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Sex estimation using skull silhouette images from postmortem computed tomography by deep learning.

Tomoyuki Seo1, Yongsu Yoon2, Yeji Kim3

  • 1Medical Quantum Science Course, Department of Health Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan.

Scientific Reports
|September 30, 2024
PubMed
Summary
This summary is machine-generated.

Rapid sex estimation from skull silhouettes using deep learning is now feasible. This method, utilizing postmortem computed tomography (PMCT) and X-ray images, aids in disaster victim identification.

Keywords:
Deep learningPersonal identificationPostmortem computed tomographySex estimationSilhouette images

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Area of Science:

  • Forensic Anthropology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Prompt personal identification is crucial in mass casualty incidents.
  • Skull morphology is a key indicator for sex estimation.
  • Traditional methods can be time-consuming.

Purpose of the Study:

  • To develop a rapid sex estimation method using skull silhouette images.
  • To apply deep learning techniques for enhanced accuracy in sex determination.
  • To explore the utility of postmortem computed tomography (PMCT) and X-ray imaging for this purpose.

Main Methods:

  • Utilized 2D silhouette images derived from head PMCT scans.
  • Employed deep learning models (AlexNet, VGG16) for transfer learning.
  • Investigated sex estimation accuracy using single and multiple projection angles with majority voting.

Main Results:

  • VGG16 model achieved 89.8% accuracy for sex estimation from lateral skull projections.
  • Incorporating a majority vote from multiple angles improved accuracy to 91.7%.
  • Demonstrated the feasibility of using silhouette images from both PMCT and conventional X-rays.

Conclusions:

  • Deep learning combined with skull silhouette images offers a viable approach for rapid sex estimation.
  • This technique holds potential for improving personal identification in forensic contexts.
  • X-ray imaging, in addition to PMCT, can be effectively used for this identification method.