Zhao Jianhua, Lui Harvey, McLean David I, Zeng Haishan
The Laboratory for Advanced Medical Photonics (LAMP), Department of Dermatology and Skin Science, University of British Columbia, Vancouver, BC, Canada.
Appl Spectrosc. 2007 Nov;61(11):1225-32. doi: 10.1366/000370207782597003.
A significant advantage of Raman spectroscopy as a noninvasive optical technique is its ability to detect subtle molecular or biochemical signatures within tissue. One of the major challenges for biomedical Raman spectroscopy is the removal of intrinsic autofluorescence background signals, which are usually a few orders of magnitude stronger than those arising from Raman scattering. A number of methods have been proposed for fluorescence background removal including excitation wavelength shifting, Fourier transformation, time gating, and simple or modified polynomial fitting. The single polynomial and the modified multi-polynomial fitting methods are relatively simple and effective, and thus are widely used in biological applications. However, their performance in real-time in vivo applications and low signal-to-noise ratio environments is sub-optimal. An improved automated algorithm for fluorescence removal has been developed based on modified multi-polynomial fitting, but with the addition of (1) a peak-removal procedure during the first iteration, and (2) a statistical method to account for signal noise effects. Experimental results demonstrate that this approach improves the automated rejection of the fluorescence background during real-time Raman spectroscopy and for in vivo measurements characterized by low signal-to-noise ratios.
拉曼光谱作为一种非侵入性光学技术的一个显著优点是它能够检测组织内细微的分子或生化特征。生物医学拉曼光谱的主要挑战之一是去除内在的自发荧光背景信号，这些信号通常比拉曼散射产生的信号强几个数量级。已经提出了许多用于去除荧光背景的方法，包括激发波长偏移、傅里叶变换、时间选通以及简单或改进的多项式拟合。单多项式和改进的多多项式拟合方法相对简单有效，因此在生物应用中被广泛使用。然而，它们在实时体内应用和低信噪比环境中的性能并不理想。基于改进的多多项式拟合开发了一种改进的荧光去除自动算法，但增加了(1)第一次迭代期间的峰值去除程序，以及(2)一种考虑信号噪声影响的统计方法。实验结果表明，这种方法在实时拉曼光谱和低信噪比的体内测量中提高了对荧光背景的自动去除能力。
