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Forensic Identification from Three-Dimensional Sphenoid Sinus Images Using the Iterative Closest Point Algorithm.

Xiaoai Dong1, Fei Fan1, Wei Wu1

  • 1West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, People's Republic of China.

Journal of Digital Imaging
|April 5, 2022
PubMed
Summary
This summary is machine-generated.

Forensic identification using sphenoid sinus morphology is now more accurate. Three-dimensional reconstructions and the Iterative Closest Point algorithm achieved over 96% accuracy in personal identification.

Keywords:
Computed Tomography (CT) imagesIterative Closest Point (ICP) algorithmPersonal identificationPoint Cloud Library (PCL)Sphenoid sinus

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Area of Science:

  • Forensic Anthropology
  • Medical Imaging
  • Computer Science

Background:

  • Accurate identification of human remains is vital for legal and humanitarian purposes.
  • Sphenoid sinus morphology exhibits significant individual variation, making it a potential biometric marker.
  • Existing identification methods may have limitations, necessitating novel approaches.

Purpose of the Study:

  • To develop and validate a new protocol for personal identification using 3D sphenoid sinus reconstructions.
  • To assess the efficacy of the Iterative Closest Point (ICP) algorithm for 3D point cloud registration in forensic identification.
  • To establish the accuracy of sphenoid sinus morphology-based identification.

Main Methods:

  • Retrospective analysis of 732 computed tomography (CT) scans (348 female, 384 male) to create 3D sphenoid sinus models.
  • Processing of CT images into Stereo lithography (.STL) format, conversion to PLY format, and adaptation for Point Cloud Library (PCL).
  • Application of the Iterative Closest Point (ICP) algorithm for point cloud matching and evaluation using Rank-N recognition rates.

Main Results:

  • Achieved Rank-1 accuracy of 96.24%, Rank-2 accuracy of 99.73%, and Rank-3 accuracy of 100% in identifying individuals.
  • Demonstrated high precision in matching 3D sphenoid sinus point clouds from different datasets.
  • The ICP algorithm proved effective for comparing complex 3D anatomical structures.

Conclusions:

  • Three-dimensional point cloud registration of sphenoid sinuses is a reliable method for personal identification in forensic contexts.
  • This novel protocol offers a promising tool for forensic identification, enhancing accuracy and efficiency.
  • The study highlights the potential of advanced imaging and computational techniques in forensic science.