Classification of reflected signals from cavitated tooth surfaces using an artificial intelligence technique incorporating a fiber optic displacement sensor.
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 reflected signals, which were obtained from the surfaces of teeth samples and captured using FODS. Two features were used for the classification of the reflected signals with one of them being the output of a fuzzy logic. The test results showed that the combined fuzzy logic and SLP network methodology contributed to a 100% classification accuracy of the network. The high-classification accuracy significantly demonstrates the suitability of the proposed features and classification using SLP networks for classifying the reflected signals from teeth surfaces, enabling the sensor to accurately measure small diameters of tooth cavity of up to 0.6 mm. The method remains simple enough to allow its easy integration in existing dental restoration support systems.
University of Malaya, Department of Electrical Engineering, Faculty of Engineering, Kuala Lumpur 50603, MalaysiabUniversity of Malaya, Photonics Research Centre, Department of Physics, Faculty of Science, Kuala Lumpur 50603, MalaysiacUniversiti Teknologi.
Husna Abdul
HA
Rahman
University of Malaya, Department of Electrical Engineering, Faculty of Engineering, Kuala Lumpur 50603, MalaysiabUniversity of Malaya, Photonics Research Centre, Department of Physics, Faculty of Science, Kuala Lumpur 50603, Malaysia.
Sulaiman Wadi
SW
Harun
University of Malaya, Department of Electrical Engineering, Faculty of Engineering, Kuala Lumpur 50603, Malaysia.
Hamzah
H
Arof
University of Malaya, Photonics Research Centre, Department of Physics, Faculty of Science, Kuala Lumpur 50603, Malaysia.
Ninik
N
Irawati
Universiti Teknologi MARA (UiTM), Faculty of Electrical Engineering, Shah Alam 40450, Malaysia.
Ismail
I
Musirin
University of Malaya, Medical Informatics and Biological Micro-electro-mechanical Systems Specialized Laboratory, Department of Biomedical Engineering, Faculty of Engineering, Kuala Lumpur 50603, Malaysia.
Fatimah
F
Ibrahim
University of Malaya, Photonics Research Centre, Department of Physics, Faculty of Science, Kuala Lumpur 50603, Malaysia.
Harith
H
Ahmad
D000818:Animals; D003952:Diagnostic Imaging / Q000295:instrumentation / Q000379:methods; D004285:Dogs; D004867:Equipment Design; D005336:Fiber Optic Technology / Q000295:instrumentation / Q000379:methods*; D017143:Fuzzy Logic; D008954:Models, Biological; D012815:Signal Processing, Computer-Assisted; D014070:Tooth / Q000737:chemistry*