GADNN: a revolutionary hybrid deep learning neural network for age and sex determination utilizing cone beam computed tomography images of maxillary and frontal sinuses.

Journal: BMC medical research methodology
Published Date: Feb 27, 2024

Abstract

INTRODUCTION: The determination of identity factors such as age and sex has gained significance in both criminal and civil cases. Paranasal sinuses like frontal and maxillary sinuses, are resistant to trauma and can aid profiling. We developed a deep learning (DL) model optimized by an evolutionary algorithm (genetic algorithm/GA) to determine sex and age using paranasal sinus parameters based on cone-beam computed tomography (CBCT).

Authors

  • Omid Hamidi
    Department of Science, Hamedan University of Technology, Hamedan, Iran.
  • Mahlagha Afrasiabi
    Department of Computer Engineering, Hamedan University of Technology, Hamedan, Iran. m.afrasiabi@hut.ac.ir.
  • Marjan Namaki
    Department of Computer Engineering, Hamedan University of Technology, Hamedan, Iran.

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