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i-BRUSH: A Gaze-Contingent Virtual Paintbrush for Dense 3D Reconstruction in Robotic Assisted Surgery

  • Marco Visentini-Scarzanella
  • George P. Mylonas
  • Danail Stoyanov
  • Guang-Zhong Yang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5761)

Abstract

With increasing demand on intra-operative navigation and motion compensation during robotic assisted minimally invasive surgery, real-time 3D deformation recovery remains a central problem. Currently the majority of existing methods rely on salient features, where the inherent paucity of distinctive landmarks implies either a semi-dense reconstruction or the use of strong geometrical constraints. In this study, we propose a gaze-contingent depth reconstruction scheme by integrating human perception with semi-dense stereo and p-q based shading information. Depth inference is carried out in real-time through a novel application of Bayesian chains without smoothness priors. The practical value of the scheme is highlighted by detailed validation using a beating heart phantom model with known geometry to verify the performance of gaze-contingent 3D surface reconstruction and deformation recovery.

Keywords

Left Anterior Descend Motion Compensation Stereo Reconstruction Depth Recovery Deformation Recovery 
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

  • Marco Visentini-Scarzanella
    • 1
  • George P. Mylonas
    • 1
    • 2
  • Danail Stoyanov
    • 2
  • Guang-Zhong Yang
    • 1
    • 2
  1. 1.Royal Society/Wolfson Foundation MIC LaboratoryUK
  2. 2.Institute of Biomedical EngineeringImperial College LondonLondonUnited Kingdom

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