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Sex estimation from virtual models: Exploring the potential of stereolithic (STL) 3D crania models for morphoscopic trait scoring

Robles, Madeline; Carew, Rachael M; Rando, Carolyn; Nakhaeizadeh, Sherry; Morgan, Ruth M

Sex estimation from virtual models: Exploring the potential of stereolithic (STL) 3D crania models for morphoscopic trait scoring Thumbnail


Authors

Rachael M Carew

Carolyn Rando

Sherry Nakhaeizadeh

Ruth M Morgan



Abstract

Modern computed tomography (CT) databases are becoming an accepted resource for the practice and development of identification methods in forensic anthropology. However, the utility of 3D models created using free and open-source visualization software such as 3D Slicer has not yet been thoroughly assessed for morphoscopic biological profiling methods where virtual methods of analysis are becoming more common. This paper presents a study that builds on the initial findings from Robles et al. (2020) to determine the feasibility of estimating sex on stereolithic (STL) 3D cranial models produced from CT scans from a modern, living UK population (n = 80) using equation 2 from the Walker's (2008) morphoscopic method. Kendall's coefficients of concordance (KCC) indicated substantial agreement using cranial features scores in an inter-observer test and a video-inter-observer test. Fleiss' Kappa scores showed moderate agreement (0.50) overall between inter-observer sex estimations, and for observer sex estimations in comparison to recorded sexes (0.56). It was found that novice users could virtually employ morphoscopic sex estimation methods effectively on STL 3D cranial models from modern individuals. This study also highlights the potential that digital databases of modern living populations can offer forensic anthropology.

Citation

Robles, M., Carew, R. M., Rando, C., Nakhaeizadeh, S., & Morgan, R. M. (2023). Sex estimation from virtual models: Exploring the potential of stereolithic (STL) 3D crania models for morphoscopic trait scoring. Forensic Sciences Research, 8(2), 123-132. https://doi.org/10.1093/fsr/owad017

Journal Article Type Article
Acceptance Date May 18, 2023
Online Publication Date Jun 23, 2023
Publication Date Jun 30, 2023
Deposit Date Jun 27, 2023
Publicly Available Date Sep 28, 2023
Journal Forensic Sciences Research
Print ISSN 2096-1790
Electronic ISSN 2471-1411
Publisher Oxford University Press
Peer Reviewed Peer Reviewed
Volume 8
Issue 2
Pages 123-132
DOI https://doi.org/10.1093/fsr/owad017
Keywords Forensic Anthropology; 3D Imaging, Forensic Imaging, Forensic Science
Public URL https://uwe-repository.worktribe.com/output/10891556
Publisher URL https://academic.oup.com/fsr/advance-article/doi/10.1093/fsr/owad017/7206008?login=false

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