title: Accuracy of software designed for automated localization of the inferior alveolar nerve canal on cone beam CT images.
abstract: OBJECTIVE
  The aim of this study was to design and evaluate a new method for automated localization of the inferior alveolar nerve canal on CBCT images.
  
  
  METHODS
  The proposed method is based on traversing both panoramic and cross-sectional slices. For the panoramic slices, morphological skeletonization is imposed, and a modified Hough transform is used while traversing the cross-sectional slices. A total of 40 CBCT images were randomly selected. Two experts twice located the inferior alveolar nerve canal during two examinations set 6 weeks apart. Agreement between experts was achieved, and the result of this manual technique was considered the gold standard for our study. The distances for the automated method and those determined using the gold standard method were calculated and recorded. The mean time required for the automated detection was also recorded.
  
  
  RESULTS
  The average mean distance error from the baseline was 0.75 ± 0.34 mm. In all, 86% of the detected points had a mean error of <1 mm compared with those determined by the manual gold standard method.
  
  
  CONCLUSIONS
  The proposed method is far more accurate and faster than previous methods. It also provides more accuracy than human annotation within a shorter time.
authors.affiliation: 1 Department of Oral and Maxillofacial Radiology, School of Dentistry, Kermanshah University of Medical Sciences, Kermanshah, Iran.
authors.forename: Ehsan
authors.initials: E
authors.lastname: Bahrampour
authors.affiliation: 2 Department of Medical Physics and Biomedical Engineering, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
authors.forename: Ali
authors.initials: A
authors.lastname: Zamani
authors.affiliation: 3 School of Dentistry, Kermanshah University of Medical Sciences, Kermanshah, Iran.
authors.forename: Sadegh
authors.initials: S
authors.lastname: Kashkouli
authors.affiliation: 4 Department of Pediatric Dentistry, School of Dentistry, Kermanshah University of Medical Sciences, Kermanshah, Iran.
authors.forename: Elham
authors.initials: E
authors.lastname: Soltanimehr
authors.affiliation: 2 Department of Medical Physics and Biomedical Engineering, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
authors.forename: Mohsen
authors.initials: M
authors.lastname: Ghofrani Jahromi
authors.affiliation: 2 Department of Medical Physics and Biomedical Engineering, School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
authors.forename: Zahra
authors.initials: Z
authors.lastname: Sanaeian Pourshirazi
mesh_terms: D000465:Algorithms; D019412:Anatomy, Cross-Sectional / Q000706:statistics & numerical data; D054893:Cone-Beam Computed Tomography / Q000706:statistics & numerical data*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data*; D021621:Imaging, Three-Dimensional / Q000706:statistics & numerical data; D008340:Mandibular Nerve / Q000000981:diagnostic imaging*; D011862:Radiography, Panoramic / Q000706:statistics & numerical data; D012984:Software / Q000706:statistics & numerical data*; D012985:Software Design
keywords: CBCT; automatic detection; inferior alveolar nerve canal