A Semantic Annotation Approach for Calcifications in Mammogram Using Bayesian Network Model

摘要：

To realize the medical semantic annotation of mammogram, a semantic modeling approach for calcifications in mammogram based on hierarchical Bayesian network was proposed. Firstly, support vector machines was used to map low-level image feature into feature semantics, then high-level semantic was captured through feature semantic fusion using Bayesian network, finally semantic model was established. To validate the method, the model was applied to annotate the semantic information of mammograms. In this experiment, we chose 142 images as training set and 50 images as testing set, the results showed that the precision ratio of malignant samples is 81.48％, and benign samples is 73.91％.

关键词： semantic modeling semantic annotation bayesian network support vector machine diagnose for micro-calcification

作者: Song Li-xin Zhao Ke-xin Zhang Chun-li Wang Li

作者单位: Dept. of Electronics and Information Engineering Harbin University of Science and Technology Harbin, Dept. of gynecology Heilongjiang hospital Harbin,China

会议类型: 国际会议

会议名称: The 6th International Forum on Strategic Technology(IFOST 2011)(第六届国际战略技术论坛)

会议地点: 哈尔滨

会议语种:英文

页码: 864-866

在线出版日期: 2011-08-22（万方平台首次上网日期，不代表论文的发表时间）