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Adaptive Optimal Thresholding for the Segmentation of Individual Tooth from CT Images  

Heo, Hoon (Department of Computer Engineering, Graduate School, KyungHee University)
Chae, Ok-Sam (Department of Computer Engineering, Graduate School, KyungHee University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.41, no.3, 2004 , pp. 163-174 More about this Journal
Abstract
The 3D tooth model in which each tooth can be manipulated individualy is essential component for the orthodontic simulation and implant simulation in dental field. For the reconstruction of such a tooth model, we need an image segmentation algorithm capable of separating individual tooth from neighboring teeth and alveolar bone. In this paper we propose a CT image normalization method and adaptive optimal thresholding algorithm for the segmenation of tooth region in CT image slices. The proposed segmentation algorithm is based on the fact that the shape and intensity of tooth change gradually among CT image slices. It generates temporary boundary of a tooth by using the threshold value estimated in the previous imge slice, and compute histograms for the inner region and the outer region seperated by the temporary boundary. The optimal threshold value generating the finnal tooth region is computed based on these two histogram.
Keywords
Segmentation of Individual Tooth; Adaptive Optimal Thresholding; CT Image Normalization;
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Times Cited By KSCI : 1  (Citation Analysis)
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