Methods for Computer-Aided Osteoporosis Screening System
Agus Harjoko1, Enny Itje Sela2, Rini Widyaningrum3, Khasnur Hidjah4
1Agus Harjoko*, Department of Computer Science and Electronics, FMIPA, UGM, Yogyakarta, Indonesia.
2Enny Itje Sela, Department of Informatics, University of Technology Yogyakarta, Yogyakarta, Indonesia.
3Rini Widyaningrum, Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Universitas Gadjah Mada, Yogyakarta, Indonesia.
4Khasnur Hidjah, Departement of Computer Science, Faculty of engineering and Design, Universitas Bumigora, Mataram, Indonesia.
Manuscript received on March 29, 2020. | Revised Manuscript received on April 25, 2020. | Manuscript published on April 30, 2020. | PP: 931-937 | Volume-9 Issue-4, April 2020. | Retrieval Number: D7453049420/2020©BEIESP | DOI: 10.35940/ijeat.D7453.049420
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Osteoporosis is a disease that is not only a national issue but has also become a global issue. Although morbidity and mortality rates are relatively low in osteoporosis, fractures because of the disease makes the sufferer feel sick and suffering and affects socio-economic conditions in terms of health care systems and communities. Osteoporosis can be prevented by conducting early detection. Currently, DEXA is used to perform an osteoporosis test that becomes the World Health Organization (WHO) standard. However, the examination with DEXA is still relatively expensive. It technically can’t show the bones’ architecture. So that the examination method using a bone image that has trabeculae like wrist, thigh, jaw, hand, or foot is developed. Some research results on the osteoporosis examination system are presented in this article. The methods include such processes as image acquisition, image enhancement, image analysis (extraction and feature selection), as well as the classification process. Survey results showed that feature extraction, feature selection, and the classification method are selected based on the expected input and output system. Each method has a different level of accuracy
Keywords: Osteoporosis, image, trabeculae, bone mass density.