NDLI: Dental R-Ray Image Segmentation Using Texture Recognition

Content Provider	IEEE Xplore Digital Library
Author	Marques Lira, P.H. Giraldi, G.A. Pereira Neves, L.A. Feijoo, R.A.
Copyright Year	2003
Abstract	Panoramic x-ray images are very popular as a first tool for diagnosis in odontological protocols. Automating the process of analysis of such images is important in order to help dentist procedures. In this process, teeth segmentation of the radiographic images is an essential step. In this paper, we propose a segmentation approach based on a supervised learning technique for texture recognition. Firstly, feature extraction is performed by computing moments and statistical features. The obtained data are the input to a Bayesian classifier that, after training, can distinguish two classes of pixels: active (inside the target texture) or inactive (outside the teeth). In the experimental results we show that the methodology is a promising one for teeth segmentation in panoramic x-ray images and discuss its limitations.
Starting Page	694
Ending Page	698
Page Count	5
File Size	673299
File Format	PDF
ISSN	15480992
Volume Number	12
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Dentistry X-ray imaging Bayes methods Chebyshev approximation Manuals Visualization X-Ray images Bayesian Classifier Pattern recognition Texture analysis
Content Type	Text
Resource Type	Article
Subject	Computer Science Electrical and Electronic Engineering

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