Computerized Medical Imaging and Graphics
Volume 32, Issue 1 , Pages 67-77, January 2008

CT-perfusion imaging of the human brain: Advanced deconvolution analysis using circulant singular value decomposition

  • H.-J. Wittsack

      Affiliations

    • Institute of Diagnostic Radiology, University of Duesseldorf, Moorenstrasse 5, 40225 Duesseldorf, Germany
    • Brain Imaging Center West, Research Center Jülich, 52425 Jülich, Germany
    • Corresponding Author InformationCorresponding author at: Institute of Diagnostic Radiology, University of Duesseldorf, Moorenstrasse 5, D-40225 Duesseldorf, Germany. Tel.: +49 211 8117356; fax: +49 211 8116299.
    • ,
  • A.M. Wohlschläger

      Affiliations

    • Department of Neurology, Nuclear Medicine, Neuroradiology, TU Munich, Möhlstrasse 28, 81675 Munich, Germany
    • ,
  • E.K. Ritzl

      Affiliations

    • Department of Neurology, Johns Hopkins University, School of Medicine, 600 N. Wolfe Street, Baltimore, MD 21287, USA
    • ,
  • R. Kleiser

      Affiliations

    • Institute of Neuroradiology, UniversitätsSpital Zürich, Frauenklinikstrasse 10, 8091 Zürich, Switzerland
    • ,
  • M. Cohnen

      Affiliations

    • Institute of Diagnostic Radiology, University of Duesseldorf, Moorenstrasse 5, 40225 Duesseldorf, Germany
    • ,
  • R.J. Seitz

      Affiliations

    • Brain Imaging Center West, Research Center Jülich, 52425 Jülich, Germany
    • Department of Neurology, Universität Düsseldorf, Moorenstrasse 5, 40225 Düsseldorf, Germany
    • ,
  • U. Mödder

      Affiliations

    • Institute of Diagnostic Radiology, University of Duesseldorf, Moorenstrasse 5, 40225 Duesseldorf, Germany

Received 15 August 2006; received in revised form 24 September 2007; accepted 25 September 2007.

Abstract 

According to indicator dilution theory tissue time–concentration curves have to be deconvolved with arterial input curves in order to get valid perfusion results. Our aim was to adapt and validate a deconvolution method originating from magnetic resonance techniques and apply it to the calculation of dynamic contrast enhanced computed tomography perfusion imaging. The application of a block-circulant matrix approach for singular value decomposition renders the analysis independent of tracer arrival time to improve the results.

Keywords: Computed tomography, Perfusion, Deconvolution, Brain

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PII: S0895-6111(07)00137-1

doi:10.1016/j.compmedimag.2007.09.004

Computerized Medical Imaging and Graphics
Volume 32, Issue 1 , Pages 67-77, January 2008

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