No abstract

This study is focused on an innovative approach to the numerical assessment of gluteal tuberosity through 3D visualization and its use as sex discriminant. The study was based on an aggregate of 40 right femora, male and female in equal proportion. The surface of tuberositas glutea femoris is captured in a 3D image, using a Hand-held Laser Scanner (FastSCAN). Afterwards, the assessment contains two ways. Firstly, the result is a 3D shape comprising two tetrahedrons with common base. Therefore, the volume of the roughness is approximately equal to the total of the volumes of these two tetrahedrons (volume). Secondly, several points (markers) are placed on the surface of the roughness of the 3D image. After that we create two-dimensional shape which is a function of the three-dimensional one. The area of the formed shape is measured (area) as well as its greatest elevation (elevation). The results were processed with SPSS 17.0 using Discriminant Function Analysis. If the predictors (volume, area and elevation) are included in the model, the percentage of cases classified correctly is 92.5%. This score coincides with world results based on various anthropometric indices of the femur.