Automatic removal of soft tissue from 3D dental photo scans; an important step in automating future forensic odontology identification

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).

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3