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Predicting the anthropometric properties of cranial structures using big data

dc.contributor.authorViloria, Amelecspa
dc.contributor.authorPinillos-Patiño, Yiselspa
dc.contributor.authorPineda, Omarspa
dc.contributor.authorRomero Marin, Ligia Cielospa
dc.date.accessioned2021-01-29T19:04:22Z
dc.date.available2021-01-29T19:04:22Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/11323/7801spa
dc.description.abstractThe 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.spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoeng
dc.publisherCorporación Universidad de la Costaspa
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/spa
dc.sourceProcedia Computer Sciencespa
dc.subjectANOVAspa
dc.subjectAnthropometryspa
dc.subjectMedical Imagingspa
dc.subjectComputed Tomographyspa
dc.titlePredicting the anthropometric properties of cranial structures using big dataspa
dc.typeArtículo de revistaspa
dc.source.urlhttps://www.sciencedirect.com/science/article/pii/S1877050920305500#!spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.identifier.doihttps://doi.org/10.1016/j.procs.2020.03.112spa
dc.identifier.instnameCorporación Universidad de la Costaspa
dc.identifier.reponameREDICUC - Repositorio CUCspa
dc.identifier.repourlhttps://repositorio.cuc.edu.co/spa
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dc.type.contentTextspa
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dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
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