Brain MR perfusion image segmentation using independent component analysis and hierarchical clustering

Chia Fung Lu, Yen Chun Chou, Wan Yuo Guo, Yu Te Wu

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

3 Citations (Scopus)

Abstract

Extraction of various perfusion components from dynamic-susceptibility- contrast (DSC) MR brain images is critical for the analysis of brain perfusion. According to the variation of temporal signal on different brain tissues, one can segment whole brain area into distinct blood supply patterns which are vital for the profound analysis of cerebral hemodynamics. In this study, independent component analysis (ICA) is used to project the perfusion image data into independent components from which each elucidated tissue cluster can be automatically segment out by using the hierarchical clustering (HC). Five normal subjects and a case of internal carotid artery stenosis subjects were analyzed. The results demonstrated that ICA-HC is effective in multi-tissue hemodynamic classification which improves differentiation of pathological and physiological hemodynamics.

Original languageEnglish
Title of host publication29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
Pages5547-5550
Number of pages4
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07 - Lyon, France
Duration: Aug 23 2007Aug 26 2007

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
ISSN (Print)0589-1019

Conference

Conference29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
Country/TerritoryFrance
CityLyon
Period8/23/078/26/07

ASJC Scopus subject areas

  • Biomedical Engineering

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