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Biomechanically Driven Registration of Pre- to Intra-Operative 3D Images for Laparoscopic Surgery

  • Ozan Oktay
  • Li Zhang
  • Tommaso Mansi
  • Peter Mountney
  • Philip Mewes
  • Stéphane Nicolau
  • Luc Soler
  • Christophe Chefd’hotel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8150)

Abstract

Minimally invasive laparoscopic surgery is widely used for the treatment of cancer and other diseases. During the procedure, gas insufflation is used to create space for laparoscopic tools and operation. Insufflation causes the organs and abdominal wall to deform significantly. Due to this large deformation, the benefit of surgical plans, which are typically based on pre-operative images, is limited for real time navigation. In some recent work, intra-operative images, such as cone-beam CT or interventional CT, are introduced to provide updated volumetric information after insufflation. Other works in this area have focused on simulation of gas insufflation and exploited only the pre-operative images to estimate deformation. This paper proposes a novel registration method for pre- and intra-operative 3D image fusion for laparoscopic surgery. In this approach, the deformation of pre-operative images is driven by a biomechanical model of the insufflation process. The proposed method was validated by five synthetic data sets generated from clinical images and three pairs of in vivo CT scans acquired from two pigs, before and after insufflation. The results show the proposed method achieved high accuracy for both the synthetic and real insufflation data.

Keywords

Abdominal Wall Laparoscopic Surgery Registration Method Biomechanical Model Registration Error 
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 2013

Authors and Affiliations

  • Ozan Oktay
    • 1
  • Li Zhang
    • 1
  • Tommaso Mansi
    • 1
  • Peter Mountney
    • 1
  • Philip Mewes
    • 2
  • Stéphane Nicolau
    • 3
  • Luc Soler
    • 3
  • Christophe Chefd’hotel
    • 1
  1. 1.Siemens Corporation, Corporate TechnologyPrincetonUSA
  2. 2.Siemens AG, Healthcare AXForchheimGermany
  3. 3.IRCAD, Virtual-SurgStrasbourg CedexFrance

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