QVCAD System
Description
QVCAD is designed to process and display a projection image, using the ABUS image stack on a customer supplied computer, and monitor it for review, with certain areas highlighted and/or marked for attention.
Detailed example
The QVCAD CAD engine employs several image pattern recognition processes and artificial neural networks to detect suspicious areas of breast tissue 5mm or more in diameter that have characteristics similar to breast lesions. It inspects every tissue location in the 3-D ABUS images it processes with dedicated algorithms. These algorithms characterize the volumetric region surrounding each location by automatically extracting features that have been determined to represent suspicious signs. These features include typical ultrasound image features described in the radiological literature, such as region boundary, margin, echo pattern, orientation, posterior enhancement, architectural distortions, etc. Using those features, the QVCAD CAD engine generates a score for each suspicious area to distinguish potential breast lesions from normal breast tissue.
AI / analytics pattern
Computer Vision: AI that processes and interprets visual data (e.g., images and videos).
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
Identify potentially suspicious findings in breast scans.
Controls / human review
ATO: Not reported; PIA: Not published