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Essential techniques for improving visual realism of laparoscopic surgery simulation.

Qian, K., 2018. Essential techniques for improving visual realism of laparoscopic surgery simulation. Doctoral Thesis (Doctoral). Bournemouth University.

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QIAN, Kun_Ph.D._2017.pdf



With the prevalence of laparoscopic surgery, the request for reliable training and assessment is becoming increasingly important. The traditional way of training is both time consuming and cost intensive, and may cause ethical or moral issues. With the development of computer technologies, virtual reality has entered the world of consumer electronics as a new way to enhance tactile and visual sensory experiences. Virtual reality based surgical skill training gradually becomes an effective supplementary to the traditional laparoscopic skill training in many surgical theatres. To provide high fidelity virtual surgery training experiences, the presentation of the virtual world should have the same level of realism as what surgeons see and feel during real operations. However, the weak computing power limits the potential level of details on the graphics presentation and physical behaviour of virtual objects, which will further influence the fidelity of tactile interaction. Achieving visual realism (realistic graphics presentation and accurate physical behaviour) and good user experience using limited computing resources is the main challenge for laparoscopic surgery simulation. The topic of visual realism in laparoscopic surgery simulation has not been well researched. This topic mainly relates to the area of 3D anatomy modeling, soft body simulation and rendering. Current researches in computer graphics and game communities are not tailored for laparoscopic surgery simulation. The direct use of those techniques in developing surgery simulators will often result in poor quality anatomy model, inaccurate simulation, low fidelity visual effect, poor user experience and inefficient production pipeline, which significantly influence the visual realism of the virtual world. The development of laparoscopic surgery simulator is an interdiscipline of computer graphics, computational physics and haptics. However, current researches barely focus on the study of tailored techniques and efficient production pipeline which often result in the long term research cycle and daunting cost for simulator development. This research is aiming at improving the visual realism of laparoscopic surgery simulation from the perspective of computer graphics. In this research, a set of tailor techniques have been proposed to improve the visual realism for laparoscopic surgery simulation. For anatomy modeling, an automatic and efficient 3D anatomy conversion pipeline is proposed which can convert bad quality 3D anatomy into simulation ready state while preserving the original model’s surface parameterization property. For simulation, a soft tissue simulation pipeline is pro- posed which can provide multi-layer heterogeneous soft tissue modeling and intuitive physically editable simulation based on uniform polynomial based hyperelastic material representation. For interaction, a collision detection and interaction system based on adaptive circumphere structure is proposed which supports robust and efficient sliding con- tact, energized dissection and clip. For rendering, a multi-layer soft tissue rendering pipeline is proposed which decomposed the multi-layer structure of soft tissue into corresponding material asset required by state-of-art rendering techniques. Based on this research, a system framework for building a laparoscopic surgery simulator is also proposed to test the feasibility of those tailored techniques.

Item Type:Thesis (Doctoral)
Additional Information:If you feel that this work infringes your copyright please contact the BURO Manager
Uncontrolled Keywords:laparoscopic surgery; simulation; visual realism; simulation ready model; soft tissue deformation; collision detection; multi-layer soft tissue; rendering
Group:Faculty of Media & Communication
ID Code:30532
Deposited By: Symplectic RT2
Deposited On:29 Mar 2018 10:59
Last Modified:09 Aug 2022 16:04


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