Deep learning-based ultra-fast identification of Raman spectra with low signal-to-noise ratio
文献类型：期刊论文
| 作者 | K. X. Liu; F. Y. Chen; L. D. Shang; Y. T. Wang; H. Peng; B. Liu and B. Li |
| 刊名 | Journal of Biophotonics
 |
| 出版日期 | 2024 |
| 卷号 | 17期号:1页码:9 |
| ISSN号 | 1864-063X |
| DOI | 10.1002/jbio.202300270 |
| 英文摘要 | 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 |
| URL标识 | 查看原文 |
| 语种 | 英语 |
| 源URL | [http://ir.ciomp.ac.cn/handle/181722/67698]  |
| 专题 | 中国科学院长春光学精密机械与物理研究所 |
| 推荐引用方式 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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