Computer-Aided Interval Change Analysis of Microcalcifications on Mammograms for Breast Cancer Detection

The goal of this project is to develop a computer-aided diagnosis CAD system for automatic interval change analysis of microcalcification clusters on mammograms. Based on our regional registration method and a search program cluster candidates were detected within the local area on the prior. The cluster on the current image is then paired with the candidates to form true TP-TP or false TP-FP pairs and a correspondence classifier is designed to reduce the TP-FP. A temporal classifier TC based on current and prior information is used if a cluster is detected in the prior, and a current classifier CurC based on current information alone is used if no prior cluster is detected. For the TC an LDA, SVM and NN were used. 175 temporal pairs of mammograms were used for evaluation. The registration stage identified 85 149175 of the TP-TP pairs with 15 false matches within the 164 image pairs that had detected clusters. The TC based on LDA, SVM and NN achieved a test Az of 0.83, 0.82, 0.84, respectively, for the 164 pairs for classifying the clusters as malignant or benign. For the 11 clusters without detection on the prior, the test Az by the CurC was 0.72. Eight radiologists participated in an observer study using our CAD. The average Az in estimating the likelihood of malignancy was 0.69 without CAD and improved to 0.75 with CADp0.005.