A custom grow-cut based scheme for 2D-gel image segmentation

Eirini Kostopoulou, Stamos Katsigiannis, Dimitris Maroulis

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

3 Citations (Scopus)

Abstract

This work introduces a novel method for the detection and segmentation of protein spots in 2D-gel images. A multi-thresholding approach is utilized for the detection of protein spots, while a custom grow-cult algorithm combined with region growing and morphological operators is used for the segmentation process. The experimental evaluation against four state-of-the-art 2D-gel image segmentation algorithms demonstrates the superiority of the proposed approach and indicates that it constitutes an advantageous and reliable solution for 2D-gel image analysis.

Original languageEnglish
Title of host publication37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015
PublisherIEEE
Pages2407-10
Number of pages4
Volume2015
ISBN (Electronic)978-1-4244-9271-8
DOIs
Publication statusPublished - 2015
Externally publishedYes

Publication series

Name
ISSN (Print)1094-687X
ISSN (Electronic)1558-4615

Keywords

  • Algorithms
  • Electrophoresis, Gel, Two-Dimensional
  • Image Processing, Computer-Assisted
  • Proteomics
  • Journal Article
  • Research Support, Non-U.S. Gov't

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  • Cite this

    Kostopoulou, E., Katsigiannis, S., & Maroulis, D. (2015). A custom grow-cut based scheme for 2D-gel image segmentation. In 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2015 (Vol. 2015, pp. 2407-10). IEEE. https://doi.org/10.1109/EMBC.2015.7318879