State Key Laboratory for Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Fujian 361005, China.
State Key Laboratory of Marine Environmental Science, Fujian Provincial Key Laboratory for Coastal Ecology and Environmental Studies, Center for Marine Environmental Chemistry & Toxicology, College of the Environment and Ecology, Xiamen University, Xiamen 361102, China.
Anal Chem. 2021 Jun 22;93(24):8408-8413. doi: 10.1021/acs.analchem.0c05391. Epub 2021 Jun 10.
In spectroscopic analysis, push-to-the-limit sensitivity is one of the important topics, particularly when facing the qualitative and quantitative analyses of the trace target. Normally, the effective recognition and extraction of weak signals are the first key steps, for which there has been considerable effort in developing various denoising algorithms for decades. Nevertheless, the lower the signal-to-noise ratio (SNR), the greater the deviation of the peak height and shape during the denoising process. Therefore, we propose a denoising algorithm along with peak extraction and retention (PEER). First, both the first and second derivatives of the Raman spectrum are used to determine Raman peaks with a high SNR whose peak information is kept away from the denoising process. Second, an optimized window smoothing algorithm is applied to the left part of the Raman spectrum, which is combined with the untreated Raman peaks to obtain the denoised Raman spectrum. The PEER algorithm is demonstrated with much better signal extraction and retention and successfully improves the temporal resolution of Raman imaging of a living cell by at least 1 order of magnitude higher than those by traditional algorithms.
在光谱分析中，推至极限的灵敏度是一个重要的课题，特别是在面对痕量目标的定性和定量分析时。通常，有效识别和提取弱信号是首要的关键步骤，为此，数十年来已经开发出了许多不同的去噪算法。然而，信号噪声比（SNR）越低，在去噪过程中峰高和形状的偏差就越大。因此，我们提出了一种去噪算法以及峰提取和保留（PEER）方法。首先，使用拉曼光谱的一阶和二阶导数来确定 SNR 较高的拉曼峰，其峰信息远离去噪过程。其次，对拉曼光谱的左侧部分应用优化的窗口平滑算法，并与未经处理的拉曼峰相结合，以获得去噪的拉曼光谱。PEER 算法在信号提取和保留方面表现出色，成功地将活细胞的拉曼成像的时间分辨率提高了至少一个数量级，优于传统算法。
