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English Abstract
Journal Article
[Relationship between Body Height and Craniofacial Lines Measured by CT in Southwest Han Males].
Fa Yi Xue za Zhi 2016 April
OBJECTIVE: To establish regression model between craniofacial lines and body height by measuring craniofacial lines in Southwest Han males using CT and to accumulate data for the study of forensic anthropology.
METHODS: Head CT data of 273 Han males in Southwest were collected and 7 craniofacial lines were determined. Multiplanar reconstruction and volume rendering were performed by image post-processing software and the selected lines were measured. The relationship between each measuring indicator and body height was analyzed using SPSS 21.0 software. The regression equation of body height estimation was established and 50 samples were selected again and put into the mathematics models to verify its accuracy.
RESULTS: The linear regression equations of 7 lines were established (P < 0.05). The correlation coefficients of the unary linear regression equations were 0.190-0.439 and the standard errors of the estimate (SEE) were 4.597-5.023 cm. The correlation coefficients of the multiple linear regression equation were 0.494-0.524 and the SEE were 4.418-4.458 cm. The return tests showed that the highest ± 1SEE accuracy of the multiple regression equation: y = 83.959+3.589 x6+2.573 x2, were 30%; and the highest ± 2SEE accuracy of the multiple regression equation: y = 72.646+3.316 x6+1.586 x2+1.553 x4+2.211 x3, were 92%.
CONCLUSION: There is significant linear correlation between 7 selected lines and the stature in this study, and the plural linear regression equation established could be applied for estimating the stature of Southwest Han males.
METHODS: Head CT data of 273 Han males in Southwest were collected and 7 craniofacial lines were determined. Multiplanar reconstruction and volume rendering were performed by image post-processing software and the selected lines were measured. The relationship between each measuring indicator and body height was analyzed using SPSS 21.0 software. The regression equation of body height estimation was established and 50 samples were selected again and put into the mathematics models to verify its accuracy.
RESULTS: The linear regression equations of 7 lines were established (P < 0.05). The correlation coefficients of the unary linear regression equations were 0.190-0.439 and the standard errors of the estimate (SEE) were 4.597-5.023 cm. The correlation coefficients of the multiple linear regression equation were 0.494-0.524 and the SEE were 4.418-4.458 cm. The return tests showed that the highest ± 1SEE accuracy of the multiple regression equation: y = 83.959+3.589 x6+2.573 x2, were 30%; and the highest ± 2SEE accuracy of the multiple regression equation: y = 72.646+3.316 x6+1.586 x2+1.553 x4+2.211 x3, were 92%.
CONCLUSION: There is significant linear correlation between 7 selected lines and the stature in this study, and the plural linear regression equation established could be applied for estimating the stature of Southwest Han males.
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