Collaborative Tracking for MRI-Guided Robotic Intervention on the Beating Heart

  • Y. Zhou
  • E. Yeniaras
  • P. Tsiamyrtzis
  • N. Tsekos
  • I. Pavlidis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6363)


Magnetic Resonance Imaging (MRI)-guided robotic interventions for aortic valve repair promise to dramatically reduce time and cost of operations when compared to endoscopically guided (EG) procedures. A challenging issue is real-time and robust tracking of anatomical landmark points. The interventional tool should be constantly adjusted via a closed feedback control loop to avoid harming these points while valve repair is taking place in the beating heart. A Bayesian network of particle filter trackers proves capable to produce real-time, yet robust behavior. The algorithm is extremely flexible and general - more sophisticated behaviors can be produced by simply increasing the cardinality of the tracking network. Experimental results on 16 MRI cine sequences highlight the promise of the method.

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Bayesian Network Survivor Group Beating Heart Landmark Point Individual Tracker 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Y. Zhou
    • 1
  • E. Yeniaras
    • 1
  • P. Tsiamyrtzis
    • 2
  • N. Tsekos
    • 1
  • I. Pavlidis
    • 1
  1. 1.Department of Computer ScienceUniversity of HoustonHoustonUSA
  2. 2.Department of StatisticsAthens University of EconomicsAthensGreece

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