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Automatic Detection of Symmetry Plane for Computer-Aided Surgical Simulation in Craniomaxillofacial Surgery Publisher Pubmed



Noori SMR1, 2 ; Farnia P1, 2 ; Bayat M3, 4 ; Bahrami N3, 5 ; Shakourirad A6, 7 ; Ahmadian A1, 2
Authors
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Authors Affiliations
  1. 1. Departments of Medical Physics and Biomedical Engineering, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
  2. 2. Research Center for Biomedical Technologies and Robotics, Tehran University of Medical Sciences, Tehran, Iran
  3. 3. Craniomaxillofacial Research Center, Tehran University of Medical Sciences, Tehran, Iran
  4. 4. Oral and Maxillofacial Surgery Department, School of Dentistry, Tehran University of Medical Sciences, Tehran, Iran
  5. 5. Department of Tissue Engineering and Applied Cell Sciences, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
  6. 6. Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Sina Hospital, Tehran University of Medical Sciences, Tehran, Iran
  7. 7. Department of Radiology, Tehran University of Medical Sciences, Tehran, Iran

Source: Physical and Engineering Sciences in Medicine Published:2020


Abstract

Abstract: Symmetry plane calculation is used in fracture reduction or reconstruction in the midface. Estimating a reliable symmetry plane without advanced anatomic knowledge is the most critical challenge. In this work, we developed a new automated method to find the mid-plane in CT images of an intact skull and a skull with a unilateral midface fracture. By use of a 3D point-cloud of a skull, we demonstrate that the proposed algorithm could find a mid-plane that meets clinical criteria. There is no need for advanced anatomical knowledge through the use of this algorithm. The algorithm used principal component analysis to find the initial plane. Then the rotation matrix, derived from an iterative closest point (ICP) registration method, is used to update the normal vector of the plane and find the optimum symmetry plane. A mathematical index, Hausdorff distance (HD), is used to evaluate the similarity of one mid-plane side in comparison to the contralateral side. HD decreased by 66% in the intact skull and 65% in a fractured skull and converged in just six iterations. High convergence speed, low computational load, and high accuracy suggest the use of the algorithm in the planning procedure. This easy-to-use algorithm with its advantages, as mentioned above, could be used as an operator in craniomaxillofacial software. Graphic abstract: [Figure not available: see fulltext.] © 2020, Australasian College of Physical Scientists and Engineers in Medicine.
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