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Dense 3D Depth Recovery for Soft Tissue Deformation During Robotically Assisted Laparoscopic Surgery

  • Danail Stoyanov
  • Ara Darzi
  • Guang Zhong Yang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3217)

Abstract

Recovering tissue deformation during robotic assisted minimally invasive surgery is an important step towards motion compensation and stabilization. This paper presents a practical strategy for dense 3D depth recovery and temporal motion tracking for deformable surfaces. The method combines image rectification with constrained disparity registration for reliable depth estimation. The accuracy and practical value of the technique is validated with a tissue phantom with known 3D geometry and motion characteristics. It has been shown that the performance of the proposed approach compares favorably against existing methods. Example results of the technique applied to in vivo robotic assisted minimally invasive surgery data are also provided.

Keywords

Minimally Invasive Surgery Stereo Camera Normalize Cross Correlation Deformable Surface Stereo Image Pair 
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 2004

Authors and Affiliations

  • Danail Stoyanov
    • 1
  • Ara Darzi
    • 2
  • Guang Zhong Yang
    • 1
    • 2
  1. 1.Royal Society/Wolfson Foundation Medical Image Computing LaboratoryImperial College of Science, Technology and MedicineLondonUK
  2. 2.Department of Surgical Oncology and TechnologyImperial College of Science, Technology and MedicineLondonUK

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