Multiple SVM-RFE using Boosting for Mammogram Classification

摘要：

Digital mammography is an effective method to diagnose breast cancer. However, unnecessary biopsies caused by low accuracy in classifying benign abnormalities and malignant ones are challenging problem of the approach. To resolve the issue, computer aided diagnosis (CADx) using various AI techniques have been proposed. Recently, reports indicate that CADx systems can be improved by exploiting mammogram and AI algorithm-specific feature selection schemes. In this regard, we propose a modified feature selection method based on a recently developed multiple support vector machine recursive feature elimination (MSVM-RFE). Experimental results on real world digital mammograms show that our method demonstrated competitive performances.

作者: Sejong Yoon Saejoon Kim

作者单位: Department of Computer Science and Engineering Sogang University 1 Shinsu-dong, Mapo-gu, Seoul, Korea

会议类型: 国际会议

会议名称: The Second International Joint Conference on Computational Science and Optimization(CSO 2009)(2009 国际计算科学与优化会议)

会议地点: 三亚

会议语种:英文

页码: 740-742

在线出版日期: 2009-04-24（万方平台首次上网日期，不代表论文的发表时间）