• DocumentCode
    1653579
  • Title

    Bio-Information Based Segmentation of 3D Dental Models

  • Author

    Yuan Tian-ran ; Dai Ning ; Hao Guo-dong ; Cheng Xiao-Sheng ; Cui Hai-hua ; Liao Wen-he ; Yu Qing ; Lv Peijun

  • Author_Institution
    Coll. of Mech. & Electr. Eng., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing
  • fYear
    2008
  • Firstpage
    624
  • Lastpage
    627
  • Abstract
    The automatic and accurate segmentation of 3-D dental model digitized through intra or extra oral measurement methods is an important step in computer aided orthodontic system. This paper presents a robust segmentation method based on the bio-information of individual\´s teeth with little manual interaction. The discrete curvature of the dental model is first computed; using the computed discrete curvature as the reference, and then the feature regions in which the segmentation boundary may be included is filtered out according given curvature threshold. The feature regions including segmentation boundary are "bridged" interactively. The skeleton of the feature regions is extracted according to the bio- information of the dental model, and the segmentation boundary is got after branches removing. Finally, the teeth of the dental model are separated one by one along the segmentation boundary.
  • Keywords
    computer aided analysis; dentistry; feature extraction; image segmentation; medical image processing; 3D dental models; bio-information based segmentation; computer aided orthodontic system; discrete curvature; extraoral measurement; feature regions extracting; intraoral measurement; robust segmentation method; segmentation boundary; Computer aided manufacturing; Dentistry; Educational institutions; Extraterrestrial measurements; Feature extraction; Image edge detection; Image segmentation; Robustness; Skeleton; Teeth;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-1747-6
  • Electronic_ISBN
    978-1-4244-1748-3
  • Type

    conf

  • DOI
    10.1109/ICBBE.2008.152
  • Filename
    4535032