Convex analysis and separation of composite signals in DCE-MRI

Li Chen, Tsung Han Chan, Peter L. Choyke, Chong Yung Chi, Ge Wang, Yue Wang

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

Abstract

Dynamic functional imaging promises powerful tools for the visualization and elucidation of important disease-causing biological processes, where the pixels often represent a composite of multiple biomarkers independent of spatial resolution. This study exploits both blind source separation and imagery marker characteristics to develop a hybrid method for the separation of mixed yet correlated biomarker distributions in DCE-MRI. A compartment latent variable model is constructed upon which a novel convex analysis framework is proposed to provide a close-form algebraic solution to separating composite markers with non-negativity and well-grounded points. A unique non-negative clustered component analysis is further developed to explicitly consider both partial volume effect and noise contamination. Experimental results show promising and robust extraction of time activity curves and vascular marker images in agreement with biomedical expectations.

Original languageEnglish (US)
Title of host publication2008 5th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, Proceedings, ISBI
Pages1557-1560
Number of pages4
DOIs
StatePublished - 2008
Event2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI - Paris, France
Duration: May 14 2008May 17 2008

Publication series

Name2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI

Other

Other2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI
Country/TerritoryFrance
CityParis
Period5/14/085/17/08

Keywords

  • Blind source separation
  • Compartment model
  • Convex analysis
  • Dynamic contrast-enhanced magnetic resonance imaging
  • Tumor angiogenesis

ASJC Scopus subject areas

  • Biomedical Engineering

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