Effective Segmentation for Dental X-Ray Images Using Texture-Based Fuzzy Inference System

Authors:
Y. H. Lai;P. L. Lin
Affiliations:
Department of Computer Science and Engineering, National Chung Hsing University, Taichung, Taiwan 40227;Department of Computer Science and Information Engineering, Providence University, Shalu, Taichung, Taiwan 43301
Venue:
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Year:
2008

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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.