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Part-Based Local Shape Models for Colon Polyp Detection

  • Rahul Bhotika
  • Paulo R. S. Mendonça
  • Saad A. Sirohey
  • Wesley D. Turner
  • Ying-lin Lee
  • Julie M. McCoy
  • Rebecca E. B. Brown
  • James V. Miller
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4191)

Abstract

This paper presents a model-based technique for lesion detection in colon CT scans that uses analytical shape models to map the local shape curvature at individual voxels to anatomical labels. Local intensity profiles and curvature information have been previously used for discriminating between simple geometric shapes such as spherical and cylindrical structures. This paper introduces novel analytical shape models for colon-specific anatomy, viz. folds and polyps, built by combining parts with simpler geometric shapes. The models better approximate the actual shapes of relevant anatomical structures while allowing the application of model-based analysis on the simpler model parts. All parameters are derived from the analytical models, resulting in a simple voxel labeling scheme for classifying individual voxels in a CT volume. The algorithm’s performance is evaluated against expert-determined ground truth on a database of 42 scans and performance is quantified by free-response receiver-operator curves.

Keywords

Principal Curvature Colon Wall Local Shape Virtual Colonoscopy Medical Image Computing 
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

  • Rahul Bhotika
    • 1
  • Paulo R. S. Mendonça
    • 1
  • Saad A. Sirohey
    • 2
  • Wesley D. Turner
    • 3
  • Ying-lin Lee
    • 1
  • Julie M. McCoy
    • 1
  • Rebecca E. B. Brown
    • 1
  • James V. Miller
    • 1
  1. 1.GE Global ResearchNiskayunaUSA
  2. 2.GE HealthcareWaukeshaUSA
  3. 3.Kitware Inc.Clifton ParkUSA

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