BACKGROUND: The aim of this study was to evaluate whether a forensic odontologist working remotely could accurately undertake forensic dental identifications using videos produced by non-dental forensic staff operating an intra-oral video camera (IOVC). The study\'s aims were to assess the accuracy and time taken to perform remote forensic dental identifications in this manner.
METHODS: Eight cadavers from the Centre for Anatomy and Human Identification (CAHID), University of Dundee, UK, were examined by a forensic odontologist via a traditional dental examination. Their dental condition was recorded to serve as ante-mortem records for this study. Videos of each dentition were produced using an IOVC operated by a medical student. Post-mortem records were produced for each dentition from the videos by a remote second forensic odontologist who was not present at the traditional dental examination. The ante-mortem and post-mortem records were then compared, and identification was classified as positively established, possible or excluded.
RESULTS: Established identifications were positively made in all eight cases although there were some non-critical inconsistencies between ante-mortem and post-mortem records. Before the second opinion, 85.6% of the teeth per study subject were charted consistently. After the second opinion, the percentage of consistency increased to 97.2%. Each video on average was about 4.13 minutes in duration and the average time taken to interpret and chart the post-mortem dental examination at the first attempt was 11.63 minutes. The time taken to chart from the videos was greater than is typical of a traditional dental examination.
CONCLUSIONS: This pilot study supports the feasibility of undertaking remote dental identification. This novel \"tele-dental virtopsy\" approach could be a viable alternative to a traditional post-mortem dental examination, in situations where access to forensic dental services is difficult or limited due to geographical, logistical, safety, and/or political reasons.

OBJECTIVE: Computer vision (CV) mimics human vision, enabling computers to automatically compare radiological images from recent examinations with a large image database for unique identification, crucial in emergency scenarios involving unknown patients or deceased individuals. This study aims to extend a CV-based personal identification method from orthopantomograms (OPGs) to computed tomography (CT) examinations using single CT slices.
METHODS: The study analyzed 819 cranial computed tomography (CCT) examinations from 722 individuals, focusing on single CT slices from six anatomical regions to explore their potential for CV-based personal identification in 69 procedures. CV automatically identifies and describes interesting features in images, which can be recognized in a reference image and then designated as matching points. In this study, the number of matching points was used as an indicator for identification.
RESULTS: Across six different regions, identification rates ranged from 41/69 (59%) to 69/69 (100%) across over 700 possible identities. Comparison of images from the same individual achieved higher matching points, averaging 6.32 ± 0.52% (100% represents the maximum possible matching points), while images of different individuals averaged 0.94 ± 0.15%. Reliable matching points are found in the teeth, maxilla, cervical spine, skull bones, and paranasal sinuses, with the maxillary sinuses and ethmoidal cells being particularly suitable for identification due to their abundant matching points.
CONCLUSIONS: Unambiguous identification of individuals based on a single CT slice is achievable, with maxillary sinus CT slices showing the highest identification rates. However, metal artifacts, especially from dental prosthetics, and various head positions can hinder identification.
CONCLUSIONS: Radiology possesses a multitude of reference images for a CV database, facilitating automated CV-based personal identification in emergency examinations or cases involving unknown deceased individuals. This enhances patient care and communication with relatives by granting access to medical history.
CONCLUSIONS: Unknown individuals in radiology or forensics pose challenges, addressed through automatic CV-based identification methods. A single CT slice highlighting the maxillary sinuses is particularly effective for personal identification. Radiology plays a pivotal role in automated personal identification by leveraging its extensive image database.

Gait recognition has become an increasingly promising area of research in the search for noninvasive and effective methods of person identification. Its potential applications in security systems and medical diagnosis make it an exciting field with wide-ranging implications. However, precisely recognizing and assessing gait patterns is difficult, particularly in changing situations or from multiple perspectives. In this study, we utilized the widely used CASIA-B dataset to observe the performance of our proposed gait recognition model, with the aim of addressing some of the existing limitations in this field. Fifty individuals are randomly selected from the dataset, and the resulting data are split evenly for training and testing purposes. We begin by excerpting features from gait photos using two well-known deep learning networks, MobileNetV1 and Xception. We then combined these features and reduced their dimensionality via principal component analysis (PCA) to improve the model\'s performance. We subsequently assessed the model using two distinct classifiers: a random forest and a one against all support vector machine (OaA-SVM). The findings indicate that the OaA-SVM classifier manifests superior performance compared to the others, with a mean accuracy of 98.77% over eleven different viewing angles. This study is conducive to the development of effective gait recognition algorithms that can be applied to heighten people\'s security and promote their well-being.

Dental measurements have been proposed as parameters for stature estimation for at least 85 years. The scientific literature on the topic, however, is controversial regarding the performance of the method. This systematic literature review of observational cross-sectional studies aimed to compile evidence to support decisions in the forensic practice regarding the use of dental measurements for stature estimation. Embase, LILACS, MedLine (via PubMed), SciELO, Scopus, Web of Science, DansEasy and Open Access Thesis and Dissertations (OATD) were searched. Data regarding the rate of correct stature classifications were extracted. A meta-analysis with a Random Intercept Logistic Regression model and a Logit Transformation was conducted. The search led to 10.803 entries, out of which 15 were considered eligible (n = 1486 individuals). The studies were published between 1990 and 2020 and were authored by South American (n = 7) and Asian (n = 8) research teams. Dental measurements were predominantly (93.34 %) performed on dental casts or via intraoral inspection. The overall rate of correct classifications based on stature was 68 %. Excluding outliers, the overall accuracy of the method decreased to 64 % (95 %CI: 54-73 %). Significant heterogeneity was detected (I² = 72.4 %, τ2 = 0.24, H = 1.91, p < 0.001). Egger\'s test (p = 0.94) and the funnel plot did not reveal publication bias. Dental measurements are not reliable for stature estimation in the forensic field.

This study aimed to evaluate the reliability of an age estimation method based on the pulp⁄tooth area ratio by assessing intra- and inter-examiner agreement across five observers at different intervals. Using the same X-ray device and technical parameters, 96 digital periapical X-ray images of upper and lower canines were obtained from 28 deceased people in Central America, whose age at death ranged from 19 to 49 years. Excellent and good agreement of results were achieved, and there were no statistically significant differences. The R2 value for upper teeth (54.0%) was higher than the R2 value for lower teeth (45.7%). The highest intraclass correlation coefficient value was 0.995 (0.993-0.997) and the lowest 0.798 (0.545-0.895). Inter-examiner agreement was high with values of 0.975 (0.965-0.983) and 0.927 (0.879-0.955). This method is adequate for assessing age in missing and unidentified people, including victims of mass disasters.

In mass disaster events, forensic DNA laboratories may be called upon to quickly pivot their operations toward identifying bodies and reuniting remains with family members. Ideally, laboratories have considered this possibility in advance and have a plan in place. Compared with traditional short tandem repeat (STR) typing, single nucleotide polymorphisms (SNPs) may be better suited to these disaster victim identification (DVI) scenarios due to their small genomic target size, resulting in an improved success rate in degraded DNA samples. As the landscape of technology has shifted toward DNA sequencing, many forensic laboratories now have benchtop instruments available for massively parallel sequencing (MPS), facilitating this operational pivot from routine forensic STR casework to DVI SNP typing. Herein, we present the commercially available SNP sequencing assays amenable to DVI, we use data simulations to explore the potential for kinship prediction from SNP panels of varying sizes, and we give an example DVI scenario as context for presenting the matrix of considerations: kinship predictive potential, cost, and throughput of current SNP assay options. This information is intended to assist laboratories in choosing a SNP system for disaster preparedness.

Background Gender determination is critical to forensic science and medico-legal applications. Given that it is the most dimorphic bone in the skull and is frequently found intact, the mandibular bone may be extremely important in determining gender. Orthopantomograms (OPGs) are quite helpful in accurately estimating age and sex in this regard. It is a laborious task for forensics to determine the gender of victims of mass casualties, natural disasters, and severely dismembered bodies. The mandible, which is susceptible to development spurts, has a high degree of accuracy for determining sex. Aim  This study aims to evaluate the potential use of coronoid height and condylar height as reliable anatomical markers for determining gender. Materials and methods In this study, 100 samples were used as study samples, 50 of which were male and 50 of which were female, in the age group of 20-30 years. The OPGs were obtained using a Planmeca Promax Scara 3 Digital OPG Machine (Planmeca, Helsinki, Finland), with settings of 70 kVp, 8 mA for 0.9 seconds, ensuring a 1:1 ratio. The images were then transferred to Planmeca Romexis® Viewer Software, Version 6.0 (Planmeca Oy, Helsinki, Finland) for measurement recording. Results Descriptive statistical analysis was done for this study and discriminant analysis was also done to create a population-specific formula. Results showed that the standard mean error for males concerning condylar height was 2.3 and coronoid height was 0.7. The standard mean error for females by condylar height was 1.6 and coronoid height was 0.6. The p-value was significant for coronoid height in both males and females. The p-value was not clinically significant for condylar height in both males and females. Conclusion The study\'s findings indicate that a larger mandibular angle is advantageous for gender assessment and helps with gender dimorphism. Out of both the parameters evaluated, coronoid height has shown statistical significance in both males and females. Hence, the study concludes that the parameter, coronoid height can be utilized to assess the gender of an individual.

In forensic scenarios, such as armed conflicts or mass disasters, the oral cavity can be a valuable source of identification information relevant to legal issues. In many European Union countries, it is mandatory to register dental records for identification purposes. A pilot and quasi-experimental study was performed. The study aims to analyze two methodologies, photography and wireless intraoral (IO) laser scanner, in the scope of the orofacial record in forensic pathology, highlighting their impact on human identification. The IO scanner i700 (Medit, Lusobionic, Portugal) and Canon 5D-Full Frame equipment were used to record the individual status, living patients (n = 5), and forensic cases (n = 5). IO and extraoral anatomical structures were recorded following six parameters: time, mineralized and soft detail, communication, extra devices, and distortion. The statistical analysis was performed in accordance with a scoring system and Mann-Whitney (P < 0.05) analysis. The photography method recorded extraoral data for all samples (score range between 15 and 23). The time elapsed to complete an IO scan in forensic cases was shorter than with photography, without requiring additional sources of light or mirror devices. Living patients and corpses identified statistically significant differences. It can be concluded that laser scanners are a valuable tool in the field of forensic pathology and can be used to record and analyze anatomic-morphological data for identification purposes accurately.
UNASSIGNED: Human identification engages in orofacial details records.Photographic and laser scans record intraoral and extraoral anatomic structures.Forensic cases assessed by intraoral scanner technology are accurate and less time-consuming, optimizing the orofacial data for identification.

Identifying edentulous victims in forensic contexts poses a significant challenge. It has been reported that having a denture to reproduce and compare Palatal Rugae (PR) patterns is crucial for identifying edentulous individuals, yet there are no validated protocols for conducting this procedure. In this study, a new method was developed and validated for plaster molding of the internal surface of upper dentures, along with a protocol involving focus-stacked photographs and reference scales. Thirty-eight edentulous subjects participated in the study, obtaining plaster models of the patients (PM), and their dentures (AM) were standardized. The AM/PM model was highlighted and photographed with ten shots in different z-focuses for each model, using standard lighting and aligning the position of the PR perpendicular to the photographic axis using tubular spirit levels and modeling clay. The images were processed using the stacking technique and analyzed by three observers through the proposed protocol using Adobe® Photoshop®. The results were analyzed based on the intra-observer and inter-observer agreement levels, with a 95% confidence interval. This study demonstrated high-precision intra-observer and inter-observer agreement (k = 1) in the matching of Palatal Rugae (PR) and maxillary morphology obtained from participants and their dentures. The protocol is simple, cost-effective, and precise. It enables standardization of the technique for obtaining plaster models, and the exposure of PR and photographic protocol minimizes the presence of artifacts in the images, thereby reducing the likelihood of errors and promoting the reproducibility of both the recording technique and the comparison of the PR.

Mass disaster events can result in high levels of casualties that need to be identified. Whilst disaster victim identification (DVI) relies on primary identifiers of DNA, fingerprints, and dental, these require ante-mortem data that may not exist or be easily obtainable. Facial recognition technology may be able to assist. Automated facial recognition has advanced considerably and access to ante-mortem facial images are readily available. Facial recognition could therefore be used to expedite the DVI process by narrowing down leads before primary identifiers are made available. This research explores the feasibility of using automated facial recognition technology to support DVI. We evaluated the performance of a commercial-off-the-self facial recognition algorithm on post-mortem images (representing images taken after a mass disaster) against ante-mortem images (representing a database that may exist within agencies who hold face databases for identity documents (such as passports or driver\'s licenses). We explored facial recognition performance for different operational scenarios, with different levels of face image quality, and by cause of death. Our research is the largest facial recognition evaluation of post-mortem and ante-mortem images to date. We demonstrated that facial recognition technology would be valuable for DVI and that the performance varies by image quality and cause of death. We provide recommendations for future research.