Development of automatic 3D model comparison (ModelMatch3D) for forensic identification and testing using odontology data

IF 0.8 Q4 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Jiwon Choi , Seongwon Choi , Arthur Porto , Harry Perkins , Sanmarié Schlebusch , Denice Higgins , Ove A. Peters , Christine I. Peters , Alex Forrest
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引用次数: 0

Abstract

Three-dimensional (3D) imaging techniques including radiographic and optical surface scans are used in many medical fields including dentistry. Comparison of the resulting antemortem (AM) and postmortem (PM) data has been limited, partly due to the absence of specialised, affordable software. To address this gap, we introduce ModelMatch3D, an open-source software built upon the established 3D Slicer platform, designed to automate general 3D comparison tasks and enable rapid comparison of 3D surface data. It requires minimal preparation of datasets prior to use.
ModelMatch3D was evaluated using de-identified 3D dental scans sourced from a collection at the University of Adelaide. Dental data was selected due to its recognised importance as one of the three major identifiers by INTERPOL. Although we tested it with dental data, it can be applied to any 3D surface datasets of distinctive shape, extending its utility beyond forensic science.
ModelMatch3D runs on all major operating systems ensuring wide accessibility. It runs well on lower-end systems without discrete graphics capability. Its broad compatibility and minimal computing requirements enable its deployment in diverse forensic environments, providing an easy-to-use, automated method for rapid comparison and where multiple victims are involved, ranking of matches for subsequent expert inspection.
Technically, ModelMatch3D employs advanced algorithms for point cloud processing and feature extraction which enable rapid handling of substantial databases with no need for preprocessing.
We believe that ModelMatch3D fills a gap in forensic identification and opens avenues for comparison of other hard tissues and structures, providing a robust platform for enhancing computational forensics.

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来源期刊
Forensic Imaging
Forensic Imaging RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING-
CiteScore
2.20
自引率
27.30%
发文量
39
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