Medical Engineering & Physics
Volume 32, Issue 2 , Pages 174-188, March 2010

Cardiac flow component analysis

  • Kelvin K.L. Wong

      Affiliations

    • School of Aerospace, Mechanical & Manufacturing Engineering, RMIT University, PO Box 71, Bundoora, VIC 3083, Australia
    • Center for Biomedical Engineering and School of Electrical & Electronics Engineering, University of Adelaide, SA 5005, Australia
    • Corresponding Author InformationCorresponding author at: School of Aerospace, Mechanical & Manufacturing Engineering, RMIT University, PO Box 71, Bundoora, VIC 3083, Australia. Tel.: +61 03 9925 6164.
  • ,
  • Jiyuan Tu

      Affiliations

    • School of Aerospace, Mechanical & Manufacturing Engineering, RMIT University, PO Box 71, Bundoora, VIC 3083, Australia
  • ,
  • Richard M. Kelso

      Affiliations

    • School of Mechanical Engineering, University of Adelaide, SA 5005, Australia
  • ,
  • Stephen G. Worthley

      Affiliations

    • School of Medicine, University of Adelaide, and Department of Cardiology, Royal Adelaide Hospital, SA 5005, Australia
  • ,
  • Prashanthan Sanders

      Affiliations

    • School of Medicine, University of Adelaide, and Department of Cardiology, Royal Adelaide Hospital, SA 5005, Australia
  • ,
  • Jagannath Mazumdar

      Affiliations

    • Center for Biomedical Engineering and School of Electrical & Electronics Engineering, University of Adelaide, SA 5005, Australia
  • ,
  • Derek Abbott

      Affiliations

    • Center for Biomedical Engineering and School of Electrical & Electronics Engineering, University of Adelaide, SA 5005, Australia

Received 26 February 2009; received in revised form 19 November 2009; accepted 22 November 2009. published online 21 December 2009.

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 The authors developed and use a medical image processing software named Medflovan to produce the results displayed in this paper. This is a system entirely created using the C++ object-oriented programming platform to provide cardiac flow visualization and analysis. Cardiac flow computation and visualization is performed on a Pentium 4-class processor on a dedicated graphics card with 512MB of memory.

PII: S1350-4533(09)00249-5

doi:10.1016/j.medengphy.2009.11.007

Medical Engineering & Physics
Volume 32, Issue 2 , Pages 174-188, March 2010