A Hybrid Feature Selection Method Using Both Filter and Wrapper in Mammography CAD

摘要：

Feature selection methods are critical in mammography computer-aided diagnosis and clinical decision support systems. However, searching for an optimal or near optimal feature subset is still a difficult task. After examining the problems with both filter and wrapper methods in feature selection, we propose a hybrid feature selection method using both Filter and Wrapper by taking advantage of both approaches in a content-based image retrieval computer-aided diagnosis. At first, we used step-by-step linear discriminative analysis (SLDA) algorithm, which belongs to filter approach, to remove irrelevant features, and then we used genetic algorithm (GA, wrapper approach) to remove useless features and achieve the ultimate feature subset. To test and evaluate the proposed method, we compared our method with using either GA or SLDA algorithm singly; the result is encouraging.

关键词： computer-aided detection and diagnosis mammography feature subset selection step-by-step linear discriminative analysis genetic algorithm filter wrapper

作者: Yihua Lan Haozheng Ren Yong Zhang Hongbo Yu Xuefeng Zhao

作者单位: School of Computer Engineering, Huaihai Institute of Technology, Lianyungang, China

会议类型: 国际会议

会议名称: 2011 International Conference on Image Analysis and Signal Processing(2011第三届图像分析与信号处理国际会议 IASP 2011)

会议地点: 武汉

会议语种:英文

页码: 378-382

在线出版日期: 2011-10-21（万方平台首次上网日期，不代表论文的发表时间）