Dose and fading time estimation of glass ceramic by using artificial neural network method

Abstract

Ceramic materials commonly used for dental prosthetics and restorations shows luminescent properties. Dental ceramics are considered the most natural-looking restorative materials for aesthetic rehabilitation due to their transparency. They are commonly used for dose response and fading assessment by using thermoluminescence method in various fields of dosimetric applications. In present study, we use artificial neural networks (ANN) toolbox of Matlab to predict irradiation dose and fading time using glow curve data from dental glass ceramic which is thermoluminescent (TL) dosimetric material. Temperature, dose value and fading time are used for input and TL intensity used for output component of the proposed ANN model. 18 neurons are used for hidden layer to analyze the experimental results of the model. Experimental and simulation results are compared and similarity is found as about 99 % in this present study.