Range-independent background subtraction algorithm for recovery of Raman spectra of biological tissue
Range-independent background subtraction algorithm for recovery of Raman spectra of biological tissue
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DOI：
10.1002/jrs.4127
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发表时间：
2012-12-01
影响因子：
2.5
通讯作者：
Gupta, Pradeep K.
中科院分区：
文献类型：
--
作者：
Krishna, Hemant;Majumder, Shovan K.;Gupta, Pradeep K.
将拉曼光谱用于组织诊断应用的一个重要要求是能够从测量的原始拉曼光谱中准确地提取微弱组织拉曼信号的适当算法。虽然基于迭代修正多项式拟合的自动化算法被广泛使用，但这些算法对拟合范围的选择很敏感，从而导致不同起始和停止波数选择的拉曼光谱明显不同。本文提出了一种与距离无关的弱喇曼信号自动恢复算法。给定原始拉曼光谱和起始和停止波数的选择，该算法首先截断光谱以包括该波数范围内的原始数据，通过使用线性最小二乘拟合系数线性外推截断的原始光谱超过两侧的截断点，在两侧外推的线性翼上添加两个适当高度和宽度的高斯峰，然后使用所有这些附加项迭代平滑数据，使得平滑的原始数据和开始原始数据的纵坐标中较小的值作为每一轮迭代平滑的输入，直到添加的高斯峰被完全恢复。使用数学模拟的拉曼光谱和实验测量的各种生物样品的拉曼光谱，将该算法与改进的基于多项式的算法进行了比较，发现该算法可以得到一致的与距离无关的、零基线的无伪迹的拉曼信号。版权所有(C)2012 John Wiley&Sons，Ltd.
An important requirement for the use of Raman spectroscopy for tissue diagnostic applications is an appropriate algorithm that can faithfully retrieve weak tissue Raman signals from the measured raw Raman spectra. Although iterative modified polynomial-fitting-based automated algorithms are widely used, these are sensitive to the choice of the fitting range, thereby leading to significantly different Raman spectra for different start and stop wavenumber selection. We report here an algorithm for automated recovery of the weak Raman signal, which is range independent. Given a raw Raman spectrum and the choice of the start and the stop wavenumbers, the algorithm first truncates the spectrum to include the raw data within this wavenumber range, linearly extrapolates the truncated raw spectrum beyond the points of truncation on the two sides by using coefficients of linear least-square fit, adds two Gaussian peaks of appropriate height and width on the extrapolated linear wings on either side and then iteratively smoothens the data with all these add-ons such that the smaller of the ordinate values of the smoothed and the starting raw data serve as the input to each successive round of iterative smoothing until the added Gaussian peaks are fully recovered. The algorithm was compared with the modified polynomial-based algorithms using mathematically simulated Raman spectrum as well as experimentally measured Raman spectra from various biological samples and was found to yield consistently range-independent and artifact-free Raman signal with zero baseline. Copyright (c) 2012 John Wiley & Sons, Ltd.