Mass Detection in Digital Mammograms Using Twin Support Vector Machine-based CAD System

摘要：

Mass in mammogram can be an indicator of breast cancer. In this work we propose a new approach using Twin Support Vector Machine (TWSVM) for automated detection of mass in digital mammograms. This algorithm finds two hyperplanes to classify data points into different classes according to the relevance between a given point and either plane. It works much faster than original SVM classifier. The proposed scheme is evaluated by a data set of 100 clinical mammograms from DDSM. Experimental results demonstrate that the proposed TWSVM-based CAD system offers a very satisfactory performance for mass detection in digitizing mammograms. Compare with previous SVM-based classifier, it provides higher classification accuracy and computational speed.

关键词： SVM Twin SVM Mass Detection Breast Cancer classification

作者: Xiong Si Lu Jing

作者单位: College of Computer Science and Technology Wuhan University of Science and Technology 430065, Wuhan, Dept.of Computer Science and Technology Hubei University of Education 430205, Wuhan, Hubei, China

会议类型: 国际会议

会议名称: 2009 WASE International Conference on Information Engineering(2009年国际信息工程会议)(ICIE 2009)

会议地点: 太原

会议语种:英文

页码: 240-243

在线出版日期: 2009-07-10（万方平台首次上网日期，不代表论文的发表时间）