GPU-friendly gallbladder modeling in laparoscopic cholecystectomy surgical training system

  • Authors:
  • J. Zhang;J. Zhou;W. Huang;J. Qin;T. Yang;J. Liu;Y. Su;C. K. Chui;S. Chang

  • Affiliations:
  • Department of Medical Information Engineering, School of Electrical Engineering and Information, Sichuan University, PR China and Institute for Infocomm Research, Agency for Science, Technology an ...;Institute for Infocomm Research, Agency for Science, Technology and Research, Singapore;Institute for Infocomm Research, Agency for Science, Technology and Research, Singapore;Department of Mechanical Engineering, National University of Singapore, Singapore;Institute for Infocomm Research, Agency for Science, Technology and Research, Singapore;Institute for Infocomm Research, Agency for Science, Technology and Research, Singapore;Institute of High Performance Computing, Agency for Science, Technology and Research, Singapore;Department of Mechanical Engineering, National University of Singapore, Singapore;Department of Surgery, National University Hospital, Singapore

  • Venue:
  • Computers and Electrical Engineering
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

A challenge in virtual reality based laparoscopic cholecystectomy simulation is to construct a fast and accurate deformable gallbladder model. This paper proposed a multi-layered mass-spring model which can adapt well to the built-in accelerating algorithms in PhysX-Engine of Graphics Processing Unit (GPU). The gallbladder was first segmented from clinical Computed Tomography (CT) images. From the segmentation result, a surface mesh of a gallbladder was constructed. The inner layers of a mass-spring model were generated from the surface mesh based on the anatomical structure of gallbladder. We configured the parameters of the springs based on the biomechanical properties of gallbladder to ensure the reality of the deformation results. Preliminary experiments demonstrated that our model was able to achieve satisfactory results in terms of both visual perception and time performance.