Targeting Accuracy under Model-to-Subject Misalignments in Model-Guided Cardiac Surgery

  • Cristian A. Linte
  • John Moore
  • Andrew D. Wiles
  • Chris Wedlake
  • Terry M. Peters
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5761)


In image-guided interventions, anatomical models of organs are often generated from pre-operative images and further employed in planning and guiding therapeutic procedures. However, the accuracy of these models, along with their registration to the subject are crucial for successful therapy delivery. These factors are amplified when manipulating soft tissue undergoing large deformations, such as the heart. When used in guiding beating-heart procedures, pre-operative models may not be sufficient for guidance and they are often complemented with real-time, intra-operative cardiac imaging. Here we demonstrate via in vitro endocardial “therapy” that ultrasound-enhanced model-guided navigation provides sufficient guidance to preserve a clinically-desired targeting accuracy of under 3 mm independently of the model-to-subject misregistrations. These results emphasize the direct benefit of integrating real-time imaging within intra-operative visualization environments considering that model-to-subject misalignments are often encountered clinically.


Augmented Reality Therapy Delivery Iterative Close Point Beating Heart Virtual Model 
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 2009

Authors and Affiliations

  • Cristian A. Linte
    • 1
  • John Moore
    • 1
  • Andrew D. Wiles
    • 1
  • Chris Wedlake
    • 1
  • Terry M. Peters
    • 1
  1. 1.Imaging Research Laboratories, Robarts Research Institute, Biomedical Engineering Graduate Program, Department of Medical BiophysicsUniversity of Western OntarioLondonCanada

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