Predicting the anthropometric properties of cranial structures using big data

The objective of this study was to generate predictive statistical models of the anthropometric dimensions of craniofacial structures, from medical images obtained by Computed Tomography (CT). The study consisted of two-dimensional measurement of the distances between the anthropometric points Glabe...

Full description

Autores:
Viloria, Amelec
Pinillos-Patiño, Yisel
Pineda, Omar
Romero Marin, Ligia Cielo
Tipo de recurso:
Article of journal
Fecha de publicación:
2020
Institución:
Corporación Universidad de la Costa
Repositorio:
REDICUC - Repositorio CUC
Idioma:
eng
OAI Identifier:
oai:repositorio.cuc.edu.co:11323/7801
Acceso en línea:
https://hdl.handle.net/11323/7801
https://doi.org/10.1016/j.procs.2020.03.112
https://repositorio.cuc.edu.co/
Palabra clave:
ANOVA
Anthropometry
Medical Imaging
Computed Tomography
Rights
openAccess
License
Attribution-NonCommercial-NoDerivatives 4.0 International
Description
Summary:The objective of this study was to generate predictive statistical models of the anthropometric dimensions of craniofacial structures, from medical images obtained by Computed Tomography (CT). The study consisted of two-dimensional measurement of the distances between the anthropometric points Glabella, Vertex, Eurion, Nasion and Opisthocranium to achieve the dimensions: skull length (G-Op), head width (Eu-Eu) and head height (V-N). The iQ-VIEW/ iQ-Lite software was used for measurement. A total of 30 adult skulls between the ages of 50 and 70 were measured, all inhabitants of the cityof Medellin, Colombia. The mean and standard deviation values were calculated. A predictive model was developed using multiple linear regression, which predicts the distance corresponding to head height (V-N) relative to G-Op and Eu-Eu regressors, obtaining a square R value of 0.375. Positive correlations were observed between the three craniofacial dimensions.