Determining the effective number and surfaces of teeth for forensic dental identification through the 3D point cloud data analysis

Grey Wolf Optimizer with Behavior Considerations and Dimensional Learning in Three-Dimensional Tooth Model Reconstruction

Three-dimensional registration with the affine transform is one of the most important steps in 3D reconstruction. In this paper, the modified grey wolf optimizer with behavior considerations and dimensional learning (BCDL-GWO) algorithm as a registration method is introduced. To refine the 3D registration result, we incorporate the iterative closet point (ICP). The BCDL-GWO with ICP method is implemented on the scanned commercial orthodontic tooth and regular tooth models. Since this is a registration from multi-views of optical images, the hierarchical structure is implemented. According to the results for both models, the proposed algorithm produces high-quality 3D visualization images with the smallest mean squared error of about 7.2186 and 7.3999 μm2, respectively. Our results are compared with the statistical randomization-based particle swarm optimization (SR-PSO). The results show that the BCDL-GWO with ICP is better than those from the SR-PSO. However, the computational complexities of both methods are similar.

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.

Applications of contemporary artificial intelligence technology in forensic odontology as primary forensic identifier: A scoping review

Background

Forensic odontology may require a visual or clinical method during identification. Sometimes it may require forensic experts to refer to the existing technique to identify individuals, for example, by using the atlas to estimate the dental age. However, the existing technology can be a complicated procedure for a large-scale incident requiring a more significant number of forensic identifications, particularly during mass disasters. This has driven many experts to perform automation in their current practice to improve efficiency.

Objective

This article aims to evaluate current artificial intelligence applications and discuss their performance concerning the algorithm architecture used in forensic odontology.

Methods

This study summarizes the findings of 28 research papers published between 2010 and June 2022 using the Arksey and O'Malley framework, updated by the Joanna Briggs Institute Framework for Scoping Reviews methodology, highlighting the research trend of artificial intelligence technology in forensic odontology. In addition, a literature search was conducted on Web of Science (WoS), Scopus, Google Scholar, and PubMed, and the results were evaluated based on their content and significance.

Results

The potential application of artificial intelligence technology in forensic odontology can be categorized into four: (1) human bite marks, (2) sex determination, (3) age estimation, and (4) dental comparison. This powerful tool can solve humanity's problems by giving an adequate number of datasets, the appropriate implementation of algorithm architecture, and the proper assignment of hyperparameters that enable the model to perform the prediction at a very high level of performance.

Conclusion

The reviewed articles demonstrate that machine learning techniques are reliable for studies involving continuous features such as morphometric parameters. However, machine learning models do not strictly require large training datasets to produce promising results. In contrast, deep learning enables the processing of unstructured data, such as medical images, which require large volumes of data. Occasionally, transfer learning was used to overcome the limitation of data. In the meantime, this method's capacity to automatically learn task-specific feature representations has made it a significant success in forensic odontology.

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.

Lifestyle changes and its effect towards the evolution of human dentition

Background

The dentition of modern humans has evolved from their hominid ancestors to their current form. Factors regarding the changes of lifestyle such as dietary habits and usage of tools have affected the evolution of human dentition. This article aimed to discuss the effect of dietary changes on the evolution of human teeth. An online literature search in the PubMed database was conducted according to the inclusion criteria of this study.

Main body

The culture transition from a hunter-gatherer society to agriculture is followed by dietary changes, which result in a decrease of tooth wear due to more refined food sources in agricultural intensification. By analyzing the microwear pattern such as shear, striation, and pattern of the buccal teeth, the dietary hypothesis based on the occlusal tooth microwear analysis could be examined.

Conclusion

The dietary hypothesis based on the occlusal tooth microwear study could be tested by analyzing the microwear pattern (shear, striation, pattern) of the buccal teeth. Posterior teeth are more closely related to diet, while anterior teeth are related to non-dietary tooth-use behaviors, or using the teeth as a tool or third hand which causes more limited striations at the labial surface.

An Overview of Three Dimensional (3D) Technologies in Forensic Odontology

Three-dimensional (3D) modalities are frequently applied in forensic practice as it tends to give complete information of the evidence merely by touching which has resulted in increased usage in legal medicine and forensic sciences. A number of sub-disciplines of forensic science utilises 3D modalities in an inter-disciplinary manner viz. forensic anthropology, forensic archaeology, forensic odontology, crime-scene investigation, pattern analysis and recovery, courtroom visualisation and ballistic comparison. With appropriate knowledge and utilisation of 3D scanning, modelling and printing technologies, innovative approaches can be implemented for identification in forensic cases. Given that these technologies are evolving rapidly and changing the face of forensic science, the present article collates current developments, working and applications of non-contact scanning techniques, modeling and 3D printing techniques.