[26a-E204-1~9] 3.4 Biomedical optics

△ [26a-E204-1] Identification of spectral features for selective detection of peripheral nerves by application of SVM to Raman spectroscopy

〇(M1)Koshirou Hori¹, Takeo Minamikawa^1,2, Yoshiki Terao³, Masami Shishibori¹, Takeshi Yasui^1,2 (1.Grad. Sch. Sci. Tech. innov., Tokushima Univ., 2.pLED, Tokushima Univ., 3.Grad. Sch. Adv. Tech. Sci, Tokushima Univ.)

Keywords:Raman spectroscopy, Machine learning

Raman spectroscopy is expected as a non-invasive and effective method for the accurate identification of peripheral nerves. However, the 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 identification criteria of SVM.