DETECTION OF OSTEOPOROSIS IN PANORAMIC IMAGE RADIOGRAPH AREA OF MANDIBLE BONE USING HARRIS CORNER DETECTION
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 o...
| Main Authors: | , , |
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| Format: | Article |
| Language: | Indonesian |
| Published: |
Universitas Muhammadiyah Ponorogo
2021-07-01
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| Series: | Multitek Indonesia |
| Subjects: | |
| Online Access: | https://journal.umpo.ac.id/index.php/multitek/article/view/3713 |
| Summary: | 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 panoramic 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 a study conducted by Eduard Royce Siswanto in 2013, regarding the advantages of the Harris corner detection method, it was stated that the Harris corner detection method had an advantage of 77.5% compared to other methods for detecting smiles on the human face. In the research I will be doing, I will use the Harris Corner Detection method as a tool for detecting osteoporosis in panoramic images of the human mandible.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%. |
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| ISSN: | 1907-6223 2579-3497 |