Dental Abnormalities Detection System through Panoramic X-ray using Backpropagation Neural Network and Cross-Validation - Pratiwi, Dian (International Journal of Technology And Business, 2017)
Healthy teeth for everyone is very influential on the structure of its teeth. Abnormalities in the shape of the teeth can only be definitely diagnosed by a dentist through the examination and analysis of x-ray panoramic photos, which will determine how large abnormalities in dental and medical measures that need to be done. How to diagnose is then applied by the researchers in this study, by building a knowledge-based artificial intelligence system that is back propagation neural network. Processes on the system developed consists of a color conversion process on the x-ray image into greyscale, noise removal x-ray, image enhancement, image segmentation teeth, the process of training and testing the neural network. From the amount of image data dental panoramic x-ray is used, namely 20 and 10 training data test data as well as parameter input unit 15, 7 hidden units, 1 unit of output, learning rate 0.01, epoch 1000, the momentum of 0.95. Accuracy obtained through cross-validation test by 80% for data of normal tooth, 86.67% for dental data is not normal, and 100% for a normal tooth and the tooth is not normal on non cross validation test. Therefore we can conclude this study was quite successful in developing a system to diagnose abnormalities of the teeth, because it has a fairly high representation accuracy in providing analysis, as well as the analysis of a dentist.