The automated detection of clusters of microcalcifications
Alistair Y. Cairns, Ian W. Ricketts, D. Folkes, M. Nimmo, PAUL E. PREECE, Alastair Mark Thompson, C. Walker · 1992
The algorithm described demonstrates the feasibility of automated detection of microcalcification clusters using edge detection, graph searching, linear discriminant analysis and cluster detection techniques. It represents a significant improvement over other methods with 100% true-positives, 0% false positives using the re-substitution method and 98% true-positives, 0% false positives using the leave-one-out method. The leave-one-out method resulted in one abnormal region being misclassified. The error occurred not in the detection of potential microcalcifications, but in their classification prior to cluster detection. A number of possible reasons for this misclassification are given.