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Related Concept Videos

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  11. Handheld Hyperspectral Imaging As A Tool For The Post-mortem Interval Estimation Of Human Skeletal Remains.
  1. Home
  3. Research Domains
  5. History, Heritage And Archaeology
  7. Historical Studies
  9. British History
  11. Handheld Hyperspectral Imaging As A Tool For The Post-mortem Interval Estimation Of Human Skeletal Remains.

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Handheld hyperspectral imaging as a tool for the post-mortem interval estimation of human skeletal remains.

Verena-Maria Schmidt1, Philipp Zelger2, Claudia Wöss1

  • 1Institute of Forensic Medicine, Medical University of Innsbruck, Muellerstraße 44, 6020 Innsbruck, Austria.

Heliyon
|February 20, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

Estimating the time since death for skeletal remains is difficult. A new handheld hyperspectral imaging (HSI) method shows promise for accurately determining post-mortem intervals (PMI) in forensic investigations.

Keywords:
Deep learningDigital image analysisHandheld hyperspectral imagingHuman skeletal remains

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Area of Science:

  • Forensic Anthropology
  • Biophotonics
  • Computational Pathology

Background:

  • Accurate estimation of the post-mortem interval (PMI) for human skeletal remains is crucial in forensic investigations.
  • Current methods for PMI estimation face limitations, necessitating improved techniques.
  • Bones undergo significant environmental interactions and transformations after death, altering their spectral properties.

Purpose of the Study:

  • To introduce and evaluate a novel methodology utilizing a handheld hyperspectral imaging (HSI) system for PMI estimation.
  • To assess the accuracy of HSI in differentiating bone samples across a wide range of post-mortem intervals.
  • To develop a machine learning model for objective and accurate PMI determination.

Main Methods:

  • A handheld hyperspectral imaging (HSI) system was employed to collect spectral data from 104 human skeletal remains.
Post-mortem interval
  • A Convolutional Neural Network (CNN) was utilized to analyze over 65,000 diagnostic spectra.
  • The CNN model was trained to classify bone samples based on their post-mortem intervals, ranging from 1 day to 2000 years.

    • Main Results:

    • The HSI system demonstrated increasing classification accuracy with longer post-mortem intervals.
    • Specific accuracies achieved were 0.58 (0-2 weeks), 0.62 (2 weeks-6 months), 0.73 (6 months-1 year), 0.81 (1-10 years), and 0.98 (>100 years).
    • The model achieved a 98% accuracy in distinguishing bone materials older than 100 years from those younger than 10 years.

    Conclusions:

    • Handheld hyperspectral imaging (HSI) presents a viable and objective approach for determining the post-mortem interval (PMI) of human skeletal remains.
    • The developed CNN model shows adequate predictive performance, particularly for distinguishing very old remains.
    • HSI offers a novel, accurate, and potentially field-deployable tool for forensic anthropology.