Skip to main content

Essential techniques for laparoscopic surgery simulation.

Qian, K., Bai, J., Yang, X., Pan, J. J. and Zhang, J. J., 2017. Essential techniques for laparoscopic surgery simulation. Computer Animation and Virtual Worlds, 28 (2), E1724.

Full text available as:

example.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.


DOI: 10.1002/cav.1724


Laparoscopic surgery is a complex minimum invasive operation that requires long learning curve for the new trainees to have adequate experience to become a qualified surgeon. With the development of virtual reality technology, virtual reality-based surgery simulation is playing an increasingly important role in the surgery training. The simulation of laparoscopic surgery is challenging because it involves large non-linear soft tissue deformation, frequent surgical tool interaction and complex anatomical environment. Current researches mostly focus on very specific topics (such as deformation and collision detection) rather than a consistent and efficient framework. The direct use of the existing methods cannot achieve high visual/haptic quality and a satisfactory refreshing rate at the same time, especially for complex surgery simulation. In this paper, we proposed a set of tailored key technologies for laparoscopic surgery simulation, ranging from the simulation of soft tissues with different properties, to the interactions between surgical tools and soft tissues to the rendering of complex anatomical environment. Compared with the current methods, our tailored algorithms aimed at improving the performance from accuracy, stability and efficiency perspectives. We also abstract and design a set of intuitive parameters that can provide developers with high flexibility to develop their own simulators.

Item Type:Article
Additional Information:Funded by: National Natural Science Foundation of China. Grant Number: 61402025 Centre for Digital Entertainment
Uncontrolled Keywords:laparoscopic surgery simulation;deformation;collision detection;dissection;rendering
Group:Faculty of Media & Communication
ID Code:24081
Deposited By: Symplectic RT2
Deposited On:21 Jun 2016 10:07
Last Modified:14 Mar 2022 13:56


Downloads per month over past year

More statistics for this item...
Repository Staff Only -