Automatic Polyp Detection Using Global Geometric Constraints and Local Intensity Variation Patterns

  • Nima Tajbakhsh
  • Suryakanth R. Gurudu
  • Jianming Liang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8674)


This paper presents a new method for detecting polyps in colonoscopy. Its novelty lies in integrating the global geometric constraints of polyps with the local patterns of intensity variation across polyp boundaries: the former drives the detector towards the objects with curvy boundaries, while the latter minimizes the misleading effects of polyp-like structures. This paper makes three original contributions: (1) a fast and discriminative patch descriptor for precisely characterizing patterns of intensity variation across boundaries, (2) a new 2-stage classification scheme for accurately excluding non-polyp edges from an overcomplete edge map, and (3) a novel voting scheme for robustly localizing polyps from the retained edges. Evaluations on a public database and our own videos demonstrate that our method is promising and outperforms the state-of-the-art methods.


Optical colonoscopy polyp detection boundary classification edge voting 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Nima Tajbakhsh
    • 1
  • Suryakanth R. Gurudu
    • 2
  • Jianming Liang
    • 1
  1. 1.Department of Biomedical InformaticsArizona State UniversityScottsdaleUSA
  2. 2.Division of Gastroenterology and HepatologyMayo ClinicScottsdaleUSA

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