Skeletal growth estimation using radiographic image processing and analysis

Authors:
S. Mahmoodi;B. S. Sharif;E. G. Chester;J. P. Owen;R. Lee
Affiliations:
Dept. of Electr. & Electron. Eng., Newcastle upon Tyne Univ., UK;-;-;-;-
Venue:
IEEE Transactions on Information Technology in Biomedicine
Year:
2000

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Abstract

An automated knowledge-based vision system for skeletal growth estimation in children is reported in this paper. Images were obtained from hand radiographs of 32 male and 25 female children of age 1-16 yr. Phalanx bones were automatically localized and segmented using hierarchical inferences and active shape models, respectively. A number of shape descriptors were obtained from the segmented bone contour to quantify skeletal growth. From these descriptors, a feature vector was selected for a regression model and a Bayesian estimator. The estimation accuracy was 84% for females and 82% for males. This level of accuracy is comparable to that of expert pediatric radiologists, which suggests that the proposed approach has a potential application in pediatric medicine.