The effect of wavelet analyis on entropy based fuzzy classification of colonoscopy images

Szilvia Nagy, Brigita Sziova, L. Kóczy

Research output: Contribution to conferencePaper

Abstract

Colorectal polyp detection is important in preventing cancer. Structural entropy can detect different structures of distributions, such as image pixel brightness. Wavelet analysis can help in separating large-scale and fine resolution behaviour. In the method presented in this paper, the colonoscopy images are separated into segments, and a classification scheme is built in order to determine, whether there is a polyp part in the image segment or not. Without wavelet analysis edge density and structural entropy can be a basis of fuzzy classification for the polyp content of only good quality colonoscopy images, and still has about 10 percent false classification. In this contribution the effect of wavelet analysis on the classification scheme is studied.

Original languageEnglish
Publication statusPublished - Jan 1 2017
Event5th International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2017 - Beijing, China
Duration: Nov 2 2017Nov 5 2017

Other

Other5th International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2017
CountryChina
CityBeijing
Period11/2/1711/5/17

Keywords

  • Colonoscopy
  • Entropy
  • Fuzzy logic
  • Image processing
  • Wavelets

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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  • Cite this

    Nagy, S., Sziova, B., & Kóczy, L. (2017). The effect of wavelet analyis on entropy based fuzzy classification of colonoscopy images. Paper presented at 5th International Workshop on Advanced Computational Intelligence and Intelligent Informatics, IWACIII 2017, Beijing, China.