Eigenfemora—Age-at-Death Estimation in the Proximal Femur through an Image Processing Approach

Author:

Navega David12,Ferreira Maria Teresa2,Curate Francisco3ORCID

Affiliation:

1. National Institute of Legal Medicine and Forensic Sciences, 3000-548 Coimbra, Portugal

2. Centre for Functional Ecology (CEF), Laboratory of Forensic Anthropology, Department of Life Sciences, University of Coimbra, 3000-456 Coimbra, Portugal

3. Research Centre for Anthropology and Health (CIAS), Department of Life Sciences, Faculty of Sciences and Technology, University of Coimbra, 3000-456 Coimbra, Portugal

Abstract

Estimating age at death is essential to establish biological profiles from human skeletal remains in both forensic and archeological settings. Imaging studies of skeletal age changes in adults have described the metamorphosis of trabecular bone structure and bone loss in the proximal femur as well as changes in morphology during different stages of life. This study aims to assess the utility of a digital representation of conventional X-ray films of the proximal femur for the estimation of age at death in a sample of 91 adult individuals (47 females and 44 males) of the Coimbra Identified Skeletal Collection. The proposed approach showed a root mean squared error (RMSE) of 17.32 years (and mean absolute error of 13.47 years) for females and an RMSE of 14.06 years (mean absolute error of 11.08 years) for males. The main advantage of this approach is consistency in feature detection and extraction, as X-ray images projected on the femora space will always produce the same set features to be analyzed for age estimation, while more traditional methods rely heavily on operator experience that can lead to inconsistent age estimates among experts.

Funder

R&D Units Center for Functional Ecology—Science for People and the Planet

Research Centre for Anthropology and Health

FCT/MCTES through national funds

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference67 articles.

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3. Navega, D., Costa, E., and Cunha, E. (2022). Adult Skeletal Age-At-Death Estimation through Deep Random Neural Networks: A New Method and Its Computational Analysis. Biology, 11.

4. Komar, D.A., and Buikstra, J.E. (2007). Forensic Anthropology: Contemporary Theory and Practice, Oxford University Press.

5. Assessing the Accuracy of Cranial and Pelvic Ageing Methods on Human Skeletal Remains from a Modern Greek Assemblage;Xanthopoulou;Forensic Sci. Int.,2018

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