Detection and classification performance levels of mammographic masses under different computer-aided detection cueing environments.

Rationale And Objectives: The authors evaluated the impact of different computer-aided detection (CAD) cueing conditions on radiologists' performance levels in detecting and classifying masses depicted on mammograms.

Materials And Methods: In an observer performance study, eight radiologists interpreted 110 subtle cases six times under different display conditions to detect depicted masses and classify them as benign or malignant. Forty-five cases depicted biopsy-proven masses and 65 were negative.