title: A semi-automated method for bone age assessment using cervical vertebral maturation.
abstract: OBJECTIVE
  To propose a semi-automated method for pattern classification to predict individuals' stage of growth based on morphologic characteristics that are described in the modified cervical vertebral maturation (CVM) method of Baccetti et al.
  
  
  METHODS
  A total of 188 lateral cephalograms were collected, digitized, evaluated manually, and grouped into cervical stages by two expert examiners. Landmarks were located on each image and measured. Three pattern classifiers based on the Naïve Bayes algorithm were built and assessed using a software program. The classifier with the greatest accuracy according to the weighted kappa test was considered best.
  
  
  RESULTS
  The classifier showed a weighted kappa coefficient of 0.861 ± 0.020. If an adjacent estimated pre-stage or poststage value was taken to be acceptable, the classifier would show a weighted kappa coefficient of 0.992 ± 0.019.
  
  
  CONCLUSIONS
  Results from this study show that the proposed semi-automated pattern classification method can help orthodontists identify the stage of CVM. However, additional studies are needed before this semi-automated classification method for CVM assessment can be implemented in clinical practice.
authors: Department of Health Informatics, Escola Paulista de Medicina, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil.
authors: Roberto S
authors: RS
authors: Baptista
authors: Camila L
authors: CL
authors: Quaglio
authors: Laila M E H
authors: LM
authors: Mourad
authors: Anderson D
authors: AD
authors: Hummel
authors: Cesar Augusto C
authors: CA
authors: Caetano
authors: Cristina Lúcia F
authors: CL
authors: Ortolani
authors: Ivan T
authors: IT
authors: Pisa
mesh_terms: D000365:Age Determination by Skeleton / Q000379:methods*; D001499:Bayes Theorem; D002508:Cephalometry / Q000379:methods*; D002574:Cervical Vertebrae / Q000033:anatomy & histology / Q000000981:diagnostic imaging / Q000254:growth & development*; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D008297:Male; D012984:Software