Skeletal growth estimation using radiographic image processing and analysis

IEEE Trans Inf Technol Biomed. 2000 Dec;4(4):292-7. doi: 10.1109/4233.897061.


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.

MeSH terms

  • Adolescent
  • Age Determination by Skeleton / methods*
  • Bayes Theorem
  • Bone Development
  • Bone and Bones / diagnostic imaging
  • Child
  • Child, Preschool
  • Female
  • Hand / diagnostic imaging
  • Humans
  • Infant
  • Male
  • Radiographic Image Interpretation, Computer-Assisted / methods*