Abstract
In teeth-related radiograph research, the information of teeth shape is the most critical factor for achieving highly automated diagnosis. Therefore, accurate segmentation is an essential but difficult task due to low contrast and uneven exposure of the dental X-ray image. In this paper, we propose a novel scheme to automatically segment teeth by using texture characteristics instead of primitive intensity or edge used in previous researches. At first, image enhancement based on homogeneity measurement is applied to accentuate the texture of gums while smoothing the teeth so that a coarse clustering result can be obtained. Then, fuzzy inference is applied to speculate degrees of pixel belonging to either part. Finally, region growing based on inferences is performed to obtain the complete shape of teeth. The experimental results show that our proposed method indeed outperforms the methods using direct intensity or edge in segmenting complete teeth from X-ray dental images.
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Lai, Y.H., Lin, P.L. (2008). Effective Segmentation for Dental X-Ray Images Using Texture-Based Fuzzy Inference System. In: Blanc-Talon, J., Bourennane, S., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2008. Lecture Notes in Computer Science, vol 5259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88458-3_85
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DOI: https://doi.org/10.1007/978-3-540-88458-3_85
Publisher Name: Springer, Berlin, Heidelberg
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