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基于主成分分析的单细胞后向散射显微光谱自动识别研究

发表时间:2014-08-15  浏览量:1579  下载量:626
全部作者: 王成,文苗,白丽红,翁小阜,魏勋斌
作者单位: 上海理工大学医疗器械与食品学院,生物医学光学与视光学研究所;上海交通大学生物医学工程学院,Med-X研究院
摘 要: 胃上皮细胞和胃癌细胞的后向散射显微光谱,采用主成分分析(principal component analysis, PCA)方法对采集的2种细胞的显微光谱进行统计处理,通过主成分的得分区分不同种类的细胞。分析结果表明:使用PCA方法能100%区分正常胃上皮细胞和胃癌细胞的后向散射显微光谱。说明基于光纤的共焦后向散射显微光谱分析系统有能力区分不同种类的细胞,而且采用PCA方法也可以实现细胞的自动分类。这将为在细胞层面快速、准确、低成本实现胃癌早期诊断提供新的手段。
关 键 词: 光学;显微光谱;单细胞;主成分分析;自动识别
Title: Auto-identification for single cell back-scattering micro-spectrum using principal component analysis
Author: WANG Cheng, WEN Miao, BAI Lihong, WENG Xiaofu2 WEI Xunbin
Organization: Institute of Biomedical Optics & Optometry, School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology; Med-X Research Institute, School of Biomedical Engineering, Shanghai Jiao Tong University
Abstract: In order to accomplish discrimination of the cell, based on confocal back scattering micro-spectroscopy system, a lot of normal stomach epithelial cells and cancerous cells micro spectra were collected. Statistic procedure of the micro-spectra of two kinds of the cells was made using principal component analysis (PCA) and the first two scores of the principal components were utilized to distinguish different kind of cells. The results showed that it can clearly distinguish the confocal back scattering micro-spectra of the normal gastric epithelial cells from cancer cells using PCA. This demonstrated that the confocal back scattering micro-spectroscopy system based on fiber is able to identify the different cell and realize automatically classifying cell using PCA. This will provide a new method for early diagnosis of gastric cancer with fast, accurate and cost-effective at single-cell level.
Key words: optics; micro-spectrum; single cell; principal component analysis; automatic identification
发表期数: 2014年8月第15期
引用格式: 王成,文苗,白丽红,等. 基于主成分分析的单细胞后向散射显微光谱自动识别研究[J]. 中国科技论文在线精品论文,2014,7(15):1541-1545.
 
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