• DocumentCode
    2153953
  • Title

    Asymmetric Affinity in Fuzzy Connectedness Segmentation for Oral Contrast-Enhances CT Colonography

  • Author

    Franaszek, Marek ; Summers, Ronald M.

  • Author_Institution
    Warren Grant Magnuson Clinical Center, Nat. Inst. of Health, Bethesda, MD
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    419
  • Lastpage
    423
  • Abstract
    In oral contrast-enhanced CT colonography, patients are given barium- or iodine-containing solutions to drink to tag out remnants of stool and residual fluid in the colon. Frequently, residual fecal matter absorbs more tagging material and appears much brighter on CT images than surrounding opacified fluid. This may cause even advanced segmentation procedures, like fuzzy connectedness, to miss local regions of colonic lumen. This in turn leads to spurious deformations of the reconstructed colonic wall and impairs interpretation. We show that these problems may be avoided when the properly designed asymmetric affinities are used for segmenting air- and fluid-filled parts of the colon. After this improvement, the segmented volume does not contain holes of missed regions and resulting colonic surface is smooth and free from undesired distortion
  • Keywords
    computerised tomography; fuzzy set theory; image segmentation; medical image processing; asymmetric affinity; colonic lumen; colonic wall; fuzzy connectedness segmentation; opacified fluid; oral contrast-enhanced CT colonography; residual fecal matter; spurious deformations; tagging material; Colon; Colonic polyps; Colonography; Computed tomography; Fuzzy systems; Histograms; Image reconstruction; Image segmentation; Tagging; Virtual colonoscopy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer-Based Medical Systems, 2006. CBMS 2006. 19th IEEE International Symposium on
  • Conference_Location
    Salt Lake City, UT
  • ISSN
    1063-7125
  • Print_ISBN
    0-7695-2517-1
  • Type

    conf

  • DOI
    10.1109/CBMS.2006.49
  • Filename
    1647606