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首页> 外文期刊>Biomedical Optics Express >Optimization of advanced Wiener estimation methods for Raman reconstruction from narrow-band measurements in the presence of fluorescence background
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Optimization of advanced Wiener estimation methods for Raman reconstruction from narrow-band measurements in the presence of fluorescence background

机译:在存在荧光背景的情况下,通过窄带测量进行拉曼重建的先进维纳估计方法的优化

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摘要

Raman spectroscopy has shown great potential in biomedical applications. However, intrinsically weak Raman signals cause slow data acquisition especially in Raman imaging. This problem can be overcome by narrow-band Raman imaging followed by spectral reconstruction. Our previous study has shown that Raman spectra free of fluorescence background can be reconstructed from narrow-band Raman measurements using traditional Wiener estimation. However, fluorescence-free Raman spectra are only available from those sophisticated Raman setups capable of fluorescence suppression. The reconstruction of Raman spectra with fluorescence background from narrow-band measurements is much more challenging due to the significant variation in fluorescence background. In this study, two advanced Wiener estimation methods, i.e. modified Wiener estimation and sequential weighted Wiener estimation, were optimized to achieve this goal. Both spontaneous Raman spectra and surface enhanced Raman spectra were evaluated. Compared with traditional Wiener estimation, two advanced methods showed significant improvement in the reconstruction of spontaneous Raman spectra. However, traditional Wiener estimation can work as effectively as the advanced methods for SERS spectra but much faster. The wise selection of these methods would enable accurate Raman reconstruction in a simple Raman setup without the function of fluorescence suppression for fast Raman imaging.
机译:拉曼光谱法已显示出在生物医学应用中的巨大潜力。但是,本质上较弱的拉曼信号会导致数据采集缓慢,尤其是在拉曼成像中。通过窄带拉曼成像然后进行光谱重建可以解决此问题。我们以前的研究表明,使用传统的维纳估计,可以从窄带拉曼测量中重建无荧光背景的拉曼光谱。但是,无荧光拉曼光谱只能从那些能够抑制荧光的复杂拉曼设置中获得。由于荧光背景的显着变化,从窄带测量中用荧光背景重建拉曼光谱更具挑战性。在这项研究中,优化了两种先进的维纳估计方法,即改进的维纳估计和顺序加权维纳估计,以实现这一目标。评估了自发拉曼光谱和表面增强拉曼光谱。与传统的维纳估计相比,两种先进的方法在重建自发拉曼光谱方面显示出显着的改进。但是,传统的维纳估计可以与SERS光谱的高级方法一样有效,但速度要快得多。这些方法的明智选择将能够在简单的拉曼设置中实现准确的拉曼重建,而无需使用荧光抑制功能进行快速拉曼成像。

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