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| Fast and Adaptive Raman Spectroscopy Baseline Correction Algorithm Based on the Principle of the Minus-Weighted Iterative Adjustment Least Square Method (MWIALS) |
| XU Jia-yang1, MENG Si-yu2, ZHANG Zhi-wei2, CHEN Hong-yi2, MA Yu-ting2, WANG Ce2, QI Xiang-dong2, HU Hui-jie2*, SONG Yi-zhi2* |
1. Department of Basic Medicine, School of Medicine, Zhejiang University, Hangzhou 310011, China
2. Suzhou Institute of Biomedical Engineering and Technology, Medical Laboratory Research Laboratory, Chinese Academy of Sciences, Suzhou 215163, China
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Abstract Raman spectroscopy is a non-destructive spectral analysis technique that obtains molecular structure information of substances by analyzing the frequency changes of scattered light. Baseline correction is a key step in enhancing spectral data quality, as it removes background signals and unrelated noise to highlight and purify the target signal. Traditional Raman spectroscopy applications do not require high timeliness for baseline correction. Still, in recent years, applications such as flow Raman and endoscopic Raman, which require real-time processing of spectral data, have increased, placing higher demands on the speed and accuracy of baseline correction. Traditional methods, such as iterative polynomial fitting and wavelet transform, have time, accuracy, or adaptability deficiencies. This study developed a fast adaptive baseline correction algorithm based on the Minus-Weighted Iterative Adjustment Least Square Method (MWIALS). The main principle is to extract the set of negative values and assign them higher weights, continuously adjust the baseline during the iteration process, and set parameter thresholds to exit the loop to achieve fast and accurate baseline correction. We also proposed two parameter selection strategies: Fixed Parameter (FMWIALS), suitable for rapid processing of batch homogeneous spectra, and Adaptive Parameter (AMWIALS), suitable for adaptive processing of heterogeneous spectra. The algorithm was applied to flow Raman spectral analysis of particulate matter, and the results showed that compared to other mainstream algorithms, it was significantly more efficient in practical spectral processing (average time of 47 milliseconds per spectrum) and achieved higher accuracy and adaptability. This algorithm can meet the real-time spectral processing needs in biological sample detection for flow Raman and endoscopic Raman applications, providing strong support for the further application of Raman spectroscopy technology.
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Received: 2024-01-16
Accepted: 2024-07-08
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Corresponding Authors:
HU Hui-jie, SONG Yi-zhi
E-mail: huhj@sibet.ac.cn; songyz@sibet.ac.cn
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[1] Raman C V, Krishnan K S. Nature, 1928, 121(3048): 501.
[2] Bumbrah G S, Sharma R M. Egyptian Journal of Forensic Sciences, 2016, 6(3): 209.
[3] ZHU Zhi-hui, MENG Fan-hao, XIA Jia-bin, et al(朱智慧，孟凡皓，夏嘉斌，等). Acta Academiae Medicinae Sinicae(中国医学科学院学报), 2020, 42(3): 399.
[4] Jin N, Yang K, Li J, et al. Analytical Chemistry, 2023, 95(9): 4291.
[5] Wang J, Meng S, Lin K, et al. Analytica Chimica Acta, 2023, 1239: 340658.
[6] Guo S, Bocklitz T, Popp J. Analyst, 2016, 141(8): 2396.
[7] Kim H H. BioMed Research International, 2015, 2015: 670121.
[8] Gala de Pablo J, Lindley M, Hiramatsu K, et al. Accounts of Chemical Research, 2021, 54(9): 2132.
[9] He S, Zhang W, Liu L, et al. Analytical Methods, 2014, 6(12): 4402.
[10] Hu H, Bai J, Xia G, et al. Photonic Sensors, 2018, 8(4): 332.
[11] Mecozzi M. APCBEE Procedia, 2014, 10: 2.
[12] SI Gan-shang, LIU Jia-xiang, LI Zhen-gang, et al(司赶上, 刘家祥, 李振钢, 等). Acta Optica Sinica(光学学报), 2022, 42(22): 200.
[13] Shao L, Griffiths P R. Environmental Science & Technology, 2007, 41(20): 7054.
[14] Zhang Z M, Chen S, Liang Y Z. The Analyst, 2010, 135(5): 1138.
[15] Dong Z Y, Yu Z H. Chemometrics and Intelligent Laboratory Systems, 2023, 240: 104908.
[16] Xu J, Chen H, Wang C, et al. Biosensors, 2024, 14(4): 171.
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