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Segmentation and Feature Extraction of Panoramic Dental X-Ray Images

Segmentation and Feature Extraction of Panoramic Dental X-Ray Images

Pedro H. M. Lira, Gilson A. Giraldi, Luiz A. P. Neves
ISBN13: 9781522519034|ISBN10: 1522519033|EISBN13: 9781522519041
DOI: 10.4018/978-1-5225-1903-4.ch011
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MLA

Lira, Pedro H. M., et al. "Segmentation and Feature Extraction of Panoramic Dental X-Ray Images." Oral Healthcare and Technologies: Breakthroughs in Research and Practice, edited by Information Resources Management Association, IGI Global, 2017, pp. 470-485. https://doi.org/10.4018/978-1-5225-1903-4.ch011

APA

Lira, P. H., Giraldi, G. A., & Neves, L. A. (2017). Segmentation and Feature Extraction of Panoramic Dental X-Ray Images. In I. Management Association (Ed.), Oral Healthcare and Technologies: Breakthroughs in Research and Practice (pp. 470-485). IGI Global. https://doi.org/10.4018/978-1-5225-1903-4.ch011

Chicago

Lira, Pedro H. M., Gilson A. Giraldi, and Luiz A. P. Neves. "Segmentation and Feature Extraction of Panoramic Dental X-Ray Images." In Oral Healthcare and Technologies: Breakthroughs in Research and Practice, edited by Information Resources Management Association, 470-485. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-1903-4.ch011

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Abstract

Automating the process of analysis of Panoramic X-Ray images is important to help dentist procedures and diagnosis. Tooth segmentation from the radiographic images and feature extraction are essential steps. The authors propose a segmentation approach based on mathematical morphology, quadtree decomposition for mask generation, thresholding, and snake models. The feature extraction stage is steered by a shape model based on Principal Component Analysis (PCA). First, the authors take the quadtree decomposition of a low-pass version of the original image and select the smallest blocks to generate a mask. Then, the original image is processed by Otsu's thresholding. The result is improved by morphological operators and the quadtree mask is applied to address overlapping, a common problem in X-ray images. The obtained regions are searched and the larger ones are selected to find tooth candidates. The boundary of the obtained regions are extracted and aligned with the shape model in order to recognize the target tooth (molar). The selected curve is used in a search method to initialize a snake technique. Finally, morphometric data extraction is performed to obtain tooth measurements for dentist diagnosis. Experiments show the advantages of the proposed method to extract teeth from X-Ray images and discuss its drawbacks.

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