Gender prediction using geometric morphometry with parameters of the cranium obtained from computed tomography images

Abstract

Purpose: The gender difference of the cranium skeleton is of great importance in forensic anthropology and forensic medicine sciences. This study is based on this hypothesis and the gender prediction rate was obtained by processing cranium images obtained from computed tomography (CT) using geometric morphometry. Materials and Methods: CT images of 200 individuals between the ages of 25 and 65 were used in our study. The images were opened at the personal workstation Horos Medical Image Viewer (Version 3.0, USA) program and processed with 3D Curved Multiplanar Reconstruction (MPR). The line passing through the nasion and inion points of the images obtained as a result of the process was determined, and all images were brought to the orthogonal plane. Later, the images were overlapped and saved in JPEG format with 100% magnification. JPEG images saved were converted into TPS format, and 21 homologous landmarks were placed. Generalized Procrustes Analysis (GPA) and Principal Component Analysis (PCA) were applied to the coordinates of landmarks, and shape variations and dimensionality were corrected by gathering the images to the center of gravity. Next, Linear Discriminant Analysis (LDA) was applied to the coordinates, the dimensionality of which was corrected. Results: The study found that 74.465% of the coordinates of 21 homologous landmarks gathered to the center of gravity could be explained with the first three PCs. As a result of the LDA applied to these coordinates, a gender prediction rate of 86.5% was obtained. In addition, a slight difference was found between the GPA sum of squares and the tangent sum of squares (0.57). Conclusion: The images of the cranium obtained from CT showed a high dimorphism by geometric morphometry analysis.