Abstract: Breast cancer is one of malignant tumours in women，the key to reduce the death rate of patients is early diagnosis and treatment.The Microcalcification Cluster（MCC） is one of the important symptoms of the early stage in breast cancer，so the first step to diagnose successfully is detecting microcalcifications quickly and accurately.At present，many methods which have their own advantages and shortcomings have been proposed for detecting microcalcifications，the typical Laplacion-of-a-Gaussian （LOG） method is one of the effective methods among them，however，it is inefficient though it can accurately detect the locations of microcalcifications.Cascading the morphology and LOG methods can improve the efficiency of detection，but it still can not satisfy the need of the large scale general survey of breast cancer.In this paper，an efficient and real-time detecting algorithm is proposed by cascading 1 dimensional and 2 dimensional LOGs and the results of experiments show that the detection method is efficient and effective.