# Sex Estimation from Computed Tomography of Os
## 1 Introduction  
Sex estimation of an individual is one of the most important elements in establishing a biological profile and an essential step for identifying skeletal remains [1]. Forensic anthropologists widely use morphologic and metric approaches to determine the sex of human remains. Almost every skeleton component has been utilized in developing sex estimation techniques. However, the pelvis, universally recognized as the most precise predictor of sex, stands out with its distinct sexual dimorphism pattern that is unmatched by any other skeletal element. Moreover, its lack of population-specific characteristics makes it a suitable tool for estimating sex across diverse populations. While other skeletal elements can also be used for sex estimation, the pelvis is generally considered the best source of information for estimating sex [2, 3, 4, 5, 6, 7]. Although it might not be as evident as in the pelvis, sexual dimorphism may also be visible in the cranium [8, 9], sternum [10], oreven long bones [11; 12]. The methods for determining sex can be broadly classified as morphologic or metric. Morphological approaches, which depend on visually evaluating sexually dimorphic characteristics [13], offer valuable and promptly obtained preliminary results. The practicality of these approaches is evident, as they can be readily applied. However, the level of subjectivity strongly influences these qualities [14; 15]. The accuracy of morphological assessment is higher when bones are intact, but decreases when dealing with shattered bones or incomplete skeletons. In contrast, metric studies, while more rigorous, rely on the fundamental concept of variation in male and female measurements and primarily employ various statistical techniques to develop models or equations that can be utilized to determine the sex of individuals [1; 7]. A novel method of estimating sex based on the anthropometric analysis of the pelvis was devised to eliminate all of these drawbacks. [PERSON] et al. [16] developed the Probabilistic Sex Diagnosis (DSP: Diagnose Sexuelle Probabiliste) method. A large reference population group (over 2000 known sex individuals) from various continents has been used to validate the DSP tool in several community-specific samples. Dry bone samples from known ages and sexes have been utilized in numerous studies to validate the DSP method in various demographic groups, including European populations (like Belgian [17] or French [18]) and even Mexican [19]. [PERSON] et al. [20] also analyzed the DSP tool and validated the method in Southeast Brazil using an osteological collection from a modern population. Additionally, the DSP method has been validated with great accuracy and reliability using 3D models of the os coxae obtained from CT scans of a living French population and 3D CT scans of a contemporary Danish population [21; 22]. By comparing real, dry bones against virtual bones (CT scan), [PERSON] et al. [17] reported that all of their collection's coxal bones were correctly identified; the level of indetermination ranged from 2.56% to 46.15%, depending on how many variables were combined. In a recent study on a modern French population using the DSP tool for sex estimation on CT scans of the pelvis, the results showed 97.2% accuracy for women and 92.3% accuracy for men and an indetermination level ranging from 2.8 to 73.1% [21]. Interest in using medical imaging in forensic anthropology has recently increased. According to numerous research studies, measurements derived from biomedical imaging techniques have shown similar accuracy in sex estimation to other classical methods [23; 24; 25; 26; 27]. The studies supported the view that DSP is a reliable method of sex estimation based on CT images of the pelvis. Instead of traditional morphological approaches, CT imaging technologies represent a promising alternative for assessing sex in forensic cases [23; 24]. According to a study by [PERSON] et al. [25], personal forensic identification may be possible using deep learning on pelvic depth images.