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There has been a significant expansion in the use of 3-dimensional (3D) dental images in recent years. In the field of forensic odontology, an automated 3D dental identification system could enhance the identification process. This study presents a novel method for automated human dental identification using 3D digital dental data by utilising a dental identification scenario. The total study sample was divided into two groups: Group A (120 dental models) and Group B (120 Intra-oral scans-IOS). Group A data was composed of 3D scanned dental models of post-orthodontic treated patients (30 maxillary and 30 mandibular). This data was considered as AM digital data. To generate an identical sample, the dental casts (60) of the same patients were retrieved and laser scanned. These models were considered as PM digital data. Group B data (IOS) was obtained from 30 study participants. To reconstruct a dental identification scenario 30 maxillary and 30 mandibular IOS were obtained from 30 participants and were considered as IOS-AM. After one year, another set of IOS (60) were acquired from the same participants and were considered as IOS-PM. The results showed that the AutoIDD (Automated Identification from Dental Data) software was consistent in accuracy; capable of differentiating "correct matches" (high match percentage) from "non-matches" (very low percentage) by 3D image superimposition. The match percentage of the maxillary and mandibular IOS ranged from 64-100% and 81-100%, with a mean percentage of 96.7 and 96.4 respectively. This study demonstrated the feasibility of using 3D scans through a new automated software-AutoIDD in digital forensics to assist the forensic expert in confirming the identity of a deceased individual from the available AM dental records.

Photographs of a person smiling may provide valuable information about their anterior dentition. These images can be an alternative ante-mortem (AM) dental source in cases with no dental records, which gives the forensic odontologist a significant opportunity for comparative dental analysis. There are no reported studies that have investigated the reliability of a superimposition technique using 2D photographs of a smile and 3D dental models in dental identification. The aim of this study was to explore novel odontological methods by combining 2D photographs with 3D dental models, simulating a dental identification scenario. The objective was to increase the accuracy of dental identification using an AM photograph with the aid of 3D imaging as an alternative to post-mortem (PM) photographs. The study comprised of 31 3D dental models (simulating PM information) and 35 digital photographs (simulating AM information). The data was analysed in two phases: Phase I-Visual Comparison of 2D-3D images and Phase II-2D-3D superimposition after a wash out period.Both methods were analysed by the principal investigator. Further, one-third (ten) of the sample was evaluated by six raters (three experienced forensic odontologists and three forensic odontology MSc. students). The interrater agreement was assessed using intra-class correlation (ICC 2, 1, absolute). The results of the study suggest that the inter-rater and intra-rater reliability using 3D superimposition was highest (ICC  1.0). In summary, there was an increase in match rates and higher certainty among the opinions reached when using the 2D-3D superimposition method. The procedure attempted to reduce the limitations of previously existing 2D methods and is intended to assist forensic experts with a reliable method in photographic dental identification when expressing conclusions on a case.

This study aimed to systematically review the correlational accuracy between width ratios and length ratios based on the Kvaal methodology with chronological age. This systematic review followed Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). The search strategy included ProQuest, PubMed, Science Direct, and Taylor and Francis and Willey online without time or language restriction using Kvaal method of age estimation as key words for the search up to December 2021. A team of two researchers independently selected the studies and extracted the data. The Covidence platform was used to systematically organize all titles. The full texts of eligible studies were analyzed. Risk of bias (RoB) was assessed using a modified (to the specific characteristics of this systematic review) checklist based on Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement checklist for observational studies. A total of 658 articles were initially reviewed, but 22 were selected for inclusion. The risk of bias was estimated to be unclear to low overall. Among the length ratios, ratio R showed a strong association with chronological age, followed by ratio P. For the width ratios, ratio B demonstrated a close association with chronological age, followed by ratio C. The results suggest that width ratios correlate better with chronological age than length ratios. This systematic review suggests the width ratios are more strongly associated with chronological age than the length ratios. Using a width ratio could serve as a convenient and rapid way to estimate dental age. Our results apply equally to all types of ethnic groups.