Automated Identification from Dental Data (AutoIDD): A New Development in Digital Forensics

Gowri Vijay Reesu (Lead / Corresponding author), Brenainn Woodsend, Scheila Manica, Gavin F. Revie, Nathan L. Brown, Peter A. Mossey

Research output: Contribution to journalArticlepeer-review

22 Citations (Scopus)
462 Downloads (Pure)

Abstract

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 to 100% and 81–100 %, with a mean distance (mm) of 0.094 and 0.093 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.

Original languageEnglish
Article number110218
Pages (from-to)1-9
Number of pages9
JournalForensic Science International
Volume309
Early online date22 Feb 2020
DOIs
Publication statusPublished - Apr 2020

Keywords

  • 3-Dimensional models
  • Automated Identification
  • Dental data
  • Forensic odontology
  • Intra-oral scans

ASJC Scopus subject areas

  • Pathology and Forensic Medicine

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