Auto-classification for confocal back-scattering micro-spectrum at single-cell scale using principal component analysis

被引：13

作者：

Wang, Cheng ^{[1
]}

Wen, Miao ^{[1
]}

Bai, Lihong ^{[1
]}

Zhang, Tong ^{[1
]}

机构：

[1] Univ Shanghai Sci & Technol, Sch Med Instrument & Food Engn, Lab Med Opt & Optometry, Shanghai, Peoples R China

来源：

OPTIK | 2016年 / 127卷 / 03期

关键词：

Spectrum; Single cell; Principal component analysis (PCA); Classification; LIGHT-SCATTERING;

D O I：

10.1016/j.ijleo.2015.10.066

中图分类号：

O43 [光学];

学科分类号：

070207 [光学];

摘要：

Early diagnosis and treatment for cancer is a key to reduce the mortality of cancer. Based on confocal back scatter micro-spectroscopic system, micro-spectra of normal stomach epithelial cells and cancerous cells were collected. In order to discriminate the two types of cells, the micro-spectra of cells were analyzed with principal component analysis in which the first two scores of the principal components were utilized. The results showed this method could clearly distinguish the confocal back scattering micro-spectra of the normal stomach epithelial cells and cancerous cells. This might provide a new method for early diagnosis of stomach cancer, which is fast, accurate and low-cost at single-cell scale. (C) 2015 Elsevier GmbH. All rights reserved.

引用

收藏

页码：1007 / 1010

页数：4

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