rhesma intan vidyastari* -  Universitas Muhammadiyah Ponorogo, Indonesia

DOI : 10.24269/mtkind.v15i1.3713

Every human will grow older. The aging process in a person is characterized by osteoporosis. Osteoporosis is a person's bone condition becomes porous and fragile. Marked by a decrease in bone tissue that is easily fragile or broken, a bent back and a shorter body. Alternative detection of osteoporosis can be done by X-ray image of the jaw bone from dental panoramik which analyzed the texture using machine learning and image processing techniques. Harris Corner Detection is a corner detection system that is often used because it is able to produce consistent values in images that experience rotation, scaling, variations in lighting and having lots of noise. Angular detection using the Harris method is based on variations in signal intensity. A large variation in intensity indicates the angle of the image. In the process of osteoporosis detection system using image processing, it is started from preprocessing, processing and final results. The data used in the study were 152 data, with 3 stages of classification, namely : 3-20 years old, 20-40 years old and 40-71 years old group. Based on the expert validation calculation that has been done, the percentage of suitability of the 3-20 years old group is 100%, group 20-40 years old is 98.78%, age group 40-71 years old is 76.47%.
  1. R. Ismi, “Early Detection of Osteoporosis with Neuro-Fuzzy System Through Anatomic Index of Citra Dental Panoramic Radiograph in Mandible Bone Area” July, 2013
  2. P. A. Rahadian, “Early Detection of Osteoporosis Through Region of Interest (ROI) from Citra Dental Panoramic Radiograph in Mandibular Bone Area” July, 2013
  3. S. N. Indrianie, “Mathematical Morphological Edge Detection for Foramen Mentale Segmentation for dental image panoramic radiograph” September, 2013
  4. S. Lestari, E.L. Utari. “Methods for Mandibular Trabecular Pattern Recognition on Digital Periapical Radiographs for Early Detection of Osteoporosis Risk” Teknosains Journal, vol. 3, no.1, December, 2013
  5. R. A. Junior,” Comparison of the Use of Several Edge Detection Methods in Radiological Image Processing of Bone Fractures,” prism of physics, Vol V no.3, 2014
  6. M. Mariastina, “Image Quality Improvement on Dental Panoramic Radiograph in Mandibular Bones Using a Histogram Modification Framework,” October, 2013
  7. Azhari, Suprijanto, “Image Analysis of Panoramic Radiography on Mandibular Bone for Early Detection of Osteoporosis with the Gray Level Cooccurance Matrix (GLCM) Method,” MKB, vol. 46 no.4, December, 2014
  8. F. Ida, “Improved Image Dental Panoramic Radiograph Quality in Mandibular Bones Using Multi Histogram Equalization,” April, 2014
  9. A. Z. Arifin, A. Yuniarti, L. R. Dewi, A. Asano, A. Taguchi, T. Nakamoto, A. Razak and H. Studiawan, "Computer aided diagnosis for osteoporosis based on trabecular bone analysis using panoramic radiographs," Dental Journal, vol. 43, no. 3, pp. 107-112, 2010
  10. Niam, Bahrun, “Analysis of Fracture Bone Detection Based on Harris Angle Detection Method,” April, 2018

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Submitted: 2021-03-31
Published: 2021-10-31
Section: Artikel
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