Identification of spectral features for selective detection of peripheral nerves by support vector machine-based Raman spectral analysis (Conference Presentation)

Koshirou Hori; Takeo Minamikawa; Yoshiki Terao; Masami Shishibori; Takeshi Yasui

doi:10.1117/12.2648014

16 March 2023 Identification of spectral features for selective detection of peripheral nerves by support vector machine-based Raman spectral analysis (Conference Presentation)

Koshirou Hori, Takeo Minamikawa, Yoshiki Terao, Masami Shishibori, Takeshi Yasui

Author Affiliations +

Proceedings Volume PC12391, Label-free Biomedical Imaging and Sensing (LBIS) 2023; PC123910Q (2023) https://doi.org/10.1117/12.2648014
Event: SPIE BiOS, 2023, San Francisco, California, United States

Abstract

Raman spectroscopy is expected as a non-invasive and effective method for the accurate identification of peripheral nerves. However, the discrimination basis of the Raman spectroscopic method is sometimes ambiguous due to the partial and complicated information of tissue molecules reflected in Raman spectra. In this study, we developed a method for identifying spectral features in Raman spectroscopic detection of peripheral nerves by utilizing a support vector machine (SVM). Raman spectral features for the discrimination of tissue species were extracted by analyzing the feature weight obtained from the linear SVM classifier.

Conference Presentation

Citation Download Citation

Koshirou Hori, Takeo Minamikawa, Yoshiki Terao, Masami Shishibori, and Takeshi Yasui "Identification of spectral features for selective detection of peripheral nerves by support vector machine-based Raman spectral analysis (Conference Presentation)", Proc. SPIE PC12391, Label-free Biomedical Imaging and Sensing (LBIS) 2023, PC123910Q (16 March 2023); https://doi.org/10.1117/12.2648014

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