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基于EST和SVM的乳腺癌识别新方法 被引量：2

New method of breast cancer diagnosis based on EST and SVM
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摘要 在分析了目前肿瘤分类检测所采用的方法基础上,提出了一种基于特征空间分离变换(Eigenspace Separation Trans-form)结合支持向量机的乳癌识别新方法。用UCI数据库提供的569例乳腺肿瘤患者,乳腺肿块细胞核显微图像的30个量化特征样本集,进行了分类识别实验,结果表明采用新方法检测乳癌正确识别率达98.3%,优于传统的其他分类识别方法。 This paper introduces the techniques and methods in breast tumor classification,presents a new method of breast cancer diagnosis based on eigenspace separation transform and support vetor machine.Classification experiments are conducted using sample set provided by UCI database with 569 cases of breast tumor cell each with 30 features.The results indicate that the accurate recognition rate of breast cancer is 98.3%.The new method is obviously superior to conventional methods.
作者 顾成扬 吴小俊
机构地区 淮阴师范学院数学科学学院 江南大学信息工程学院
出处 《计算机工程与应用》 CSCD 北大核心 2011年第8期183-185,193,共4页 Computer Engineering and Applications
基金 国家自然科学基金(No.60572034 No.90820002) 教育部新世纪优秀人才计划(No.NCET-06-0487) 江苏省自然科学基金(No.BK2006081) 江南大学创新团队计划项目(No.JNIRT0702) 淮安市科技支撑计划(No.HAS2010042)~~
关键词 主成分分析 特征空间分离变换 支持向量机 肿瘤分类 principal componnet analysis eigenspace separation transform support vector machine tumor classification
分类号 TP391.4 [自动化与计算机技术—计算机应用技术]
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参考文献14

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二级参考文献32

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共引文献2313

同被引文献15

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计算机工程与应用
2011年 第8期

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