Publication: Diagnosis and interpretation of dental X-ray in case of deciduous tooth extraction decision in children using active contour model and J48 tree
Issued Date
2014-01-01
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2-s2.0-84911948072
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Mahidol University
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SCOPUS
Bibliographic Citation
2014 International Electrical Engineering Congress, iEECON 2014. (2014)
Suggested Citation
Juthamas Nuansanong, Supaporn Kiattisin, Adisorn Leelasantitham Diagnosis and interpretation of dental X-ray in case of deciduous tooth extraction decision in children using active contour model and J48 tree. 2014 International Electrical Engineering Congress, iEECON 2014. (2014). doi:10.1109/iEECON.2014.6925902 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/33855
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Title
Diagnosis and interpretation of dental X-ray in case of deciduous tooth extraction decision in children using active contour model and J48 tree
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Abstract
© 2014 IEEE. Normally, children suffer from a tooth eruption because their permanent teeth do not push their ways through the gums; therefore, dentist will need to diagnose dental X-ray image based on characteristics of the gap between deciduous teeth and permanent teeth. This paper proposes image processing based on Active Contour Model and data mining for analyzing the ratio of teeth's gap area. In addition, the experiment relates to medical knowledge so as to evaluate the treatment. The results show that the ratio of teeth's gap area in a case of extraction is 20 ± 5 and tooth extraction decision in expert's way is 78 ± 7%. In a case of no extraction, the ratio of teeth's gap area is 40 ± 4.5 and tooth extraction decision in expert's way is 60 ± 6%. Therefore, if the teeth's gap area between the deciduous teeth and the permanent teeth is small, then an occasion of the tooth extraction will be higher. The decision to retain or extract a questionable tooth is one that occurs frequently in dental practice. There are many factors to consider when making this decision. Some cases are very straightforward while others fall into an unclear area of decision-making. This proposed method creates the decision model supported for the dental tooth extraction using J48 tree, and the accuracy is approximately at 98%.