Literature DB >> 25929827

Modeling Bone Surface Morphology: A Fully Quantitative Method for Age-at-Death Estimation Using the Pubic Symphysis.

Dennis E Slice1, Bridget F B Algee-Hewitt2.   

Abstract

The pubic symphysis is widely used in age estimation for the adult skeleton. Standard practice requires the visual comparison of surface morphology against criteria representing predefined phases and the estimation of case-specific age from an age range associated with the chosen phase. Known problems of method and observer error necessitate alternative tools to quantify age-related change in pubic morphology. This paper presents an objective, fully quantitative method for estimating age-at-death from the skeleton, which exploits a variance-based score of surface complexity computed from vertices obtained from a scanner sampling the pubic symphysis. For laser scans from 41 modern American male skeletons, this method produces results that are significantly associated with known age-at-death (RMSE = 17.15 years). Chronological age is predicted, therefore, equally well, if not, better, with this robust, objective, and fully quantitative method than with prevailing phase-aging systems. This method contributes to forensic casework by responding to medico-legal expectations for evidence standards.
© 2015 American Academy of Forensic Sciences.

Keywords:  age-at-death estimation; forensic anthropology; forensic science; human skeletal identification; morphometrics; pubic symphysis; three-dimensional coordinate data

Mesh:

Year:  2015        PMID: 25929827     DOI: 10.1111/1556-4029.12778

Source DB:  PubMed          Journal:  J Forensic Sci        ISSN: 0022-1198            Impact factor:   1.832


  6 in total

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Review 2.  Evaluating osteological ageing from digital data.

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3.  Technical note: preliminary insight into a new method for age-at-death estimation from the pubic symphysis.

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4.  Correlation of the human pubic symphysis surface with age-at-death: a novel quantitative method based on a bandpass filter.

Authors:  Guillermo Bravo Morante; Fred L Bookstein; Barbara Fischer; Katrin Schaefer; Inmaculada Alemán Aguilera; Miguel Cecilio Botella López
Journal:  Int J Legal Med       Date:  2021-04-15       Impact factor: 2.686

5.  Adult Skeletal Age-at-Death Estimation through Deep Random Neural Networks: A New Method and Its Computational Analysis.

Authors:  David Navega; Ernesto Costa; Eugénia Cunha
Journal:  Biology (Basel)       Date:  2022-03-30

6.  The computational age-at-death estimation from 3D surface models of the adult pubic symphysis using data mining methods.

Authors:  Anežka Kotěrová; Michal Štepanovský; Zdeněk Buk; Jaroslav Brůžek; Nawaporn Techataweewan; Jana Velemínská
Journal:  Sci Rep       Date:  2022-06-20       Impact factor: 4.996

  6 in total

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