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01273 am a22001693u 4500 |
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265872 |
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|a dc
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|a Mahmoodi, Sasan
|e author
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|a Sharif, Bayan
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|a Chester, Graeme
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|a Owen, John
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|a Lee, Richard
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|a Skeletal Growth Estimation Using Radiographic Image Processing and Analysis
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|c 2000-12.
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|z Get fulltext
|u https://eprints.soton.ac.uk/265872/1/ieeeBiomedicine.pdf
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|a 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.
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|a Article
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