Entropy based fuzzy classification and detection aid for colorectal polyps

Szilvia Nagy, Ferenc Lilik, L. Kóczy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Colorectal polyps affect a large percentage of the population all over the world, and they can be a basis for more serious conditions such as cancers. As the most reliable method for detecting a polyp in the lower bowel tract is colonoscopy, more and more image processing experiments appear that help to find or characterize such a lesion. The social benefit of such methods is clear, any aid in detecting pre-cancer states saves lives. In the present considerations a fuzzy decision method for finding polyps on a colonoscopy image is presented. As a first step, the image taken during the colonoscopy is cut into tiles of size N by N, thus a rough localization of the lesion within the picture is also possible. The antecedent dimensions consist of statistical characteristics of the colour channels of the tiles, their Renyi entropies, edge density and fitted polynomial coefficients. The method's dependence on the tile-size within the images are also studied, and the success rate increases with the decrease of the tile size between 70 by 70 and 20 by 20 tile sizes.

Original languageEnglish
Title of host publication2017 IEEE AFRICON
Subtitle of host publicationScience, Technology and Innovation for Africa, AFRICON 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages78-82
Number of pages5
ISBN (Electronic)9781538627754
DOIs
Publication statusPublished - Nov 3 2017
EventIEEE AFRICON 2017 - Cape Town, South Africa
Duration: Sep 18 2017Sep 20 2017

Other

OtherIEEE AFRICON 2017
CountrySouth Africa
CityCape Town
Period9/18/179/20/17

Keywords

  • Colorectal polyp detection
  • Entropy
  • Fuzzy classification
  • Stabilized KH interpolation
  • Wavelets

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications

Fingerprint Dive into the research topics of 'Entropy based fuzzy classification and detection aid for colorectal polyps'. Together they form a unique fingerprint.

  • Cite this

    Nagy, S., Lilik, F., & Kóczy, L. (2017). Entropy based fuzzy classification and detection aid for colorectal polyps. In 2017 IEEE AFRICON: Science, Technology and Innovation for Africa, AFRICON 2017 (pp. 78-82). [8095459] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AFRCON.2017.8095459