Three-dimensional quantitative characterization of human auricular morphology: A geometric morphometric approach for...

Auricular morphology exhibits marked inter-individual variability and has potential applications in forensic human identification and morphometric research. However, conventional ear measurements mainly rely on two-dimensional images or limited linear parameters, which are insufficient to comprehensively characterize the three-dimensional spatial structure and complex surface variations of the auricle. This study aims to establish a standardized and reproducible three-dimensional quantification framework for auricular morphology, enabling systematic description and analysis of spatial morphological features of the human ear. Based on three-dimensional auricular models, a homologous morphometric framework was constructed using anatomical landmarks, and a two-stage Generalized Procrustes Analysis (GPA) was applied to achieve spatial standardization across individuals. A multi-scale quantitative system was then developed, including global morphological features, regional morphological characteristics, curvature-based features, surface curvature metrics, thickness-related descriptors, and spatial relational features. Principal Component Analysis (PCA) was further used to evaluate patterns of auricular shape variation and assess feature space coverage. The results show that the GPA-based normalization effectively removes inter-individual differences in position, orientation, and scale while preserving key geometric information related to auricular morphological variation. Multi-dimensional feature analysis indicates that auricular shape variation arises not only from differences in overall contour but also from local structural variations across anatomical regions, surface complexity, and spatial organization relationships. The proposed framework converts complex auricular morphology into stable and comparable continuous variables, providing a robust methodological basis for sample variation analysis, individual identification, and forensic applications.