A semi-automated method for bone age assessment using cervical vertebral maturation

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dc.contributor.authorBaptista, Roberto Silva [UNIFESP]
dc.contributor.authorQuaglio, Camila L. [UNIFESP]
dc.contributor.authorMourad, Leila M. E. H. [UNIFESP]
dc.contributor.authorHummel, Anderson Diniz [UNIFESP]
dc.contributor.authorCaetano, Cesar Augusto C.
dc.contributor.authorOrtolani, Cristina Lúcia Feijó
dc.contributor.authorPisa, Ivan Torres [UNIFESP]
dc.contributor.institutionUniversidade Federal de São Paulo (UNIFESP)
dc.contributor.institutionFac Informat & Adm Paulista FIAP
dc.contributor.institutionUniv Paulista UNIP
dc.date.accessioned2016-01-24T14:27:24Z
dc.date.available2016-01-24T14:27:24Z
dc.date.issued2012-07-01
dc.description.abstractObjective: 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.Materials and 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 Naive 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.Conclusion: 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. (Angle Orthod. 2012;82:658-662.)en
dc.description.affiliationUniversidade Federal de São Paulo UNIFESP, Postgrad Program Hlth Informat, Dept Hlth Informat, Escola Paulista Med, São Paulo, Brazil
dc.description.affiliationUniversidade Federal de São Paulo UNIFESP, TMD Orofacial Pain Outpatient Clin, Escola Paulista Med, São Paulo, Brazil
dc.description.affiliationFac Informat & Adm Paulista FIAP, Dept Informat Syst, São Paulo, Brazil
dc.description.affiliationUniv Paulista UNIP, Dept Orthodont, Sch Dent, São Paulo, Brazil
dc.description.affiliationUnifespUniversidade Federal de São Paulo UNIFESP, Postgrad Program Hlth Informat, Dept Hlth Informat, Escola Paulista Med, São Paulo, Brazil
dc.description.affiliationUnifespUniversidade Federal de São Paulo UNIFESP, TMD Orofacial Pain Outpatient Clin, Escola Paulista Med, São Paulo, Brazil
dc.description.sourceWeb of Science
dc.format.extent658-662
dc.identifierhttp://dx.doi.org/10.2319/070111-425.1
dc.identifier.citationAngle Orthodontist. Newton N: E H Angle Education Research Foundation, Inc, v. 82, n. 4, p. 658-662, 2012.
dc.identifier.doi10.2319/070111-425.1
dc.identifier.fileWOS000306380300013.pdf
dc.identifier.issn0003-3219
dc.identifier.urihttp://repositorio.unifesp.br/handle/11600/35032
dc.identifier.wosWOS:000306380300013
dc.language.isoeng
dc.publisherE H Angle Education Research Foundation, Inc
dc.relation.ispartofAngle Orthodontist
dc.rightsAcesso aberto
dc.subjectDecision support systemsen
dc.subjectClinicalen
dc.subjectAge determination by skeletonen
dc.subjectCervical vertebraeen
dc.subjectOrthodonticsen
dc.titleA semi-automated method for bone age assessment using cervical vertebral maturationen
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