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Volume 26, Issue 4-5, Pages 231-236

Raman spectral statistical classification of nasopharyngeal carcinoma and nasopharyngeal normal cell lines based on support vector classification

Yang Chen,1 Lei Sun,1 Yangwen Huang,2 Lin Ou,3,5 and Ying Su4

1Zhicheng College, Fuzhou University, Fuzhou, China
2Key Laboratory of Instrumentation Science and Dynamic Measurement Ministry of Education, North University of China, Taiyuan, China
3College of Physics and OptoElectronics Technology, Fujian Normal University, Fuzhou, China
4Fujian Provincial Tumor Hospital, Fuzhou, China
5College of Physics and OptoElectronics Technology, Fujian Normal University, Building 7, Room 401, Wansheng Community (East), Shangsan Road, Cangshan District, Fuzhou, China

Copyright © 2011 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Raman spectroscopy (RS) has been used in the discrimination of normal and tumor cells for years. It is very important to validate an existing classification model using different algorithms. In this work, two algorithms of support vector classification (SVC) are utilized to validate our previous work about a LDA classification model of nasopharyngeal carcinoma (NPC) cell lines C666-1, CNE2 and nasopharyngeal normal cell line NP69. All of these two SVC algorithms use the same data set as the previous LDA model and, achieve great sensitivity and specificity. The final results show that our previous LDA classification model could be supported by different SVC algorithms and this demonstrates our classification model is reliable and may be helpful to the realization of RS to be one of diagnostic techniques of NPC.