Exploring the feasibility of smartphone cameras for 3D modelling of bite patterns in forensic dental identification.

The field of bitemark analysis involves examining physical alterations in a medium resulting from contact with teeth and other oral structures. Various techniques, such as 2D and 3D imaging, have been developed in recent decades to ensure precise analysis of bitemarks. This study assessed the precision of using a smartphone camera to generate 3D models of bitemark patterns. A 3D model of the bite mark pattern was created using 3Shape TRIOSTM and a smartphone camera combined with monoscopic photogrammetry. The mesiodistal dimensions of the anterior teeth were measured using Rapidform Explorer and OrtogOnBlender, and the collected data were analyzed using IBM® SPSS® Statistics version 23.0. The mean mesiodistal dimension of the anterior teeth, as measured on the 3D model from 3Shape TRIOSTM and smartphone cameras, was found to be 6.95 ± 0.7667 mm and 6.94 ± 0.7639 mm, respectively. Statistical analysis revealed no significant difference between the two measurement methods, p > 0.05. The outcomes derived from this study unequivocally illustrate that a smartphone camera possessing the specific parameters detailed in this study can create a 3D representation of bite patterns with an accuracy level on par with the outputs of a 3D intraoral camera. These findings underscore the promising trajectory of merging smartphone cameras and monoscopic photogrammetry techniques, positioning them as a budget-friendly avenue for 3D bitemark analysis. Notably, the monoscopic photogrammetry methodology assumes substantial significance within forensic odontology due to its capacity for precise 3D reconstructions and the preservation of critical measurement data.

3D Bitemark Analysis in Forensic Odontology Utilizing a Smartphone Camera and Open-Source Monoscopic Photogrammetry Surface Scanning

Abstract Bitemark analysis is a challenging procedure in the field of criminal case investigation. The unique characteristics of dentition are used to find the best match between the existing patterned injury and the suspected perpetrator in bitemark identification. Bitemark analysis accuracy can be influenced by various factors, including biting pressure, tooth morphology, skin elasticity, dental cast duplication, timing, and image quality. This review article discusses the potential of a smartphone camera as an alternative method for 3D bitemark analysis. Bitemark evidence on human skin and food should be immediately recorded or duplicated to retrieve long-lasting proof, allowing for a sufficient examination period. Various studies utilizing two-dimensional (2D) and three-dimensional (3D) technologies have been developed to obtain an adequate bitemark analysis. 3D imaging technology provides accurate and precise analysis. However, the currently available method using an intraoral scanner (IOS) requires high-cost specialized equipment and a well-trained operator. The numerous advantages of monoscopic photogrammetry may lead to a novel method of 3D bitemark analysis in forensic odontology. Smartphone cameras and monoscopic photogrammetry methodology could lead to a novel method of 3D bitemark analysis with an efficient cost and readily available equipment.

Children and Adolescent Dental Age Estimation by the Willems and Al Qahtani Methods in Surabaya, Indonesia.

Objectives: Dental age estimation has been employed in a range of legal operations as well as catastrophe victim identification. Dental age estimation is regarded as an appropriate method for estimating a person's age because there is a high association between age and teeth. This study aims to assess the suitability of the Al Qahtani and Willems dental age estimation approaches for the Indonesian children and adolescent population. Methods: A total of 150 panoramic radiographs of patients (75 boys and 75 girls, 6-17 years old) were obtained from the Department of Radiology, Airlangga University, Indonesia. One researcher analyzed estimated dental age (EDA) twice in a one-week time-lapse using the Willems and Al Qahtani methods. The statistical analysis of the present study was carried out using IBM® SPSS® Statistics version 25.0 (IBM, Armonk, NY, USA). Results: The mean of this study's chronological age (CA) was 11.60 ± 3.41. Using the Willems method, the mean difference between CA and EDA for boys and girls was -0.41 ± 0.90. The mean difference between CA and EDA for boys and girls is 0.33 ± 0.61 using the Al Qahtani method. Conclusions: According to the findings of this investigation, the dental age estimation method proposed by Al Qahtani and Willems can be applied to the population in Surabaya. However, a comprehensive study is required when using this method because the data revealed significant statistical disparities between the two methods.

The Applicable Dental Age Estimation Methods for Children and Adolescents in Indonesia.

Indonesia is an archipelagic country bordered by tectonically active zones with intense seismicity and volcanism. This condition is often associated with a high-risk situation of disasters in Indonesia. Forensic identification is a necessary procedure to reveal an individual's identity. An identity, including sex and age, is needed to build a conclusion of human identification. Dental age estimation is a subfield of forensic odontology which focuses on establishing an individual's age. Tooth development, biochemical, and postformation changes are the parameters for estimating dental age. This review discusses the applicable dental age estimation method for children and adolescents in Indonesia. Several articles that have previously studied dental age estimation in Indonesia were reviewed for this manuscript. On reviewing these articles, it was found that the Demirjian method, the Willems method, and the Al Qahtani method are useful in this population with higher accuracy than other methods.