OBJECTIVE: Age-at-death estimation is usually done manually by experts. As such, manual estimation is subjective and greatly depends on the past experience and proficiency of the expert. This becomes even more critical if experts need to evaluate individuals with unknown population affinity or with affinity that they are not familiar with. The purpose of this study is to design a novel age-at-death estimation method allowing for automatic evaluation on computers, thus eliminating the human factor. METHODS: We used a traditional machine-learning approach with explicit feature extraction. First, we identified and described the features that are relevant for age-at-death estimation. Then, we created a multi-linear regression model combining these features. Finally, we analysed the model performance in terms of Mean Absolute Error (MAE), Mean Bias Error (MBE), Slope of Residuals (SoR) and Root Mean Squared Error (RMSE). RESULTS: The main result of this study is a population-independent method of estimating an individual's age-at-death using the acetabulum of the pelvis. Apart from data acquisition, the whole procedure of pre-processing, feature extraction and age estimation is fully automated and implemented as a computer program. This program is a part of a freely available web-based software tool called CoxAGE3D, which is available at https://coxage3d.fit.cvut.cz/. Based on our dataset, the MAE of the presented method is about 10.7 years. In addition, five population-specific models for Thai, Lithuanian, Portuguese, Greek and Swiss populations are also given. The MAEs for these populations are 9.6, 9.8, 10.8, 10.5 and 9.2 years, respectively. Our age-at-death estimation method is suitable for individuals with unknown population affinity and provides acceptable accuracy. The age estimation error cannot be completely eliminated, because it is a consequence of the variability of the ageing process of different individuals not only across different populations but also within a certain population.

• MeSH
• Acetabulum * diagnostic imaging   MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Linear Models MeSH
• Young Adult MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Software * MeSH
• Forensic Anthropology * methods   MeSH
• Machine Learning * MeSH
• Age Determination by Skeleton * methods   MeSH
• Imaging, Three-Dimensional * MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

Thanks to technical progress and the availability of virtual data, sex estimation methods as part of a biological profile are undergoing an inevitable evolution. Further reductions in subjectivity, but potentially also in measurement errors, can be brought by approaches that automate the extraction of variables. Such automatization also significantly accelerates and facilitates the specialist's work. The aim of this study is (1) to apply a previously proposed algorithm (Kuchař et al. 2021) to automatically extract 10 variables used for the DSP2 sex estimation method, and (2) to test the robustness of the new automatic approach in a current heterogeneous population. For the first aim, we used a sample of 240 3D scans of pelvic bones from the same individuals, which were measured manually for the DSP database. For the second aim a sample of 108 pelvic bones from the New Mexico Decedent Image Database was used. The results showed high agreement between automatic and manual measurements with rTEM below 5% for all dimensions except two. The accuracy of final sex estimates based on all 10 variables was excellent (error rate 0.3%). However, we observed a higher number of undetermined individuals in the Portuguese sample (25% of males) and the New Mexican sample (36.5% of females). In conclusion, the procedure for automatic dimension extraction was successfully applied both to a different type of data and to a heterogeneous population.

• MeSH
• Algorithms * MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Pelvic Bones * diagnostic imaging   MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Forensic Anthropology * methods   MeSH
• Sex Determination by Skeleton * methods   MeSH
• Imaging, Three-Dimensional * MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Portugal MeSH

In today's biometric and commercial settings, state-of-the-art image processing relies solely on artificial intelligence and machine learning which provides a high level of accuracy. However, these principles are deeply rooted in abstract, complex "black-box systems". When applied to forensic image identification, concerns about transparency and accountability emerge. This study explores the impact of two challenging factors in automated facial identification: facial expressions and head poses. The sample comprised 3D faces with nine prototype expressions, collected from 41 participants (13 males, 28 females) of European descent aged 19.96 to 50.89 years. Pre-processing involved converting 3D models to 2D color images (256 × 256 px). Probes included a set of 9 images per individual with head poses varying by 5° in both left-to-right (yaw) and up-and-down (pitch) directions for neutral expressions. A second set of 3,610 images per individual covered viewpoints in 5° increments from -45° to 45° for head movements and different facial expressions, forming the targets. Pair-wise comparisons using ArcFace, a state-of-the-art face identification algorithm yielded 54,615,690 dissimilarity scores. Results indicate that minor head deviations in probes have minimal impact. However, the performance diminished as targets deviated from the frontal position. Right-to-left movements were less influential than up and down, with downward pitch showing less impact than upward movements. The lowest accuracy was for upward pitch at 45°. Dissimilarity scores were consistently higher for males than for females across all studied factors. The performance particularly diverged in upward movements, starting at 15°. Among tested facial expressions, happiness and contempt performed best, while disgust exhibited the lowest AUC values.

• MeSH
• Algorithms * MeSH
• Automated Facial Recognition * methods   MeSH
• Biometric Identification methods   MeSH
• Adult MeSH
• Head Movements physiology   MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Face anatomy & histology   MeSH
• Image Processing, Computer-Assisted methods   MeSH
• Posture physiology   MeSH
• Facial Expression * MeSH
• Imaging, Three-Dimensional MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

An increasing number of software tools can be used in forensic anthropology to estimate a biological profile, but further studies in other populations are required for more robust validation. The present study aimed to evaluate the validity of MorphoPASSE software for sex estimation from sexually dimorphic cranial traits recorded on 3D CT models (n = 180) from three populations samples (Czech, French, and Egyptian). Two independent observers performed scoring of 4 cranial traits (2 of them bilateral) in each population sample of 30 males and 30 females. The accuracy of sex estimation using traditional posterior probability threshold (pp = 0.5) ranged from 85.6% to 88.3% and overall classification error from 14.4% to 11.7% for both observers, and corresponds to the previously published values of the method. The MorphoPASSE method is also affected by the subjectivity of the observers, as both observers show agreement in sex assignment in 83.9% of cases, regardless of the accuracy of the estimates. Applying a higher posterior probability threshold (pp 0.95) provided classification accuracy of 97.9% and 93.3% of individuals (for observer A and B respectively), minimizing the risk of error to 2.1% and 6.7%, respectively. However, sex estimation can only be applied to 54% and 66% of individuals, respectively. Our results demonstrate the validity of the MorphoPASSE software for cranial sex estimation outside the reference population. However, the achieved classification success is accompanied by a high risk of errors, the reduction of which is only possible by increasing the posterior probability threshold.

• MeSH
• Adult MeSH
• Skull * anatomy & histology   diagnostic imaging   MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Tomography, X-Ray Computed MeSH
• Probability MeSH
• Reproducibility of Results MeSH
• Software * MeSH
• Forensic Anthropology * methods   MeSH
• Sex Determination by Skeleton * methods   MeSH
• Imaging, Three-Dimensional MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Validation Study MeSH
• Geographicals
• Egypt MeSH
• France MeSH

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.

• MeSH
• Frontal Bone * diagnostic imaging   anatomy & histology   MeSH
• Adult MeSH
• Humans MeSH
• Tomography, X-Ray Computed MeSH
• Sex Characteristics MeSH
• Forensic Anthropology * methods   MeSH
• Sex Determination by Skeleton * methods   MeSH
• Imaging, Three-Dimensional * MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

Age-at-death estimation of adult skeletal remains is a key part of biological profile estimation, yet it remains problematic for several reasons. One of them may be the subjective nature of the evaluation of age-related changes, or the fact that the human eye is unable to detect all the relevant surface changes. We have several aims: (1) to validate already existing computer models for age estimation; (2) to propose our own expert system based on computational approaches to eliminate the factor of subjectivity and to use the full potential of surface changes on an articulation area; and (3) to determine what age range the pubic symphysis is useful for age estimation. A sample of 483 3D representations of the pubic symphyseal surfaces from the ossa coxae of adult individuals coming from four European (two from Portugal, one from Switzerland and Greece) and one Asian (Thailand) identified skeletal collections was used. A validation of published algorithms showed very high error in our dataset-the Mean Absolute Error (MAE) ranged from 16.2 and 25.1 years. Two completely new approaches were proposed in this paper: SASS (Simple Automated Symphyseal Surface-based) and AANNESS (Advanced Automated Neural Network-grounded Extended Symphyseal Surface-based), whose MAE values are 11.7 and 10.6 years, respectively. Lastly, it was demonstrated that our models could estimate the age-at-death using the pubic symphysis over the entire adult age range. The proposed models offer objective age estimates with low estimation error (compared to traditional visual methods) and are able to estimate age using the pubic symphysis across the entire adult age range.

• MeSH
• Data Mining MeSH
• Adult MeSH
• Humans MeSH
• Forensic Anthropology methods   MeSH
• Pubic Symphysis * MeSH
• Age Determination by Skeleton methods   MeSH
• Imaging, Three-Dimensional MeSH
• Check Tag
• Adult MeSH
• Humans MeSH
• Publication type
• Journal Article MeSH

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.

• MeSH
• Frontal Bone anatomy & histology   diagnostic imaging   MeSH
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Tomography, X-Ray Computed MeSH
• Computer Simulation * MeSH
• Image Processing, Computer-Assisted MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Forensic Anthropology MeSH
• Support Vector Machine MeSH
• Sex Determination by Skeleton methods   MeSH
• Imaging, Three-Dimensional * MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Czech Republic MeSH

Forensic dental identification has employed traditionally 2D digital radiological imaging techniques. More recently, 3D cone beam computer tomography (CBCT) data, widely applied in clinical dentistry, have been gradually used. The purpose of this study was to compare the precision and quality of 2D digital orthopantomogram (OPG) and 2D OPG images generated from cone beam computed tomography (CBCT). The study sample consisted of 50 patients with archived conventional 2D OPG and 3D CBCT images. Patients signed an informed consent form to take part in our study. Measurements of the mandible, teeth and dental restorations were taken by two observers on calibrated 2D OPG and 3D CBCT-to-OPG images using measurement functionalities of DOPLHIN software. Acquired dimensions were compared side by side and images of fillings were superimposed. For better visual comparison and more efficient image registration, the methods of spline interpolation were used. The pairs of absolute measurements obtained from conventional OPG and CBCT-to-OPG-converted images were highly correlated (p < 0.05). However, larger, and horizontally measured distances were revealed to be more affected than shorter vertically taken measurements. In relative terms, CBCT-generated width/length indices of the canines and the first molars ranged from 84% to 99.8% of those acquired from traditional OPGs. In addition, corresponding points on the teeth and fillings were compared side by side and in superimposition. The average coincidence of images was 6.1%. The results revealed that for selected metric variables 2D OPGs and 3D CBCT-generated OPGs were complementary and could be used for forensic comparisons.

• MeSH
• Radiography, Dental, Digital methods   MeSH
• Humans MeSH
• Mandible MeSH
• Cone-Beam Computed Tomography methods   MeSH
• Radiography, Panoramic methods   MeSH
• Sensitivity and Specificity MeSH
• Forensic Dentistry * methods   MeSH
• Dental Restoration, Permanent MeSH
• Tooth MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Comparative Study MeSH

Diffeomorphic shape registration allows for the seamless geometric alignment of shapes. In this study, we demonstrated the use of a registration algorithm to automatically seed anthropological landmarks on the CT images of the pelvis. We found a high correlation between manually and automatically seeded landmarks. The registration algorithm makes it possible to achieve a high degree of automation with the potential to reduce operator errors in the seeding of anthropological landmarks. The results of this study represent a promising step forward in effectively defining the anthropological measures of the human skeleton.

• MeSH
• Algorithms * MeSH
• Anatomic Landmarks * MeSH
• Middle Aged MeSH
• Humans MeSH
• Pelvic Bones anatomy & histology   diagnostic imaging   MeSH
• Tomography, X-Ray Computed * MeSH
• Image Processing, Computer-Assisted * MeSH
• Aged MeSH
• Forensic Anthropology methods   MeSH
• Sex Determination by Skeleton methods   MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH

This paper introduces an automated method for estimating sex from cranial sex diagnostic traits by extracting and evaluating specialized morphometric features from the glabella, the supraorbital ridge, the occipital protuberance, and the mastoid process. The proposed method was developed and evaluated using two European population samples, a Czech sample comprising 170 crania reconstructed from anonymized CT scans and a Greek sample of 156 crania from the Athens Collection. It is based on a fully automatic algorithm applied on 3D models for extracting sex diagnostic morphometric features which are further processed by computer vision and machine learning algorithms. Classification accuracy was evaluated in a population specific and a population generic 2-way cross-validation scheme. Population-specific accuracy for individual morphometric features ranged from 78.5 to 96.7%, whereas population generic correct classification ranged from 71.7 to 90.8%. Combining all sex diagnostic traits in multi-feature sex estimation yielded correct classification performance in excess of 91% for the entire sample, whereas the sex of about three fourths of the sample could be determined with 100% accuracy according to posterior probability estimates. The proposed method provides an efficient and reliable way to estimate sex from cranial remains, and it offers significant advantages over existing methods. The proposed method can be readily implemented with the skullanalyzer computer program and the estimate_sex.m GNU Octave function, which are freely available under a suitable license.

• MeSH
• Algorithms * MeSH
• Adult MeSH
• Cephalometry * MeSH
• Skull anatomy & histology   MeSH
• Middle Aged MeSH
• Humans MeSH
• Sex Characteristics MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Software MeSH
• Forensic Anthropology methods   MeSH
• Sex Determination by Skeleton methods   MeSH
• Imaging, Three-Dimensional MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Czech Republic MeSH
• Greece MeSH