A Localization Framework under Non-rigid Deformation for Robotic Surgery

  • Xiang Xiang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6938)

Abstract

In surgery, it is common to open large incisions to remove tiny tumors. Now, robotic surgery has been well recognized for high precision. However, target localization is still a challenge, owing to non-rigid deformations. Thus, we propose a precise and flexible localization framework for an MRI-compatible needle-insertion robot. We primarily address with two problems: 1) How to predict the position after deformation? 2) How to turn MRI coordinate to real-world one? Correspondingly, the primary novelty is the non-rigid position transformation model based on Thin-Plate Splines. A minor contribution lies in the data acquisition for coordinate correspondences. We validate the precision of the whole framework, and each procedure of coordinate acquisition and position transformation. It is proven that the system under our framework can predict the position with a good approximation to the target’s real position.

Keywords

Robotic Surgery Grape Fruit Localization Framework Medical Image Registration Position Transformation 
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

  • Xiang Xiang
    • 1
  1. 1.Key Lab of Intelligent Information Processing of CAS, Institute of Computing TechnologyChinese Academy of Sciences (CAS)BeijingChina

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