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An automatic method for skeletal patterns classification using craniomaxillary variables on a Colombian population.

Abstract：

BACKGROUND:The mandibular bone is an important part of the forensic facial reconstruction and it has the possibility of getting lost in skeletonized remains; for this reason, it is necessary to facilitate the identification process simulating the mandibular position only through craniomaxillary measures, for this task, different modeling techniques have been performed, but they only contemplate a straight facial profile that belong to skeletal pattern Class I, but the 24.5% corresponding to the Colombian skeletal patterns Class II and III are not taking into account, besides, craniofacial measures do not follow a parametric trend or a normal distribution. OBJECTIVE:The aim of this study was to employ an automatic non-parametric method as the Support Vector Machines to classify skeletal patterns through craniomaxillary variables, in order to simulate the natural mandibular position on a contemporary Colombian sample. MATERIALS AND METHODS:Lateral cephalograms (229) of Colombian young adults of both sexes were collected. Landmark coordinates protocols were used to create craniomaxillary variables. A Support Vector Machine with a linear kernel classifier model was trained on a subset of the available data and evaluated over the remaining samples. The weights of the model were used to select the 10 best variables for classification accuracy. RESULTS:An accuracy of 74.51% was obtained, defined by Pr-A-N, N-Pr-A, A-N-Pr, A-Te-Pr, A-Pr-Rhi, Rhi-A-Pr, Pr-A-Te, Te-Pr-A, Zm-A-Pr and PNS-A-Pr angles. The Class Precision and the Class Recall showed a correct distinction of the Class II from the Class III and vice versa. CONCLUSIONS:Support Vector Machines created an important model of classification of skeletal patterns using craniomaxillary variables that are not commonly used in the literature and could be applicable to the 24.5% of the contemporary Colombian sample.

journal_name

Forensic Sci Int

journal_title

Forensic science international

authors

Niño-Sandoval TC,Guevara Perez SV,González FA,Jaque RA,Infante-Contreras C

doi

10.1016/j.forsciint.2015.12.025

subject

Has Abstract

pub_date

2016-04-01 00:00:00

pages

159.e1-6

eissn

0379-0738

issn

1872-6283

pii

S0379-0738(15)00526-5

journal_volume

261

pub_type

杂志文章

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