The objective is to distinguish potential breast lesions from normal breast tissue. The QVCAD CAD engine employs several image pattern recognition processes and artificial neural networks to detect suspicious areas in the breast. Figure 1 shows a schematic of the QVCAD system. The native images from the ABUS system together with the output of the QVCAD CAD Engine are concurrently displayed on the Q-Viewer. The QVCAD system receives input images via a standard DICOM format. The Viewer subsystem that formats the ABUS images together with the output of the QView CAD engine for display on the monitor. The CAD subsystem containing the sophisticated image processing algorithms QVCAD is a software system consisting of two major integrated subsystems The result is the QView QVCAD system for 3D Automated Breast Ultrasound. The team developed enhanced functionality of the viewer to improve review times. With the QView team’s experience in artificial intelligence, they developed sophisticated algorithms and underwent rigorous testing with a comprehensive training set to achieve acceptable performance in diagnostic accuracy. QView recognized the value of ABUS but saw the need to improve reading time while preserving diagnostic confidence. This multi-modality approach of mammography and breast ultrasound is becoming the preferred screening protocol for women with breast density. The QVCAD System is indicated for use as an aid to the radiologist during breast screening procedures for women who have negative mammograms but have had a 3D breast ultrasound (ABUS”) because of her dense breast tissue.
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