Classification of reflected signals from cavitated tooth surfaces using an artificial intelligence technique incorporating a fiber optic displacement sensor

• Main Authors: Rahman, H.A., Harun, Sulaiman Wadi, Arof, Hamzah, Irawati, Ninik, Musirin, I., Ibrahim, Fatimah, Ahmad, Harith
• Format: Article
• Published: International Society for Optical Engineering (SPIE) 2014
• Subjects: QC Physics; TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.um.edu.my/14328/; https://doi.org/10.1117/1.JBO.19.5.057009

An enhanced dental cavity diameter measurement mechanism using an intensity-modulated fiber optic displacement sensor (FODS) scanning and imaging system, fuzzy logic as well as a single-layer perceptron (SLP) neural network, is presented. The SLP network was employed for the classification of the re...