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

• Open-source software for automating 3D surface comparison. • Does not require high-end or discrete graphics hardware or Internet connection. • Automates 3D comparison tasks. • Applies automatic segmentation of datasets. • Ranks best matches for operator assessment. 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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Publication Details

Journal
Forensic Imaging
Published
2024-12-28
DOI
https://doi.org/10.1016/j.fri.2024.200621
Citations
3
Primary Topic
Dental Radiography and Imaging
Type
article
Field-Weighted Citation Impact
1.48
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article

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

Alex Forrest, Ryan Choi, Denice Higgins, Ove A. Peters et al.
3 citations
Forensic Imaging
Dental Radiography and Imaging
1.48
article

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

Alex Forrest, Ryan Choi, Denice Higgins, Ove A. Peters, Arthur Porto, Harry Perkins, Christine Peters, Sean Choi, Sanmarié Schlebusch
article en
3 citations

Abstract

• Open-source software for automating 3D surface comparison. • Does not require high-end or discrete graphics hardware or Internet connection. • Automates 3D comparison tasks. • Applies automatic segmentation of datasets. • Ranks best matches for operator assessment. 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.

Forensic ImagingVol. 40
Griffith University (AU), Queensland Health (AU), Florida Museum of Natural History (US), The University of Queensland (AU), University of South Australia (AU), Loma Linda University (US), Scientific Services (ZA), The University of Adelaide (AU)
Gender equality
Openalex Percentile: Top 17%
Dental Radiography and Imaging
1.48
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