title: Influence of CBCT parameters on the output of an automatic edge-detection-based endodontic segmentation.
abstract: OBJECTIVE
  To determine the optimal CBCT settings for an automatic edge-detection-based endodontic segmentation procedure by assessing the accuracy of the root canal measurements.
  
  
  METHODS
  12 intact teeth with closed apexes were cut perpendicular to the root axis, at pre-determined levels to the reference plane (the first section made before acquisition). Acquisitions of each specimen were performed with Kodak 9000(®) 3D (76 µm, 14 bits; Kodak Carestream Health, Trophy, France) by using different combinations of milliamperes and kilovolts. Three-dimensional images were displayed and root canals were segmented with the MeVisLab software (edge-detection-based method; MeVis Research, Bremen, Germany). Histological root canal sections were then digitized with a 0.5- to 1.0-µm resolution and compared with equivalent two-dimensional cone-beam reconstructions for each pair of settings using the Pearson correlation coefficient, regression analysis and Bland-Altman method for the canal area and Feret's diameter. After a ranking process, a Wilcoxon paired test was carried out to compare the pair of settings.
  
  
  RESULTS
  The best pair of acquisition settings was 3.2 mA/60 kV. Significant differences were found between 3.2 mA/60 kV and other settings (p < 0.05) for the root canal area and for Feret's diameter.
  
  
  CONCLUSIONS
  The quantitative analyses of the root canal system with the edge-detection-based method could depend on acquisition parameters. Improvements in segmentation still need to be carried out to ensure the quality of the reconstructions when we have to deal with closer outlines and because of the low spatial resolution.
authors.affiliation: 1 Faculté de Chirurgie Dentaire, Université Paul Sabatier, Centre Hospitalier Universitaire, Toulouse, France.|2 Laboratoire INSERM, Imagerie Cérébrale et Handicaps Neurologiques UMR 825, Centre Hospitalier Universitaire, Toulouse, France.
authors.forename: J
authors.initials: J
authors.lastname: Michetti
authors.affiliation: 1 Faculté de Chirurgie Dentaire, Université Paul Sabatier, Centre Hospitalier Universitaire, Toulouse, France.|3 Laboratoire des Déficiences, Incapacités et Désavantages en Santé Orale, EA4847, Université d'Auvergne, Clermont-Ferrand, France.
authors.forename: M
authors.initials: M
authors.lastname: Georgelin-Gurgel
authors.affiliation: 1 Faculté de Chirurgie Dentaire, Université Paul Sabatier, Centre Hospitalier Universitaire, Toulouse, France.
authors.forename: J-P
authors.initials: JP
authors.lastname: Mallet
authors.affiliation: 1 Faculté de Chirurgie Dentaire, Université Paul Sabatier, Centre Hospitalier Universitaire, Toulouse, France.|4 Group SUMO, Institut Clément Ader, Toulouse, France.
authors.forename: F
authors.initials: F
authors.lastname: Diemer
authors.affiliation: 2 Laboratoire INSERM, Imagerie Cérébrale et Handicaps Neurologiques UMR 825, Centre Hospitalier Universitaire, Toulouse, France.
authors.forename: K
authors.initials: K
authors.lastname: Boulanouar
mesh_terms: D001641:Bicuspid / Q000000981:diagnostic imaging; D054893:Cone-Beam Computed Tomography / Q000379:methods*; D003481:Cuspid / Q000000981:diagnostic imaging; D003786:Dental Pulp Cavity / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D007180:Incisor / Q000000981:diagnostic imaging; D008963:Molar / Q000000981:diagnostic imaging; D009811:Odontometry / Q000379:methods; D019252:Radiography, Dental, Digital / Q000379:methods; D015203:Reproducibility of Results; D019227:Tooth Apex / Q000000981:diagnostic imaging
keywords: cone-beam computed tomography; endodontics; image processing; radiographic image enhancement; root canal