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| 支持向量机算法对鼻咽癌与正常鼻咽细胞株拉曼光谱分析 | |
| 引用本文： | 孙磊,陈阳,黄洋文,欧琳,苏颖,冯尚源,雷晋萍.支持向量机算法对鼻咽癌与正常鼻咽细胞株拉曼光谱分析[J].光谱学与光谱分析,2013,33(6):1566-1569. |
| 作者姓名： | 孙磊 陈阳 黄洋文 欧琳 苏颖 冯尚源 雷晋萍 |
| 作者单位： | 1. 福州大学至诚学院，福建 福州 350002 2. 中北大学仪器科学与动态测试教育部重点实验室，山西 太原 030051 3. 福建师范大学医学光电科学与技术教育部重点实验室，福建 福州 350007 4. 福建省肿瘤医院放射生物研究室，福建 福州 350014 |
| 基金项目： | 国家自然科学基金项目(11104030);福建省自然科学基金项目(2011J01153)资助 |
| 摘 要： | 拉曼光谱技术在肿瘤与正常细胞株的鉴别方面有着广泛的应用。对一个已有的诊断模型进行可靠性验证是非常重要和有意义的工作。采用两种不同的支持向量机分类算法对鼻咽癌和正常鼻咽细胞株的拉曼光谱进行分析和识别，结果显示灵敏度和特异性均在90%以上，并且与已知的相关线性判别分析结果一致。结论表明，两种支持向量机算法都能较好地对细胞株进行鉴别，同时也表明拉曼光谱技术结合相关统计分类算法的方法可以实现对肿瘤细胞的准确鉴别，这一结果将进一步证实拉曼光谱可以作为鼻咽癌诊断的一种方式。 |
| 关 键 词： | 拉曼光谱 鼻咽癌 细胞 支持向量机 线性判别分析 |
| 收稿时间： | 2012-11-09 |
Raman Spectral Analysis of Nasopharyngeal Carcinoma and Nasopharyngeal Normal Cell Lines Based on Support Vector Machines |
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| SUN Lei,CHEN Yang,HUANG Yang-wen,OU Lin,SU Ying,FENG Shang-yuan,LEI Jin-ping.Raman Spectral Analysis of Nasopharyngeal Carcinoma and Nasopharyngeal Normal Cell Lines Based on Support Vector Machines[J].Spectroscopy and Spectral Analysis,2013,33(6):1566-1569. | |
| Authors: | SUN Lei CHEN Yang HUANG Yang-wen OU Lin SU Ying FENG Shang-yuan LEI Jin-ping |
| Institution: | 1. Zhicheng College, Fuzhou University, Fuzhou 350002, China2. Key Laboratory of Instrumentation Science & Dynamic Measurement(North University of China), Ministry of Education, North University of China, Taiyuan 030051, China3. Key Laboratory of Optoelectronic Science and Technology for Medicine, Ministry of Education, Fujian Normal University, Fuzhou 350007, China4. Laboratory of Radiobiology, Fujian Provincial Tumor Hospital, Fuzhou 350014, China |
| Abstract: | In the present work, two algorithms of support vector classification (SVC) were utilized to analyze and classify Raman spectra of nasopharyngeal cell lines C666-1, CNE2 and nasopharyngeal normal cell line NP69, and achieved great sensitivity and specificity which are all up to 90%. This is coincident with our previous LDA classification model. The final results show that both of these two SVC algorithms can well classify the cell lines, and meanwhile may be helpful to the realization of Raman spectroscopy to be one of diagnostic techniques of nasopharyngeal carcinoma. |
| Keywords: | Raman spectroscopy Nasopharyngeal carcinoma Cell Support vector machines Linear discriminant analysis |
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