The classification of the depth of burn injury using hybrid neural network

摘要

This paper reports on a preliminary study of the classification of burn injuries using a neural network enhanced spectrometer system. Each burn injury is classified as superficial or full-thickness. Spectra covering the visible and near infrared range were collected from burn areas and subjected to autoscaling, principal component analysis, signal preprocessing, and pattern recognition. Classification of 56 data sets collected by the University of Washington Burn Center by this method showed 87.5% classification accuracy.