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)

Abstract

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.

Additional material can be found at http://ourpapers.info/miccai10-mri.

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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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