• DocumentCode
    3073773
  • Title

    Edge cross-section features for detection of appendiceal orifice appearance in colonoscopy videos

  • Author

    Wang, Yi ; Tavanapong, Wallapak ; Wong, Johnny ; Oh, JungHwan ; De Groen, Piet C.

  • Author_Institution
    Department of Computer Science, Iowa State University, Ames, 50011, USA
  • fYear
    2008
  • fDate
    20-25 Aug. 2008
  • Firstpage
    3000
  • Lastpage
    3003
  • Abstract
    Colonoscopy is an endoscopic technique that allows a physician to inspect the inside of the human colon. The appearance of the appendiceal orifice during colonoscopy indicates a complete traversal of the colon, which is one of important quality indicators of examination of the colon. In this paper, we propose a new algorithm that detects appendix images—images showing the appendiceal orifice. We introduce new features based on geometric shape, saturation and intensity changes along the norm direction (cross-section) of an edge to discriminate appendix images. Our experimental results on real colonoscopic images show the average sensitivity and specificity of 88.12% and 94.25%, respectively.
  • Keywords
    Cancer; Colon; Colonoscopy; Computer vision; Endoscopes; Guidelines; Image edge detection; Orifices; Shape; Videos; Algorithms; Appendix; Artificial Intelligence; Bayes Theorem; Colon; Colonoscopy; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Models, Statistical; Pattern Recognition, Automated; Reproducibility of Results; Surgery, Computer-Assisted; Video Recording;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE
  • Conference_Location
    Vancouver, BC
  • ISSN
    1557-170X
  • Print_ISBN
    978-1-4244-1814-5
  • Electronic_ISBN
    1557-170X
  • Type

    conf

  • DOI
    10.1109/IEMBS.2008.4649834
  • Filename
    4649834