Cell Segmentation & Abnormality Risk Estimation

The Challenge: Manufacturer of leading FISH imaging platform required robust nuclei segmentation and abnormality risk estimation modules for their integrated software Tightly clumped and overlapping cells Precise interpretation is necessary to overcome ambiguity, avoid false positives, and detect all rare events Our Approach: Customized our state-of-the-art deep learning based segmentation technology for client dataset image …

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Endoscopic Video Analysis

The challenge Innovative startup initiative in the endoscopy space desired to quickly prove out a range of AI benefits for video analysis application Our approach RSIP Vision R&D team in close collaboration with in-house and client medical experts developed a multi-functional proof of concept Quickly & efficiently building key capabilities including pathology detection, image segmentation, …

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Auto-FAC & quality grading for Cardiac Ultrasound

The challenge Innovative manufacturer of point-of-care Ultrasound device desired to integrate unique AI capabilities Users of the device are typically non-experts in US interpretation Automated feedback on image quality and automated measurement of heart function in short-axis view was required, to improve the measurement and drive better patient outcomes Our approach RSIP Vision’s multidisciplinary team …

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Orthopedic Surgery Planning & Navigation

The challenge Precision orthopedic surgery requires strong computer vision capabilities Planning requires accurate 2d and 3d models of arthritic patient bones, as well as automatic bony landmark localization Navigation requires image-based registration between multiple coordinate frames Our approach RSIP Vision offers a fully functional suite of AI modules for orthopedic surgery Modules are highly customizable, …

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3D Reconstruction for Heart Chambers

The challenge Industry leader in electrophysiology space desired to develop innovative solutions for improved mapping of electrical activity and anatomy of heart chambers Goal was to create faster and more informative maps from noisy and sparse data Developing these unique capabilities to gain a competitive edge Our approach RSIP Vision R&D teams developed production quality …

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Chest CT Segmentation

The challenge An industry leading medical device company required the capability to automatically generate an accurate 3d model of complex patient-specific anatomies The anatomical model was needed for planning challenging surgical navigation procedures The pre-existing solution was slow and not robust, requiring extensive and time-consuming manual editing by the interventionist Our approach RSIP Vision leveraged …

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CT Segmentation

Separate any joint including tough edge cases Support noisy images, metal artifact, cone-beam Detect osteophytes Proven on clinical patients data Accuracy at level of scan resolution or better