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Detection of Protrusions in Curved Folded Surfaces Applied to Automated Polyp Detection in CT Colonography

  • Cees van Wijk
  • Vincent F. van Ravesteijn
  • Frank M. Vos
  • Roel Truyen
  • Ayso H. de Vries
  • Jaap Stoker
  • Lucas J. van Vliet
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)

Abstract

Over the past years many computer aided diagnosis (CAD) schemes have been presented for the detection of colonic polyps in CT Colonography. The vast majority of these methods (implicitly) model polyps as approximately spherical protrusions. Polyp shape and size varies greatly, however and is often far from spherical. We propose a shape and size invariant method to detect suspicious regions. The method works by locally deforming the colon surface until the second principal curvature is smaller than or equal to zero. The amount of deformation is a quantitative measure of the ’protrudeness’. The deformation field allows for the computation of various additional features to be used in supervised pattern recognition. It is shown how only a few features are needed to achieve 95% sensitivity at 10 false positives (FP) per dataset for polyps larger than 6 mm.

Keywords

Principal Curvature Shape Index Colon Wall High Posterior Probability Candidate Object 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Cees van Wijk
    • 1
  • Vincent F. van Ravesteijn
    • 1
    • 2
  • Frank M. Vos
    • 1
    • 3
  • Roel Truyen
    • 2
  • Ayso H. de Vries
    • 3
  • Jaap Stoker
    • 3
  • Lucas J. van Vliet
    • 1
  1. 1.Quantitative Imaging GroupDelft University of TechnologyThe Netherlands
  2. 2.Philips Medical SystemsBestThe Netherlands
  3. 3.Department of RadiologyAcademic Medical CenterAmsterdamThe Netherlands

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