Skip to main navigation Skip to search Skip to main content

Automated fuzzy-connectedness-based segmentation in extraction of multiple sclerosis lesions

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

12 Citations (Scopus)

Abstract

In the current study, a fuzzy-connectedness-based approach to fine segmentation of demyelination lesions in Multiple Sclerosis is introduced as an enhancement to the existing 'fast' segmentation method. First a fuzzy connectedness relation is introduced, next a short overview of the 'fast' segmentation method is presented. Finally, a novel, automated segmentation approach is described. The combined method is applied to segmentation of clinical Magnetic Resonance FLAIR Images.

Original languageEnglish
Title of host publicationInformation Technologies in Biomedicine
EditorsEwa Pietka, Jacek Kawa
Pages149-156
Number of pages8
DOIs
Publication statusPublished - 2008

Publication series

NameAdvances in Soft Computing
Volume47
ISSN (Print)1615-3871
ISSN (Electronic)1860-0794

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computational Mechanics
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'Automated fuzzy-connectedness-based segmentation in extraction of multiple sclerosis lesions'. Together they form a unique fingerprint.

Cite this