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Dynamic Guidance for Robotic Surgery Using Image-Constrained Biomechanical Models

  • Philip Pratt
  • Danail Stoyanov
  • Marco Visentini-Scarzanella
  • Guang-Zhong Yang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6361)

Abstract

The use of physically-based models combined with image constraints for intraoperative guidance is important for surgical procedures that involve large-scale tissue deformation. A biomechanical model of tissue deformation is described in which surface positional constraints and internally generated forces are derived from endoscopic images and preoperative 4D CT data, respectively. Considering cardiac motion, a novel technique is presented which minimises the average registration error over one or more complete cycles. Features tracked in the stereo video stream provide surface constraints, and an inverse finite element simulation is presented which allows internal forces to be recovered from known preoperative displacements. The accuracy of surface texture, segmented mesh and volumetrically rendered overlays is evaluated with detailed phantom experiments. Results indicate that by combining preoperative and intraoperative images in this manner, accurate intraoperative tissue deformation modelling can be achieved.

Keywords

Augmented Reality Video Frame Robotic Surgery Partial Nephrectomy Laparoscopic Partial Nephrectomy 
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 2010

Authors and Affiliations

  • Philip Pratt
    • 1
  • Danail Stoyanov
    • 1
  • Marco Visentini-Scarzanella
    • 1
  • Guang-Zhong Yang
    • 1
  1. 1.Institute of Biomedical Engineering Imperial College of Science, Technology and MedicineLondonUK

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