An annotation approach for masto-calcifications based on semantic model / 生物医学工程学杂志

ABSTRACT

To realize the medical semantic annotation of mammogram, a semantic modeling approach for micro-calcifications in mammogram based on hierarchical Bayesian network (BN) was proposed. Firstly, support vector machines (SVM) were used to map low-level image feature into feature semantics, then high-level semantic was captured through fusing the feature semantics using BN. Finally semantic model was established. To validate the method, the model was applied to annotate the semantic information of mammograms. In this experiment, 142 images were chosen as training set and 50 images as testing set. The results showed that the accuracy of malignant samples was 81.48%, and that of benign samples was 73.91%.