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Journal of Biomedicine and Biotechnology
Volume 2009, Article ID 623853, 7 pages
http://dx.doi.org/10.1155/2009/623853
Methodology Report

A Bayesian Approach to Multistage Fitting of the Variation of the Skeletal Age Features

1Department of Computer Science, The George Washington University, 801 22nd Street NW, Washington, DC 20052, USA
2Division of Epidemiology and Biostatistics, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD 20814, USA
3Department of Computer Science, University of Texas-Pan American, 1201 W. University Drive, Edinburg, TX 78539, USA

Received 1 December 2008; Accepted 17 March 2009

Academic Editor: Zhenqiu Liu

Copyright © 2009 Dong Hua et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Accurate assessment of skeletal maturity is important clinically. Skeletal age assessment is usually based on features encoded in ossification centers. Therefore, it is critical to design a mechanism to capture as much as possible characteristics of features. We have observed that given a feature, there exist stages of the skeletal age such that the variation pattern of the feature differs in these stages. Based on this observation, we propose a Bayesian cut fitting to describe features in response to the skeletal age. With our approach, appropriate positions for stage separation are determined automatically by a Bayesian approach, and a model is used to fit the variation of a feature within each stage. Our experimental results show that the proposed method surpasses the traditional fitting using only one line or one curve not only in the efficiency and accuracy of fitting but also in global and local feature characterization.