• DocumentCode
    1721126
  • Title

    Mean Shape Models for Polyp Detection in CT Colonography

  • Author

    Ong, Ju Lynn ; Seghouane, Abd-Krim ; Osborn, Kevin

  • Author_Institution
    RSISE, Australian Nat. Univ., Canberra, ACT
  • fYear
    2008
  • Firstpage
    287
  • Lastpage
    293
  • Abstract
    A global representation of polyp and non polyp shapes are constructed following a point distribution model (PDM) as an alternative to current methods which only inspect local shape characteristics at a point on the surface. The decision on whether or not a candidate lesion is a polyp can then be made by comparing the minimum Euclidean distance of the candidate lesion to the constructed mean shapes. The model closer in distance to the candidate lesion is selected to represent that particular lesion - polyp or non polyp. This shape model can also be used to investigate the shape variability of the different lesions detected by constructing an allowable shape domain for each of these lesions.
  • Keywords
    computerised tomography; CT colonography; Euclidean distance; candidate lesion; computerised tomography; global representation; mean shape models; point distribution model; polyp detection; shape domain; shape variability; Australia; Cancer; Colon; Colonic polyps; Computed tomography; Distributed computing; Lesions; Shape measurement; Surface fitting; Virtual colonoscopy;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Digital Image Computing: Techniques and Applications (DICTA), 2008
  • Conference_Location
    Canberra, ACT
  • Print_ISBN
    978-0-7695-3456-5
  • Type

    conf

  • DOI
    10.1109/DICTA.2008.9
  • Filename
    4700033