Virtual Reality-Based Simulation of Endoscopic Surgery

Székely, Gábor; Brechbühler, Christian; Dual, Jürg; Enzler, Rolf; Hug, Johannes; Hutter, R.; Ironmonger, Nicholas; Kauer, M.; Meier, Valeria; Niederer, Peter F.; Rhomberg, A.; Schmid, P. E.; Schweitzer, Gerhard; Thaler, Marlene; Vuskovic, Vladimir; Tröster, Gerhard; Haller, U.; Bajka, Michael

doi:10.1162/105474600566817

Cited by 83 publications

(52 citation statements)

References 27 publications

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“…Currently, there are a number of simulators under development, which allow physical-based, real-time deformations of virtual tissues and organs (see, for example [5,39]). Most of these simulators use FEM for computing virtual deformations because FEM are well known to solve similar problems in non real-time environments.…”

Section: Application Example: Virtual Surgerymentioning

confidence: 99%

Using recurrent neuro-fuzzy techniques for the identification and simulation of dynamic systems

Nürnberger

Radetzky²,

Kruse

2001

Neurocomputing

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The identi"cation and simulation of dynamic systems is still a challenging problem. In this article some basic aspects of neuro-fuzzy techniques for the identi"cation and simulation of time-dependent physical systems are presented. In particular, a neuro-fuzzy model that can be used for the identi"cation and the (real-time) simulation of viscoelastic models, is described. The presented model is motivated by a cooperative neuro-fuzzy approach based on a vectorized recurrent neural network architecture. The physical motivation of this model is illustrated and speci"c propagation procedures and a learning algorithm are presented. Moreover, the usability in practice is demonstrated by an application of the model in the area of surgical simulation.

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Section: Application Example: Virtual Surgerymentioning

confidence: 99%

Using recurrent neuro-fuzzy techniques for the identification and simulation of dynamic systems

Nürnberger

Radetzky²,

Kruse

2001

Neurocomputing

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“…Even critical situations could be recreated turning the simulator into an attractive training option also for experienced physicians. The computational power that became available in the last few years enabled the development of many different simulator systems [13,7]. There is consensus on the possible benefits of such virtual reality based training systems, provided that they can overcome some of the current limitations.…”

Section: Introductionmentioning

confidence: 99%

Pathology Growth Model Based on Particles

Sierra

Bajka

Székely

2003

Lecture Notes in Computer Science

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Abstract. Virtual reality based surgical simulators offer the possibility to provide training on a wide range of findings of different pathologies. Current research aims at a high fidelity hysteroscopy simulator. Different methods for the generation of pathologies have been investigated to realize the first surgical simulator that challenges the trainee with a new scene in every training session. In this paper, a particles-based tumor growth model is presented that overcomes different limitations of previous approaches. It allows for a realistic generation of both polyps and myomas protruding to different extents into the uterine cavity. The model incorporates several biological as well as mechanical factors, which influence the growth process and thus the appearance of the pathologies.

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“…Within the framework of an earlier project at our institute a realistic, VRbased, endoscopic surgery simulator has been developed [10]. The soft tissue deformations are determined using a complex, non-linear, explicit Finite Element (FE) model.…”

Section: Introductionmentioning

confidence: 99%

A New Approach to Cutting into Finite Element Models

Serby

Harders

Székely

2001

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001

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Abstract. Virtual reality based surgical simulators offer a very elegant approach to enhancing traditional training in endoscopic surgery. In this context a realistic soft tissue model is of central importance. The most accurate procedures for modeling elastic deformations of tissue use the Finite Element Method to solve the governing mechanical equations. Therapeutic interventions (e.g. cutting) require topological changes of the Finite Element mesh, thus making a non-trivial remeshing step necessary. This paper describes a new approach to cutting in Finite Element models. The central idea is not to introduce new nodes/elements but to displace the existing ones to account for the topological changes introduced by a cut. After the displacement of the nodes/elements the mesh is homogenized to avoid tiny elements which destabilize the explicit time integration necessary for solving the equations of motion.

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Virtual Reality-Based Simulation of Endoscopic Surgery

Cited by 83 publications

References 27 publications

Using recurrent neuro-fuzzy techniques for the identification and simulation of dynamic systems

Using recurrent neuro-fuzzy techniques for the identification and simulation of dynamic systems

Pathology Growth Model Based on Particles

A New Approach to Cutting into Finite Element Models

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