拉曼光谱
多项式的
信号(编程语言)
残余物
背景减法
生物系统
减法
计算机科学
样品(材料)
信号处理
谱线
算法
分析化学(期刊)
人工智能
化学
数字信号处理
光学
数学
物理
色谱法
数学分析
生物
算术
像素
计算机硬件
程序设计语言
天文
作者
Brooke D. Beier,Andrew J. Berger
出处
期刊:Analyst
[Royal Society of Chemistry]
日期:2009-01-01
卷期号:134 (6): 1198-1198
被引量:149
摘要
The use of Raman spectroscopy for biomedical applications requires overcoming the obstacle of the broad background that is also generated by biological samples. This background, which is often largely attributed to fluorescence, is frequently orders of magnitude greater than the Raman signal and needs to be removed in order to use Raman spectra in sample analysis. Several methods have been proposed for removing fluorescent signal, both instrumental and computational. Of the computational methods, polynomial fitting has become increasingly popular. Typically, a polynomial of approximately fifth order is used in the fitting. This method alone is not always capable of fitting some more tightly featured spectra that may be present in data, potentially coming from a contaminant in the sample itself or from the experimental design. If this signal is present in varying amounts, the polynomial background removal method can leave the residual spectra with non-uniform artifacts that hinder classification results. If a reference spectrum can be obtained for this interfering signal, however, it can be incorporated into the polynomial fit and removed separately. An automated method for the removal of broad and/or moderately featured background signal is described. In addition to simulations, the method has been applied to spectra from biofilms of Streptococcus mutans.
科研通智能强力驱动
Strongly Powered by AbleSci AI