Segmentação de Imagens de Raio-X Odontológico usando Reconhecimento de Texturas (Dental R-Ray Image Segmentation Using Texture Recognition)

Pedro Henrique Marques Lira (pedrohml@gmail.com)1, Gilson Antonio Giraldi (gilson@lncc.br)1, Luiz Antônio Pereira Neves (neves@ufpr.br)2, Raúl Antonino Feijóo (feij@lncc.br)1


1National Laboratory for Scientific Computing
2Federal University of Paraná

This paper appears in: Revista IEEE América Latina

Publication Date: June 2014
Volume: 12,   Issue: 4 
ISSN: 1548-0992


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.

Index Terms:
Image segmentation, X-Ray images, Texture analysis, Pattern recognition, Bayesian Classifier   


Documents that cite this document
This function is not implemented yet.


[PDF Full-Text (445)]