Author:
Kofod Petersen Anika,Forgie Andrew,Bindslev Dorthe Arenholt,Villesen Palle,Staun Larsen Line
Abstract
AbstractThe potential of intraoral 3D photo scans in forensic odontology identification remains largely unexplored, even though the high degree of detail could allow automated comparison of ante mortem and post mortem dentitions. Differences in soft tissue conditions between ante- and post mortem intraoral 3D photo scans may cause ambiguous variation, burdening the potential automation of the matching process and underlining the need for limiting inclusion of soft tissue in dental comparison. The soft tissue removal must be able to handle dental arches with missing teeth, and intraoral 3D photo scans not originating from plaster models. To address these challenges, we have developed the grid-cutting method. The method is customisable, allowing fine-grained analysis using a small grid size and adaptation of how much of the soft tissues are excluded from the cropped dental scan. When tested on 66 dental scans, the grid-cutting method was able to limit the amount of soft tissue without removing any teeth in 63/66 dental scans. The remaining 3 dental scans had partly erupted third molars (wisdom teeth) which were removed by the grid-cutting method. Overall, the grid-cutting method represents an important step towards automating the matching process in forensic odontology identification using intraoral 3D photo scans.
Funder
Aarhus University Research Foundation
Publisher
Springer Science and Business Media LLC
Reference20 articles.
1. Brough, A. L., Morgan, B. & Rutty, G. N. The basics of disaster victim identification. J. For. Radiol. Imag. 3(1), 29–37 (2015).
2. Interpol, Disaster Victim Identification (DVI) https://www.interpol.int/en/How-we-work/Forensics/Disaster-Victim-Identification-DVI. Accessed 16th May 2023. 2023.
3. Berketa, J. W., James, H. & Lake, A. W. Forensic odontology involvement in disaster victim identification. For. Sci. Med. Pathol. 8(2), 148–156 (2012).
4. Interpol, Interpol Disaster Victim Identification Guide, in Part B, Annexure 8: Methods of Identification. November 2023.
5. Eto, N., Yamazoe, J., Tsuji, A., Wada, N. & Ikeda, N. Development of an artificial intelligence-based algorithm to classify images acquired with an intraoral scanner of individual molar teeth into three categories. PLoS ONE 17(1), e0261870 (2022).