Computerized Discrimination of Malignant and Benign Microcalcification Clusters on Mammograms
Ryohei Nakayama, Yoshikazu Uchiyama, Isamu Hatsukade, Koji Yamamoto, Ryoji Watanabe, Kiyoshi Namba, Kakuya Kitagawa, Kan Takeda · Japanese Journal of Radiological Technology · 2000
This paper introduces a classification of clustered microcalcifications that is based on the weighted-wavelet transform technique in digitized mammograms. The method uses three indicators of malignancy : (1)the standard deviation of the densities of individual microcalcifications within a cluster, (2)the coefficient of veriation of their sizes within a cluster, and(3)the circularity of a cluster. The method was applied to the evaluation of malignancy in 62 microcalcification clusters selected as somewhat difficult cases from Breastpia Namba Hospital's patient files by an experienced mammographer. The results of the discriminant analysis using these indicators showed 85.3% sensitivity and 85.7% specificity.