimation, to advanced procedure planning and in-op guided tracking.
When integrated into third-party ultrasound carts, PACS systems, and proprietary cloud platforms, these modules will enable a new set of innovative capabilities in a wide range of domains, such as urology, OBGYN, general imaging, cardiac procedures, and more.
These new building blocks will enable new applications, including:
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Biopsy guidance – The modules allow for real-time, AI-guided needle biopsy procedures, while providing an improved understanding of the lesion or mass. They utilize automated tissue segmentation capabilities, clearly separate the abnormal tissue from the healthy one, and provide the surgeon with all the necessary data required to get to the desired area quickly and precisely.
Automated measurements and function evaluation in Cardiac Ultrasound - These AI modules perform fully automated segmentation of the heart chambers from different ultrasound views, which automates the most important measurements, such as Ejection Fraction, CO, EDA, and EDA. It also evaluates the performance of main heart functions, such as motion of the valves and walls, and detects and classifies abnormalities.
3D Reconstruction - In many cases, the sonographer will be able to demonstrate only a few slices of the organ at focus. The reconstruction function can build the complete organ from sparse information and help the interventional surgeon navigate accurately for biopsy or ablation procedures.
Patient Screening - Integrated into cloud-based settings, these AI capabilities can perform automated analysis of ongoing ultrasound studies, provide triage and second-opinion analysis, detect irregularities and potential errors, prioritize workflow, and boost population healthcare management capabilities.
"Ultrasound is extremely user dependent and can be challenging to interpret. These innovative AI modules help medical teams make quick and accurate clinical decisions and lower the dependence on teams' experience," says Dr. Rabeeh Fares, Radiologist; Department of Diagnostic Radiology, Sourasky Medical Center, Tel Aviv, Israel.