• DocumentCode
    501720
  • Title

    Automated Thickness Measurements of Pearl from Optical Coherence Tomography Images

  • Author

    Lei, Ming ; Sun, Yankui ; Wang, Daoshun ; Li, Peng

  • Author_Institution
    Dept. of Comput. Sci. & Technol., Tsinghua Univ., Beijing, China
  • Volume
    1
  • fYear
    2009
  • fDate
    12-14 Aug. 2009
  • Firstpage
    247
  • Lastpage
    251
  • Abstract
    In this paper, we explored the automatic thickness measurements of pearl from optical coherence tomography (OCT) images. We used a two stage scheme to extract the upper and lower boundaries of nacre respectively, and computed the thickness of nacre based on the extracted upper and lower boundaries. At the first stage, we employed edge detection method to extract the upper boundary. At the following stage, we used pixel classification method to detect the lower boundary. In both stages, boundary refinement and fitting were conducted. The proposed approach is evaluated using pearl optical coherence tomography images, and achieved high segmentation accuracy of 93.56% and relative measurement error of 1.69%. Experimental results demonstrate the effectiveness and robustness of our method.
  • Keywords
    edge detection; image classification; medical image processing; optical tomography; thickness measurement; automated thickness measurements; boundary refinement; edge detection method; pearl optical coherence tomography images; pixel classification method; Biomedical measurements; Biomedical optical imaging; High-resolution imaging; Image edge detection; Nonlinear optics; Optical imaging; Optical scattering; Thickness measurement; Tomography; Ultrasonic imaging; Support vector machine; boundary fitting; nonlinear complex diffusion; optical coherence tomography; pearl;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Hybrid Intelligent Systems, 2009. HIS '09. Ninth International Conference on
  • Conference_Location
    Shenyang
  • Print_ISBN
    978-0-7695-3745-0
  • Type

    conf

  • DOI
    10.1109/HIS.2009.56
  • Filename
    5254320