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Determining sex by bone volume from 3D images: discriminating analysis of the tali and radii in a contemporary Spanish reference collection
Ruiz Mediavilla, Elena, Perea Pérez, Bernardo, Labajo González, Elena, Sánchez Sánchez, José Antonio, Santiago Sáez, Andrés y Dorado Fernández, Enrique.
Int J Legal Med, vol. 126, núm. 4, 2012, pp. 623-631.
  ARK: https://n2t.net/ark:/13683/pcQr/6DN
Resumen
The discriminant power of bone volume for determining sex has not been possible to determine due to the difficulty in its calculation. At present, new advancements based on 3D technology make it possible to reproduce the bone digitally and calculate its volume using computerized tools, which opens up a new window to ascertaining the discriminant power of this variable. With this objective in mind, the tali and radii of 101 individuals (48 males and 53 females) of a contemporary Spanish reference collection (twentieth century) (EML 1) were scanned using the Picza 3D Laser Scanner. Calculated for the tali were total volume, the volume of the posterior region, which includes the posterior calcaneal facet and other three volumes of the anterior region. Calculated for the radius were total volume, volume of the radius head, volume of the diaphysis, and volume of the distal end. The data are presented for all of the variables, distinguishing between the right and left side. The data were processed using the statistical program PASW Statistics 18, thereby obtaining classification functions for sex which accurately classify 90.9 % of tali and 93.9 % of radii on the basis of their total left and right volume, respectively. Studying the volume in different regions of the bone shows that the diaphysis of the right radius possesses a high level of discriminant power, offering classification functions which accurately classify 96.9 % of the sample. The validation test performed on a sample of 20 individuals from another contemporary Spanish reference collection (EML 2) confirms the high discriminant power of the volume obtaining an accurate classification rate of 80–95 % depending on the variable studied.
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