Automated detection for microcalcifications in digital mammograms using difference image technique

Clustered microcalcifications (MCCs) on mammograms are an important early sign of breast cancer. An intelligent computer-aided diagnosis system can be very helpful for radiologist in detecting and diagnosing MCCs earlier than typical screening programs. In this paper, the detection algorithm is able to extract high-frequency signal and remove low-frequency background by exploiting a difference-image technique in which a signal-suppressed image is subtracted from a signal-enhanced image to remove the structured background in a mammogram. The difference image is thresholded to detect these MCCs in mammograms. The algorithm is tested with a series of clinical mammograms. A true positive rate of more than 75.5% is obtained at a false-positive (FP) detection of 2.18 per image.