Exocranial surfaces for sex assessment of the human cranium

Enhancing Sex Estimation Accuracy with Cranial Angle Measurements and Machine Learning

The development of current sexing methods largely depends on the use of adequate sources of data and adjustable classification techniques. Most sex estimation methods have been based on linear measurements, while the angles have been largely ignored, potentially leading to the loss of valuable information for sex discrimination. This study aims to evaluate the usefulness of cranial angles for sex estimation and to differentiate the most dimorphic ones by training machine learning algorithms. Computed tomography images of 154 males and 180 females were used to derive data of 36 cranial angles. The classification models were created by support vector machines, naïve Bayes, logistic regression, and the rule-induction algorithm CN2. A series of cranial angle subsets was arranged by an attribute selection scheme. The algorithms achieved the highest accuracy on subsets of cranial angles, most of which correspond to well-known features for sex discrimination. Angles characterizing the lower forehead and upper midface were included in the best-performing models of all algorithms. The accuracy results showed the considerable classification potential of the cranial angles. The study demonstrates the value of the cranial angles as sex indicators and the possibility to enhance the sex estimation accuracy by using them.

The influence of biological relatedness on sexual dimorphism and sex classification based on external morphology of the frontal bone

The most significant sexual differences in the human skull are located in the upper third of the face (the frontal bone), which is a useful research object, mainly in combination with virtual anthropology methods. However, the influence of biological relatedness on sexual dimorphism and frontal bone variability remains unknown. This study was directed at sexual difference description and sex classification using the form and shape of the external surface of the frontal bones from a genealogically documented Central European osteological sample (nineteenth to twentieth centuries). The study sample consisted of 47 cranial CT images of the adult members of several branches of one family group over 4 generations. Three-dimensional virtual models of the frontal bones were analyzed using geometric morphometrics and multidimensional statistics. Almost the entire external frontal surface was significantly different between males and females, especially in form. Significant differences were also found between this related sample and an unrelated one. Sex estimation of the biologically related individuals was performed using the classification models developed on a sample of unrelated individuals from the recent Czech population (Čechová et al. in Int J Legal Med 133: 1285 1294, 2019), with a result of 74.46% and 63.83% in form and shape, respectively. Failure of this classifier was caused by the existence of typical traits found in the biologically related sample different from the usual manifestation of sexual dimorphism. This can be explained as due to the increased degree of similarity and the reduction of variability in biologically related individuals. The results show the importance of testing previously published methods on genealogical data.

Sex estimation from maxillofacial radiographs using a deep learning approach

The purpose of this study was to construct deep learning models for more efficient and reliable sex estimation. Two deep learning models, VGG16 and DenseNet-121, were used in this retrospective study. In total, 600 lateral cephalograms were analyzed. A saliency map was generated by gradient-weighted class activation mapping for each output. The two deep learning models achieved high values in each performance metric according to accuracy, sensitivity (recall), precision, F1 score, and areas under the receiver operating characteristic curve. Both models showed substantial differences in the positions indicated in saliency maps for male and female images. The positions in saliency maps also differed between VGG16 and DenseNet-121, regardless of sex. This analysis of our proposed system suggested that sex estimation from lateral cephalograms can be achieved with high accuracy using deep learning.

Gender Differences in the Cortical Distribution of Corpus Callosum Fibers

Introduction Research on gender-based disparities in human brain structure has spanned over a century, yielding conflicting results and ongoing debate. While some studies indicate minimal distinctions, others consistently highlight differences in the corpus callosum (CC), even after accounting for average brain size. Methods Diverging from previous approaches, this study examines the morphology of the entire CC fiber rather than solely focusing on its midsagittal structure. Utilizing advanced neuroimaging techniques and generalized Q-imaging tractography, CC streamlines were constructed to assess gender differences in fractional anisotropy (FA), volume ratio, and cortical distribution. Student's t-test was employed to examine the disparities in FA between gender groups, while gender-based distinctions in the normalized volume of the CC and its segments were assessed using analysis of covariance (ANCOVA), with absolute whole white matter volume serving as a covariate. Results No significant gender-based disparities were found in either FA or normalized CC volume. While females exhibited consistently larger normalized volume CC streamlines than males, these differences lost statistical significance after adjusting for absolute total white matter volume as a covariate. Nonetheless, CC streamlines in females displayed a broader spatial distribution, encompassing various cortical regions, including the bilateral prefrontal cortex (medial and lateral surfaces), as well as medial parietal and temporal regions. Conclusion This study elucidates gender-related variations in the morphology of the brain's white matter pathways, indicating a more widespread cortical distribution of CC fibers in females compared to males. However, the study underscores the need for further investigations into connectivity patterns to fully elucidate these gender-based disparities.

How reliable is the application of the sex classifier based on exocranial surface (Musilová et al., 2016) for geographically and temporally distant skull series

Sex estimation is one of the crucial trends in cases of findings of unknown skeletal remains in forensics and bioarchaeology. The changing nature of sexual dimorphism (population specificity, secular trend, other external and internal factors influence) brings challenges to developing new methods; and there are new aims to be independent of these changes such, as the method by Musilová et al. (2016). These methods need to be evaluated on different datasets to determine if they are truly reliable among populations from different places and times, in the case of bioarchaeology. This study assessed the application of the aforementioned method on non-European contemporary and ancient populations to identify the reliability of the method on this separate dataset. The study sample consisted of 96 CT scans of skulls from contemporary Egyptians and 54 3D models of skulls from the Egyptian Old Kingdom Period (2700-2180 BC). The classifier method, previously tested on both Czech and French populations, yielded high accuracies (over 90 %) for sex estimation. For the contemporary Egyptian skull sample, the classifier was able to determine males versus females with an 89.59 % accuracy rate and an AUC value (area under the curve - a measure of the combined specificity and sensitivity of the test) of 0.99; this proves that the classifier is reliable even with a lower degree of accuracy. Conversely, the Old Kingdom Period sample yielded a lower level of accuracy at around 70 % (61.11 %, precisely), although with an AUC value of 0.92, the result is not considered reliable.

A Comparison of Semilandmarking Approaches in the Analysis of Size and Shape

Often, few landmarks can be reliably identified in analyses of form variation and covariation. Thus, ‘semilandmarking’ algorithms have increasingly been applied to surfaces and curves. However, the locations of semilandmarks depend on the investigator’s choice of algorithm and their density. In consequence, to the extent that different semilandmarking approaches and densities result in different locations of semilandmarks, they can be expected to yield different results concerning patterns of variation and co-variation. The extent of such differences due to methodology is, as yet, unclear and often ignored. In this study, the performance of three landmark-driven semilandmarking approaches is assessed, using two different surface mesh datasets (ape crania and human heads) with different degrees of variation and complexity, by comparing the results of morphometric analyses. These approaches produce different semilandmark locations, which, in turn, lead to differences in statistical results, although the non-rigid semilandmarking approaches are consistent. Morphometric analyses using semilandmarks must be interpreted with due caution, recognising that error is inevitable and that results are approximations. Further work is needed to investigate the effects of using different landmark and semilandmark templates and to understand the limitations and advantages of different semilandmarking approaches.

A Comparison of Semilandmarking Approaches in the Visualisation of Shape Differences

In landmark-based analyses of size and shape variation and covariation among biological structures, regions lacking clearly identifiable homologous landmarks are commonly described by semilandmarks. Different algorithms may be used to apply semilandmarks, but little is known about the consequences of analytical results. Here, we assess how different approaches and semilandmarking densities affect the estimates and visualisations of mean and allometrically scaled surfaces. The performance of three landmark-driven semilandmarking approaches is assessed using two different surface mesh datasets with different degrees of variation and complexity: adult human head and ape cranial surfaces. Surfaces fitted to estimates of the mean and allometrically scaled landmark and semilandmark configurations arising from geometric morphometric analyses of these datasets are compared between semilandmarking approaches and different densities, as well as with those from warping to landmarks alone. We find that estimates of surface mesh shape (i.e., after re-semilandmarking and then re-warping) made with varying numbers of semilandmarks are generally consistent, while the warping of surfaces using landmarks alone yields surfaces that can be quite different to those based on semilandmarks, depending on landmark coverage and choice of template surface for warping. The extent to which these differences are important depends on the particular study context and aims.

A Geometric Morphometric Study on Sexual Dimorphism in Viscerocranium

The level of sexual dimorphism manifested by human bones is an important factor for development of effective sex estimation methods. The aim of the study was to investigate the sexual dimorphism in the size and shape of the viscerocranium using geometric morphometric techniques. It also aimed to explore the sex differences in distinct viscerocranial regions and to establish the most dimorphic region with regard to size and shape. Computed tomography images of 156 males and 184 females were used in the study. Three-dimensional coordinates of 31 landmarks were acquired. Five landmark configurations were constructed from the viscerocranium and its orbital, nasal, maxillary, and zygomatic region. Generalized Procrustes superimposition, principal component analysis, and discriminant analysis were applied to each configuration. The significance of the sex differences in size and shape was assessed and significant differences were found in all configurations. The highest accuracy was obtained from both shape and size of the whole viscerocranium. Based on size only, the highest accuracy was achieved by the nasal region. The accuracy based on shape was generally low for all configurations, but the highest result was attained by the orbital region. Hence, size is a better sex discriminator than shape.

Sexual dimorphism in shape and size of the neurocranium

Sex identification is a primary step in forensic analysis of skeletal remains. The accuracy of sex estimation methods greatly depends on the sexual dimorphism manifested by the target anatomical region. The study aims to evaluate the sexual dimorphism in shape and size of the neurocranium and to compare the potential of shape and size of different cranial regions to classify correctly the male and female crania. The study was carried out on computed tomography images of 373 Bulgarian adults (161 males and 212 females). Three-dimensional coordinates of 32 landmarks were acquired. The landmarks were arranged in 4 configurations: neurocranium, frontal bone, parietotemporal region, and occipital bone. For each configuration, the presence of significant sex differences in shape and size was tested. Principal component analysis (PCA) was applied to explore the shape variation. The classification power of size and shape was tested using discriminant analysis and k-means clustering. The neurocranium shows significant sex differences in shape and size. The parietotemporal region is the most dimorphic neurocranial part in size and the frontal bone is the most differing one in shape. The size of the parietotemporal region and frontal bone classifies correctly more than 80% of the crania. The discrimination ability based on shape is rather low as the highest values of about 70% are obtained for the frontal and occipital bone. The PCA plots show large overlapping of the male and female crania. It can be inferred that the sex-specific size differences in the neurocranium are more important than the shape differences.

Correlation of the external occipital protuberance with venous sinuses: a magnetic resonance imaging study

PURPOSE

To date, no study has explored the external occipital protuberance (EOP) using neuroimaging modalities. This study aims to characterize them using magnetic resonance imaging (MRI).

METHODS

A total of 96 patients underwent thin-sliced, post-contrast MRI. The sagittal images were analyzed.

RESULTS

In 97%, the EOPs were delineated as a focal external protrusion of the midline region of the occiput with varying morphologies. In 89% of 93 patients with identifiable EOPs, parts of the intracranial dural sinuses were found to lie just below the inion, the most prominent point of the EOP. The most frequently targeted dural sinus was the confluence of sinuses that was found in 57%, followed by the superior sagittal sinus. In 16%, a bony foramen and transmitting vessel were detected in the EOP, connecting between the diploic channels and the subcutaneous veins. Furthermore, in 33%, bony foramina and transmitting venous structures were identified in the region just below the EOPs, connecting between the diploic channels and the subcutaneous veins.

CONCLUSIONS

The intracranial dural venous sinus is located just below the EOP with a high probability. Most bony foramina in the EOP and midline suboccipital region may transmit veinous structures connecting to the diploic channel.

Estimation of sex from computed tomography images of skull measurements in an adult Turkish population

BACKGROUND

Nowadays, data on the anthropometric measurements of populations is needed in many areas, especially forensic and legal. Using various methods, researchers obtain various data such as race, sex, and age, and thus provide identification of the material used. Morphological or metric methods are often used for identification.

PURPOSE

To evaluate the usefulness of the results of skull measurements using computed tomography (CT) to determine sex in a Turkish population.

MATERIAL AND METHODS

We analyzed 300 male and 300 female CT images of Turkish individuals with an age range of 21-50 years. Maximum cranial length, maximum cranial breadth, bimastoid diameter, bizygomatic diameter, and bigonial breadth were measured by CT tomography. All data were subjected to discriminant function analyses for estimating sex. Intra-observer and inter-observer variances of the measurements were examined using intraclass correlation coefficient analysis.

RESULTS

Discriminant function analysis indicated that there was a significant difference between male and female with 88% accuracy. Discriminant function for estimation of sex was obtained with satisfactory accuracy rates for the parameters used.

CONCLUSION

This study confirms that skull measurements show sexual dimorphism in the Turkish population, and also suggests that it may be useful to use CT to assess skull anthropometric measurements.

Sexual differences in human cranial morphology: Is one sex more variable or one region more dimorphic?

The quantification of cranial sexual dimorphism (CSD) among modern humans is relevant in evolutionary studies of morphological variation and in a forensic context. Despite the abundance of quantitative studies of CSD, few have specifically examined intra-sex variability. Here we quantify CSD in a geographically homogeneous sample of adult crania, which includes Italian individuals from the 19th and 20th centuries. Cranial morphology is described with 92 3D landmarks analyzed using Procrustean geometric morphometrics (PGMM). Size and shape variables are used to compare morphological variance between sexes in the whole cranium and four individual regions. The same variables, plus Procrustes form, are used to quantify average sex differences and explore classification accuracy. Our results indicate that: (a) as predicted by Wainer's rule, males present overall more variance in size and shape, albeit this is statistically significant only for total cranial size; (b) differences between sexes are dominated by size and to a lesser extent by Procrustes form; (c) shape only accounts for a minor proportion of variance; (d) the cranial base shows almost no dimorphism for shape; and (e) facial Procrustes form is the most accurate predictor of skeletal sex. Overall, this study suggests developmental factors underlying differences in CSD among cranial regions; stresses the need for population-specific models that describe craniofacial variation as the basis for models that facilitate the estimation of sex in unidentified skeletal remains; and provides one of the first confirmations of "Wainer's rule" in relation to sexual dimorphism in mammals specific to the human cranium.

Age-related differences in cranial sexual dimorphism in contemporary Europe

Biomechanical load and hormonal levels tended to change just like the soft and skeletal tissue of the elderly with age. Although aging in both sexes shared common traits, it was assumed that there would be a reduction of sexual dimorphism in aged individuals. The main goals of this study were (1) to evaluate age-related differences in cranial sexual dimorphism during senescence, (2) to determine age-related differences in female and male skulls separately, and (3) to compare skull senescence in Czech and French adult samples as discussed by Musilová et al. (Forensic Sci Int 269:70-77, 2016). The cranial surface was analyzed using coherent point drift-dense correspondence analysis. The study sample consisted of 245 CT scans of heads from recent Czech (83 males and 59 females) and French (52 males and 51 females) individuals. Virtual scans in the age range from 18 to 92 years were analyzed using geometric morphometrics. The cranial form was significantly greater in males in all age categories. After size normalization, sexual dimorphism of the frontal, occipital, and zygomatic regions tended to diminish in the elderly. Its development during aging was caused by morphological changes in both female and male skulls but secular changes must also be taken into account. The most notable aging changes were the widening of the neurocranium and the retrusion of the face, including the forehead, especially after the age of 60 in both sexes. Sexual dimorphism was similar between the Czech and French samples but its age-related differences were partially different because of the population specificity. Cranial senescence was found to degrade the accuracy of sex classification (92-94%) in the range of 2-3%.

Machine learning approaches for sex estimation using cranial measurements

The aim of the present study is to apply support vector machines (SVM) and artificial neural network (ANN) as sex classifiers and to generate useful classification models for sex estimation based on cranial measurements. Besides, the performance of the generated sub-symbolic machine learning models is compared with models developed through logistic regression (LR). The study was carried out on computed tomography images of 393 Bulgarian adults (169 males and 224 females). The three-dimensional coordinates of 47 landmarks were acquired and used for calculation of the cranial measurements. A total of 64 measurements (linear distances, angles, triangle areas and heights) and 22 indices were calculated. Two datasets were assembled including the linear measurements only and all measurements and index, respectively. An additional third dataset comprising all possible interlandmark distances between the landmarks was constructed. Two machine learning algorithms-SVM and ANN and a traditional statistical analysis LR-were applied to generate models for sex estimation. In addition, two advanced attribute selection techniques (Weka BestFirst and Weka GeneticSearch) were used. The classification accuracy of the models was evaluated by means of 10 × 10-fold cross-validation procedure. All three methods achieved accuracy results higher than 95%. The best accuracy (96.1 ± 0.5%) was obtained by SVM and it was statistically significantly higher than the best results achieved by ANN and LR. SVM and ANN reached higher accuracy by training on the full datasets than the selection datasets, except for the sample described by the interlandmark distances, where the reduction of attributes by the GeneticSearch algorithm improved the accuracy.

Frontal sinus anatomy of the noble Swéerts-Sporck family and verification of their biological relationships using similarity analysis

The evaluation of frontal sinus similarity is one way to detect biological relationships, especially in small groups, including families of historically known personalities. However, possibilities for studying this issue are currently limited. This contribution deals with the frontal sinuses of a rare osteological sample with known genealogical data, members of the noble Swéerts-Sporck family from the 17th to 20th centuries. The aim is to verify whether the frontal sinuses reflect documented family relationships. Basic dimensions of the frontal sinus such as total surface area and volume, and maximum height and width, and also morphology and anatomical features were evaluated using computed tomography scans. The portions of the frontal sinus above the "external supraorbital line" were analyzed. The degree of similarity between biologically related individuals was determined for each variable and compared with their known biological distance. The degree of similarity based on dimensions was evaluated using both the unadjusted measured data and standardized data adjusted to size. For the unadjusted dimensions, a positive correlation between morphological similarity and biological relatedness was apparent. On the other hand, no positive correlation was apparent for most of the standardized data. Only total volume showed a very weak indication of a positive trend in the standardized data, but this was weaker than in the original values. A positive quantifiable relationship between morphological patterns and biological distance is not clearly indicated. However, nonmetric features do support the documented relationships of the individuals.

A test of the Bulut et al. (2016) landmark-free method of quantifying sex differences in frontal bone roundness in a contemporary Czech sample

The skull, along with the pelvic bone, serves an important source of clues as to the sex of human skeletal remains. The frontal bone is one of the most significant sexually dimorphic structures employed in anthropological research, especially when studied by methods of virtual anthropology. For this reason, many new methods have been developed, but their utility for other populations remains to be verified. In the present study, we tested one such approach-the landmark-free method of Bulut et al. (2016) for quantifying sexually dimorphic differences in the shape of the frontal bone, developed using a sample of the Turkish population. Our study builds upon this methodology and tests its utility for the Czech population. We evaluated the shape of the male and female frontal bone using 3D morphometrics, comparing virtual models of frontal bones and corresponding software-generated spheres. To do so, we calculated the relative size of the frontal bone area deviating from the fitted sphere by less than 1 mm and used these data to estimate the sex of individuals. Using our sample of the Czech population, the method estimated the sex correctly in 72.8% of individuals. This success rate is about 5% lower than that achieved with the Turkish sample. This method is therefore not very suitable for estimating the sex of Czech individuals, especially considering the significantly greater success rates of other approaches.

Biological relationships and frontal sinus similarity in skeletal remains with known genealogical data

Frontal sinus analysis has potential utility for detecting biologically related individuals. However, the methodological approach to its evaluation, as well as its informative value, have been questioned. The aim of this work is to introduce a new approach to evaluating the frontal sinus using the 'external supraorbital line' (ESOL) and to determine whether there are sex differences within families in frontal sinus measurements and whether frontal sinus similarity reflects known genetic relationships in both measurements and morphology. We examined the skeletal remains of 41 adult individuals (25 males, 16 females), all members of one family over four generations (19th to 20th centuries), including individuals with very close consanguinity. CT images of skulls were acquired, and both the dimensions and morphology of the frontal sinuses were analyzed using their portions above the ESOL. No significant sex differences were found within families based on frontal sinus dimensions. Significant relationships were found between biological distance and the maximum height and morphology of the frontal sinuses. The greatest degree of similarity was found among closely related individuals. Additionally, in several cases, there was a greater degree of similarity between first cousins or grandparents and their grandchildren than among siblings or parents and their children. Total surface, volume and width are not significant indicators of relatedness. Known genetic relationships are also supported by individual morphological features. Variability within families with very close consanguineous relationships was lower than within families with common degrees of consanguinity, although differences are significant only for some variables.

Data mining for sex estimation based on cranial measurements

The aim of the present study is to develop effective and understandable classification models for sex estimation and to identify the most dimorphic linear measurements in adult crania by means of data mining techniques. Furthermore, machine learning models and models developed through logistic regression analysis are compared in terms of performance. Computed tomography scans of 393 adult individuals were used in the study. A landmark-based approach was applied to collect the metric data. The three-dimensional coordinates of 47 landmarks were acquired and used for calculation of linear measurements. Two datasets of cranial measurements were assembled, including 37standard measurements and 1081 interlandmark distances, respectively. Three data mining algorithms were applied: the rule induction algorithms JRIP and Ridor, and the decision tree algorithm J48. Two advanced attribute selection methods (Weka BestFirst and Weka GeneticSearch) were also used. The best accuracy result (91.9 %) was achieved by a set of rules learnt by the JRIP algorithm from the dataset constructed by application of the GeneticSearch selection algorithm to the dataset of standard cranial measurements. The set consisted of five rules including seven cranial measurements. Its accuracy was even better than the classification rates achieved by the logistic regression models. Concerning the second dataset of nonstandard measurements, the best accuracy (88.3 %) was obtained by using classification models learnt by two algorithms - JRIP with a dataset preprocessed by the BestFirst selection algorithm and Ridor with preprocessing by the GeneticSearch selection algorithm. Our experiments show that for the two datasets mentioned above the rule-based models contain smaller sets of rules with shorter lists of measurements and achieve better classification accuracy results in comparison with decision tree-based models.

Impact of 3D surface scanning protocols on the Os coxae digital data: Implications for sex and age-at-death assessment

The 3D imaging technologies have become of paramount importance for example in disciplines such as forensic anthropology and bioarchaeology, where they are being used more and more frequently. There are several new possibilities that they offer; for instance, the easier and faster sharing of data among institutions, the possibility of permanent documentation, or new opportunities of data analysis. An important requirement, however, is whether the data obtained from different scanning devices are comparable and whether the possible varying outputs could affect further analyses, such as the estimation of the biological profile. Therefore, we aimed to investigate two important questions: (1) whether 3D models acquired by two different scanning technologies (structured light and laser) are comparable and (2) whether the scanning equipment has an effect on the anthropological analyses, such as age-at-death estimation and sex assessment. 3D models of ossa coxa (n = 29) were acquired by laser (NextEngine) and structured light (HP 3D Structured Light Scanner PRO 2) scanners. The resulting 3D models from both scanners were subjected to age-at-death analyses (via the quantitative method of Stoyanova et al., 2017) and sex analyses (via Diagnose Sexuelle Probabiliste 2 of Brůžek et al., 2017). Furthermore, high quality scans of a small sample (n = 5) of pubic symphyseal surfaces with the RedLux Profiler device were acquired as reference surfaces to which the outputs from both scanners were compared. Small deviations between surfaces were more evident in more rugged surfaces (in areas of depression and protrusion). Even though small differences from the reference surfaces were found, they did not have a significant effect on the age and sex estimates. It never resulted in the opposite sex assignment, and no significant differences were observed between age estimates (with the exception of those with the TPS/BE model).

Sex estimation from skull base radiographs in a contemporary Colombian population

The aim is to study the sexual dimorphism of the base of the skull in radiographs of a bone collection of contemporary Colombian adults, with the intention of formulating discriminant functions capable of classifying sex in this population. The sample consisted of 115 skull base radiographs, (44 females and 71 males), which originated from the Colombian Human Skeletals Collection. Radiographs with good contrast were selected. Images of skulls with asymmetries and fractures were excluded. Five measures: Maximum cranial base length, Foramen magnum length, Maximum cranial breadth, Bizygomatic breadth, Foramen magnum breadth length, were preformed using ImageJ5 software ^®; an intra-observer error was determined using paired t-test. Statistical analysis showed a sexual dimorphism for all variables (p < 0.05). The step-by-step procedure of the discriminant function selected 2 variables from the 5 (Foramen magnum length and Bizygomatic breadth) and the precision was between 86.4% and 88.6% in the determination of sex. However cross-validation showed an accuracy of 85.7% to male and 87.2% to female. The skull base is highly dimorphic. The established discriminant functions can be used to estimate sex in the Colombian population.

Sex Determination of 3D Skull Based on a Novel Unsupervised Learning Method

In law enforcement investigation cases, sex determination from skull morphology is one of the important steps in establishing the identity of an individual from unidentified human skeleton. To our knowledge, existing studies of sex determination of the skull mostly utilize supervised learning methods to analyze and classify data and can have limitations when applied to actual cases with the absence of category labels in the skull samples or a large difference in the number of male and female samples of the skull. This paper proposes a novel approach which is based on an unsupervised classification technique in performing sex determination of the skull of Han Chinese ethnic group. The 78 landmarks on the outer surface of 3D skull models from computed tomography scans are marked, and a skull dataset of a total of 40 interlandmark measurements is constructed. A stable and efficient unsupervised algorithm which we abbreviated as MKDSIF-FCM is proposed to address the classification problem for the skull dataset. The experimental results of the adult skull suggest that the proposed MKDSIF-FCM algorithm warrants fairly high sex determination accuracy for females and males, which is 98.0% and 93.02%, respectively, and is superior to all the classification methods we attempted. As a result of its fairly high accuracy, extremely good stability, and the advantage of unsupervised learning, the proposed method is potentially applicable for forensic investigations and archaeological studies.