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Deteksi osteoporosis pada citra radiograf panoramik dental menggunakan algoritme J48 dan Learning Vector Quantization

Osteoporosis detection on the dental panoramic radiographic images using J48 algorithm and Learning Vector Quantization

Department of Informatics, Universitas Teknologi Yogyakarta. Jl. Siliwangi, Ring Road Utara, Jombor, Sleman, Daerah Istimewa Yogyakarta, Indonesia

Received: 15 Apr 2021; Revised: 20 Jun 2021; Accepted: 11 Jul 2021; Available online: 4 Aug 2021; Published: 30 Oct 2021.
Open Access Copyright (c) 2021 The Authors. Published by Department of Computer Engineering, Universitas Diponegoro
Creative Commons License This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Citation Format:
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.
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Keywords: osteoporosis; radio morphometry index; texture analyis; J48; LVQ
Funding: Universitas Teknologi Yogyakarta

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