Deteksi Granuloma Melalui Citra Radiograf Periapikal Dengan Metode GLCM Dan Klasifikasi Learning Vector Quantization

Abstract

Teeth are the hardest parts in the mouth. .One of dental abnormalities that are often found is granuloma. A doctor can detect disease in human’s teeth through the results of x-rays but in its development x-ray are still not able to generate proper diagnosis. On this research will develop an application that can detect granuloma deases with an output on spatial domain with an extraction feature using GLCM which is tabulated by how often different combination of pixel brightness values occur in the image as the method. The classification processed by using LVQ. The classification purpose to classify the image into two conditions, namely: normal and granuloma. The purpose of this research is to facilitate dentist all around Indonesia’s region to detect dental granuloma by radiology tool with affordable price. . The obtained result is a program with a matlab software with Graphical User Interface designed to simplify user application.