An Application of Gray Level Co-occurrence Matrix in Computer-assisted Tooth Decay Diagnosis

摘要

Artificial neural network (ANN) has got great success in medical image processing for clinical diagnostic-application because of its ability to arrange complex problems [3-7]. In this paper, an ANN tooth decay diagnostic strategy was proposed and carefully experimented. A back propagation (BP) neural network was formed to analyze the X-ray image of patient's teeth. With four coefficients form gray level co-occurrence matri|9, 10) as its input feature vector, the network is used to make differential diagnoses between decayed and normal teeth after it has been trained for many times. The experimental results indicated that using computer-assisted tooth decay diagnosis is a new method good for dentists.