[20p-C301-1~17] 3.3 Biomedical optics (formerly 3.4)

△ [20p-C301-7] Identification of spectral features for selective detection of peripheral nerves by applying of SVM-based Raman spectral analysis

〇Koshirou Hori¹, Takeo Minamikawa^1,2, Yoshiki Terao¹, Masami Shishibori¹, Takeshi Yasui^1,2 (1.Grad. Sch. Sci. Tech. innov., Tokushima Univ., 2.pLED, Tokushima Univ.)

Keywords:Raman spectroscopy, Machine learning

An Identification 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 identification of tissue species can be extracted by analyzing the feature weight obtained from the linear SVM classifier.