• DocumentCode
    1653686
  • Title

    Automated dental arch detection using computed tomography images

  • Author

    Chanwimaluang, Thitiporn ; Sotthivirat, Saowapak ; Sinthupinyo, Wasin

  • Author_Institution
    Nat. Electron. & Comput. Technol. Center, Pathumthani
  • fYear
    2008
  • Firstpage
    737
  • Lastpage
    740
  • Abstract
    The dental arch detection from an x-ray computed tomography (CT) image is an important feature in generating panoramic images as well as in rearranging teeth in orthodontics. This paper introduces an automated approach in dental arch detection. Because teeth have higher intensities than their surrounding area, local entropy thresholding technique is employed to binarize a dental CT image. Next, we use connected component labeling to partially remove metal artifacts. Then, morphological dilation is applied to close the interstices between teeth so the maxilla/mandible region is connected into one piece. After that, morphological thinning operation is used to thin the binary maxilla/mandible region. The thinning result is a rough shape of dental arch. Lastly, we exploit the thinning result in curve fitting method to get a mathematically represented dental arch. We tested our algorithm on the total of 60 dental CT images which are taken from 6 different data sets (ten images per data set). Simulation results demonstrate satisfactory outcomes.
  • Keywords
    computerised tomography; dentistry; X-ray computed tomography image; automated dental arch detection; binary maxilla/mandible region; component labeling; curve fitting method; dental computed tomography images; entropy thresholding; metal artifacts; morphological dilation; morphological thinning operation; orthodontics; panoramic images; teeth rearrangement; Computed tomography; Dentistry; Entropy; Image generation; Labeling; Shape; Teeth; X-ray detection; X-ray detectors; X-ray imaging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing, 2008. ICSP 2008. 9th International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-2178-7
  • Electronic_ISBN
    978-1-4244-2179-4
  • Type

    conf

  • DOI
    10.1109/ICOSP.2008.4697235
  • Filename
    4697235