Blood classification method based on single-cell laser tweezers Raman spectroscopy and machine learning

Zhehai Zhou; Yiming Liu; Xingfei Xie; Ziqing Wu

doi:10.1117/12.2685225

27 November 2023 Blood classification method based on single-cell laser tweezers Raman spectroscopy and machine learning

Zhehai Zhou, Yiming Liu, Xingfei Xie, Ziqing Wu

Author Affiliations +

Proceedings Volume 12770, Optics in Health Care and Biomedical Optics XIII; 127701I (2023) https://doi.org/10.1117/12.2685225
Event: SPIE/COS Photonics Asia, 2023, Beijing, China

Conference Poster

Abstract

Multi-species blood identification is especially useful in animal quarantine, import and export, criminal cases, forensic examination, and wildlife conservation. Raman spectroscopy is a non-destructive, label-free, and highly specific method for providing chemical information on materials and serving as an analytical tool to characterize biological samples. Machine learning approaches in conjunction with Raman tweezers are proposed to extract the Raman spectral characteristics of single red blood cells (RBCs), then the cells based on the spectral characteristics are classified, and some classification prediction models to achieve single cell identification of different blood species are achieved finally.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhehai Zhou, Yiming Liu, Xingfei Xie, and Ziqing Wu "Blood classification method based on single-cell laser tweezers Raman spectroscopy and machine learning", Proc. SPIE 12770, Optics in Health Care and Biomedical Optics XIII, 127701I (27 November 2023); https://doi.org/10.1117/12.2685225

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