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Non Rigid Registration of 3D Images to Laparoscopic Video for Image Guided Surgery

  • Max Allan
  • Ankur Kapoor
  • Philip Mewes
  • Peter MountneyEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9515)

Abstract

Image guidance and the visualization of sub surface structures during laparoscopic procedures have the potential to change the current capabilities of surgery. Increased target localization accuracy and the identification of critical structures can reduce resection mar-gins, procedure time and tissue trauma while simplifying procedures and enabling new functional capabilities. Image guidance requires the registration of 3D images to the laparoscopic video. Tissue deformation and lack of cross modality landmarks make this challenging. Registration can be performed by aligning the 3D image to a surface reconstructed from stereo laparoscopic images. Current research is focused on creating more generic stereo reconstruction techniques and rigid registration methods. This paper proposes a novel stereo reconstruction approach which exploits prior knowledge of patient specific organ models and outlier robust non rigid registration. The approach is validated on phantom data and the practical application of the reconstruction is demonstrated on in vivo data.

Keywords

Gaussian Mixture Model Iterative Close Point Tissue Deformation Rigid Registration Disparity Estimate 
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 International Publishing Switzerland 2016

Authors and Affiliations

  • Max Allan
    • 1
  • Ankur Kapoor
    • 1
  • Philip Mewes
    • 2
  • Peter Mountney
    • 1
    Email author
  1. 1.Siemens Corporate ResearchPrincetonUSA
  2. 2.Siemens HealthcareForchheimGermany

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