Polyps Flagging in Virtual Colonoscopy

  • Marcelo Fiori
  • Pablo Musé
  • Guillermo Sapiro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8259)

Abstract

Computer tomographic colonography, combined with computer-aided detection, is a promising emerging technique for colonic polyp analysis. We present a complete pipeline for polyp detection, starting with a simple colon segmentation technique that enhances polyps, followed by an adaptive-scale candidate polyp delineation and classification based on new texture and geometric features that consider both the information in the candidate polyp and its immediate surrounding area. The proposed system is tested with ground truth data, including challenging flat and small polyps. For polyps larger than 6mm in size we achieve 100% sensitivity with just 0.9 false positives per case, and for polyps larger than 3mm in size we achieve 93% sensitivity with 2.8 false positives per case.

Keywords

Texture Feature Shape Index Virtual Colonoscopy Optical Colonoscopy Polyp Detection 
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 2013

Authors and Affiliations

  • Marcelo Fiori
    • 1
  • Pablo Musé
    • 1
  • Guillermo Sapiro
    • 2
  1. 1.Universidad de la RepúblicaUruguay
  2. 2.Duke UniversityDurhamUSA

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