The study of sexual dimorphism in human crania has important applications in the fields of human evolution and human osteology. Current, the identification of sex from cranial morphology relies on manual visual inspection of identifiable anatomical features, which can lead to bias due to user's expertise. We developed a landmark-based approach to automatically map the sexual dimorphism signal on the human cranium. We used a sex-known sample of 228 individuals from different geographical locations to identify which cranial regions are most sexually dimorphic taking into account shape, form and size. Our results, which align with standard protocols, show that glabellar and supraciliary regions, the mastoid process and the nasal region are the most sexually dimorphic traits (with an accuracy of 73%). The accuracy increased to 77% if they were considered together. Surprisingly the occipital external protuberance resulted to be not sexually dimorphic but mainly related to variations in size. Our approach here applied could be expanded to map other variable signals on skeletal morphology.
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