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Proceedings Paper

Tooth numbering in cone-beam CT using a relation network for automatic filing of dentition charts
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Paper Abstract

Dental record plays an important role in dental diagnosis and personal identification. Automatic image preinterpretation can help reducing dentists’ workload and improving diagnostic efficiency. Systematic dental record filing enables effective utilization of accumulated records at dental clinics for forensic identification. We have been investigating a tooth labeling method on dental cone-beam CT images for the purpose of automatic filing of dental charts. In our previous method, two separate networks were employed for detection and classification of teeth. Although detection accuracy was promising, classification performance had a room of improvement. The purpose of this study was to investigate the use of the relation network to utilize information of positional relationship between teeth for the detection and classification. Using the proposed method, both detection and classification performance improved. Especially, the tooth type classification accuracy improved. The proposed method can be useful in automatic filing of the dental chart.

Paper Details

Date Published: 2 March 2020
PDF: 6 pages
Proc. SPIE 11318, Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications, 113180L (2 March 2020); doi: 10.1117/12.2550933
Show Author Affiliations
Chisako Muramatsu, Shiga Univ. (Japan)
Shota Kutsuna, Gifu Univ. (Japan)
Ryo Takahashi, Media Co. Ltd. (Japan)
Tatsuro Hayashi, Media Co. Ltd. (Japan)
Wataru Nishiyama, Asahi Univ. School of Dentistry (Japan)
Yoshiko Ariji, Aichi-Gakuin Univ. School of Dentistry (Japan)
Xiangrong Zhou, Gifu Univ. (Japan)
Takeshi Hara, Gifu Univ. (Japan)
Akitoshi Katsumata, Asahi Univ. School of Dentistry (Japan)
Eiichiro Ariji, Aichi-Gakuin Univ. School of Dentistry (Japan)
Hiroshi Fujita, Gifu Univ. (Japan)

Published in SPIE Proceedings Vol. 11318:
Medical Imaging 2020: Imaging Informatics for Healthcare, Research, and Applications
Po-Hao Chen; Thomas M. Deserno, Editor(s)

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