title: [Nerve classification with hyperspectral imaging technology].
abstract: In surgical nerve repair surgery, the identification of nerve fascicles is a key to a good repair of their broken end. Some of the existing nerve fascicles identification method are not ideal. Hyperspectral imaging (HSI) technology provides information of images and spectra of biological tissue at the same time. It can supply a qualitative, quantitative and positioning description of the test objectives, and identify different biological tissues by biochemical characteristic difference, and classify and position these tissues in the image. Compared to other medical imaging technology, this techriology has unique advantages. In this study, the hyperspectral imaging technology is used in the identification and classification of the nerve fascicles by the spectral characteristics of different nerve fascicles, and in determining the orientation of the nerve fascicles in the image by the image spectral information in order to better help surgical personnel to carry out the nerve repair surgery. The significance of this paper is: the first to propose a new method of identification and location of the nerve fascicles and assist surgical staff to improve the efficacy of nerve repair; the second to reserve hyperspectral imaging techniques used in qualitative and quantitative and orientation research combined with biological organization, and speed up the molecular hyperspectral imaging technology to the practical stage.
authors.forename: Hong-ying
authors.initials: HY
authors.lastname: Liu
authors.forename: Wen-quan
authors.initials: WQ
authors.lastname: Gu
authors.forename: Qing-li
authors.initials: QL
authors.lastname: Li
authors.forename: Yi-ting
authors.initials: YT
authors.lastname: Wang
authors.forename: Zeng-gan
authors.initials: ZG
authors.lastname: Chen
authors.forename: Qin-tong
authors.initials: QT
authors.lastname: Xu
mesh_terms: D003952:Diagnostic Imaging / Q000379:methods*; D006801:Humans; D057054:Molecular Imaging; D009474:Neurons / Q000145:classification* / Q000166:cytology*; D013057:Spectrum Analysis / Q000379:methods*