Dense Surface Reconstruction for Enhanced Navigation in MIS

  • Johannes Totz
  • Peter Mountney
  • Danail Stoyanov
  • Guang-Zhong Yang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6891)

Abstract

Recent introduction of dynamic view expansion has led to the development of computer vision methods for minimally invasive surgery to artificially expand the intra-operative field-of-view of the laparoscope. This provides improved awareness of the surrounding anatomical structures and minimises the effect of disorientation during surgical navigation. It permits the augmentation of live laparoscope images with information from previously captured views. Current approaches, however, can only represent the tissue geometry as planar surfaces or sparse 3D models, thus introducing noticeable visual artefacts in the final rendering results. This paper proposes a high-fidelity tissue geometry mapping by combining a sparse SLAM map with semi-dense surface reconstruction. The method is validated on phantom data with known ground truth, as well as in-vivo data captured during a robotic assisted MIS procedure. The derived results have shown that the method is able to effectively increase the coverage of the expanded surgical view without compromising mapping accuracy.

Keywords

Video Frame Extend Kalman Filter Minimally Invasive Surgery Salient Region Camera Position 
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 2011

Authors and Affiliations

  • Johannes Totz
    • 1
  • Peter Mountney
    • 1
  • Danail Stoyanov
    • 1
  • Guang-Zhong Yang
    • 1
  1. 1.The Hamlyn Centre for Robotic SurgeryImperial CollegeLondonUK

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