Open AccessOsteoporosis detection on the dental panoramic radiographic images using J48 algorithm and learning vector quantization
Author(s) -
Enny Itje Sela
Publication year - 2021
Publication title -
jurnal teknologi dan sistem komputer
Language(s) - English
Resource type - Journals
eISSN - 2620-4002
pISSN - 2338-0403
DOI - 10.14710/jtsiskom.2021.14197
Subject(s) - c4.5 algorithm , learning vector quantization , osteoporosis , artificial intelligence , radiography , medicine , dentistry , computer science , vector quantization , support vector machine , pathology , radiology , naive bayes classifier
Osteoporosis is one type of disease that is not easily detected. This disease can cause fractures for the sufferer. Early detection of osteoporosis is crucial to prevent fractures. This study aims to detect osteoporosis through features extracted from cortical bone and trabeculae in dental panoramic images. The results of the selected feature extraction are trained using an artificial neural network. Based on the study results, the dominant features for osteoporosis detection are radio morphometric index and morphological features. The accuracy, sensitivity, and specificity of the J48 and Learning Vector Quantization (LVQ) are 83.88 %, 78.57 %, and 100 %, respectively.