Polyp Detection in Endoscopic Video Using SVMs

  • Luís A. Alexandre
  • João Casteleiro
  • Nuno Nobreinst
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4702)


Colon cancer is one of the most common cancers in developed countries. Most of these cancers start with a polyp. Polyps are easily detected by physicians. Our goal is to mimic this detection ability so that endoscopic videos can be pre-scanned with our algorithm before the physician analyses them. The method will indicate which part of the video needs attention (polyps were detected there) and hence can speedup the procedures. In this paper we present a method for polyp detection in endoscopic images that uses SVM for classification. Our experiments yielded a result of 93.16 ± 0.09% of area under the Receiver Operating Characteristic (ROC) curve on a database of 4620 images indicating that the approach proposed is well suited to the detection of polyps in endoscopic video.


Feature Extraction Original Image Receiver Operating Characteristic Curve Local Binary Pattern Endoscopic Image 
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 2007

Authors and Affiliations

  • Luís A. Alexandre
    • 1
    • 2
  • João Casteleiro
    • 1
  • Nuno Nobreinst
    • 1
  1. 1.Department of Informatics, Univ. Beira InteriorPortugal
  2. 2.IT - Networks and Multimedia Group, CovilhãPortugal

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