Imago’s robust patented IP portfolio, trade secrets and time-to-market advantage will disrupt and lead the market.

IMAGO’S Characterization Engine (ICE) Reveal delivers a suite of new visualizations intended to improve both sensitivity and specificity when interpreting an image.

Most imaging companies manufacture new machines to create “better images”, leading to significant capital and operational costs for medical facilities and providers. By comparison, Imago’s Image Characterization Engine (ICE) software, which powers the VI platform, operates regardless of the technology used to acquire the image (mammogram, ultrasound, X-Ray, MRI, CAT Scan, PET Scan, and others) and offers an intelligent decision and knowledge support approach that re-visualizes each image in seconds without the need for new image acquisition hardware. Imago’s ICE utilizes the industry standard DICOM platforms and will therefore integrate with all major brands of standards-based equipment and will complement emerging AI and genomic technologies with additional data and detail.

Left and right CC mammogram views of breast with silicone implants and leakage occurring at arrows.
Imago's ICE Symmetry algorithm characterizes the internal structure of each breast and it's implant, the change in silicone distribution due to the leakage, and the "flow disturbance" patterns created by the leakage.

The patented technology underlying Imago ICE Reveal is a multiple-algorithmic processing approach that mathematically sequences original image data in ways that cause neighborhoods of pixels associated with each type of bodily tissue (or any other “object”) to converge into deterministic patterns that can be differentiated, visualized, characterized, displayed for a clinician’s interpretation, and quantified for machine learning and automated detection. Imago’s ICE Reveal transforms poorly differentiated image content into structured data revealing early-stage cancer and other structural abnormalities as small as 1mm in size.

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Cancer Revealed

See characteristics not observable in the original
Improve diagnosis and patient care

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