Deep learning-based ultra-fast identification of Raman spectra with low signal-to-noise ratio

doi:10.1002/jbio.202300270

CIOMP OpenIR

	Deep learning-based ultra-fast identification of Raman spectra with low signal-to-noise ratio
	K. X. Liu; F. Y. Chen; L. D. Shang; Y. T. Wang; H. Peng; B. Liu and B. Li
	2024
Source Publication	Journal of Biophotonics
ISSN	1864-063X
Volume	17 Issue:1 Pages:9
Abstract	Ensuring the correct use of cell lines is crucial to obtaining reliable experimental results and avoiding unnecessary waste of resources. Raman spectroscopy has been confirmed to be able to identify cell lines, but the collection time is usually 10-30 s. In this study, we acquired Raman spectra of five cell lines with integration times of 0.1 and 8 s, respectively, and the average accuracy of using long-short memory neural network to identify the spectra of 0.1 s was 95%, and the average accuracy of identifying the spectra of 8 s was 99.8%. At the same time, we performed data enhancement of 0.1 s spectral data by real-valued non-volume preserving method, and the recognition average accuracy of long-short memory neural networks recognition of the enhanced spectral data was improved to 96.2%. With this method, we shorten the acquisition time of Raman spectra to 1/80 of the original one, which greatly improves the efficiency of cell identification. Data enhancement of low signal-to-noise spectral data was performed using a real-valued non-volume preservation method, and the enhanced spectral data were recognised with a long-short memory neural network, which improved the spectral recognition accuracy and shortened the spectral acquisition time.image
DOI	10.1002/jbio.202300270
URL	查看原文
Indexed By	sci
Language	英语
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Document Type	期刊论文
Identifier	http://ir.ciomp.ac.cn/handle/181722/67698
Collection	中国科学院长春光学精密机械与物理研究所
Recommended Citation GB/T 7714	K. X. Liu,F. Y. Chen,L. D. Shang,et al. Deep learning-based ultra-fast identification of Raman spectra with low signal-to-noise ratio[J]. Journal of Biophotonics,2024,17(1):9.
APA	K. X. Liu,F. Y. Chen,L. D. Shang,Y. T. Wang,H. Peng,&B. Liu and B. Li.(2024).Deep learning-based ultra-fast identification of Raman spectra with low signal-to-noise ratio.Journal of Biophotonics,17(1),9.
MLA	K. X. Liu,et al."Deep learning-based ultra-fast identification of Raman spectra with low signal-to-noise ratio".Journal of Biophotonics 17.1(2024):9.

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中国科学院长春光学精密机械与物理研究所