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Virtual Space Editing of Tagged MRI Heart Data

  • Luis Serra
  • Tim Poston
  • Ng Hem
  • Heng Pheng Ann
  • Chua Beng Choon
Part of the Lecture Notes in Computer Science book series (LNCS, volume 905)

Abstract

To estimate local contraction from tagged MRI heartbeat images, and deduce the presence of non-contributing muscle (usually ischemic), it is necessary to map the heart contours accurately in each slice at each imaged time. Neither an algorithm nor a human has been found able to do this on the evidence contained in a single slice; machine estimates must be corrected by humans, using criteria of 4D (space and time) consistency. This has taken a full working day per heartbeat, using only a 2D interface; in our Virtual Workbench environment for dextrous ‘reach-in’ work in virtual spaces, this time is reduced to less than an hour, making it practical to analyze larger numbers of cases.

Keywords

Control Point Magnetic Resonance Image Data Heart Motion Simulator Sickness Magnetic Resonance Image Slice 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Luis Serra
    • 1
  • Tim Poston
    • 1
  • Ng Hem
    • 1
  • Heng Pheng Ann
    • 1
  • Chua Beng Choon
    • 1
  1. 1.Centre for Information-Enhanced Medicine Institute of Systems ScienceNational University of SingaporeSingapore

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