AUTOMATED DETECTION FOR MICROCALCIFICATIONS IN DIGITAL MAMMOGRAMS USING DIFFERENCE-IMAGE TECHNIQUE

摘要

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 background suppression and threshold classification. The algorithm is tested with a series of clinical mammograms. A True positive rate of more than 75% is obtained at a false-positive (FP) detection of 2.18 per image.