Human Identification via Lateral Patella Radiographs: A Validation Study

Niespodziewanski, Emily, Stephan, Carl N., Guyomarc'h, Pierre and Fenton, Todd W. (2015) Human Identification via Lateral Patella Radiographs: A Validation Study. Journal of Forensic Sciences, 61 1: 134-140. doi:10.1111/1556-4029.12898

Author Niespodziewanski, Emily
Stephan, Carl N.
Guyomarc'h, Pierre
Fenton, Todd W.
Title Human Identification via Lateral Patella Radiographs: A Validation Study
Journal name Journal of Forensic Sciences   Check publisher's open access policy
ISSN 0022-1198
Publication date 2015
Year available 2015
Sub-type Article (original research)
DOI 10.1111/1556-4029.12898
Open Access Status Not Open Access
Volume 61
Issue 1
Start page 134
End page 140
Total pages 7
Place of publication Hoboken, United States
Publisher Wiley-Blackwell
Collection year 2016
Language eng
Abstract This research examines the utility of patella outline shape for matching 3D scans of patellae to knee radiographs using elliptical Fourier analysis and subjective methods of human visual comparison of patellae across radiographs for identification purposes. Repeat radiographs were captured of cadaver's knees for visual comparison before patellae were extracted and skeletonized for quantitative comparisons. Quantitative methods provided significant narrowing down of the candidate pool to just a few potential matches (<5% of original sample), while the human analysts showed high capacity for correctly matching radiographs, irrespective of educational level (positive predictive value = 99.8%). The successful computerized matching based on a single quantified patella trait (outline shape) helps explain the potency achieved by subjective visual examination. This work adds to a growing body of studies demonstrating the value of single isolated infracranial bones for human identification via radiographic comparison.
Keyword Forensic science
Forensic anthropology
Human remains
Comparative radiology
Geometric morphometrics
Elliptical Fourier analysis
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Biomedical Sciences Publications
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 0 times in Thomson Reuters Web of Science Article
Scopus Citation Count Cited 0 times in Scopus Article
Google Scholar Search Google Scholar
Created: Tue, 25 Aug 2015, 01:58:05 EST by System User on behalf of Scholarly Communication and Digitisation Service