In this paper, we propose a stable and efficient algorithm for animating mass-spring systems. An integration scheme derived from implicit integration allows us to obtain interactive realistic animation of any mass-spring network. We alleviate the need to solve a linear system through the use of a predictor-corrector approach: We first compute a rapid approximation of the implicit integration, then we correct this estimate in a post-step process to preserve momentum. Combined with an inverse kinematics process to implement collisions and other constraints, this method provides a simple, stable and tunable model for deformable objects suitable for virtual reality. An implementation in a VR environment demonstrates this approach. 1

Most of today's medical simulation systems are based on geometric representations of anatomical structures that take no account of their physical nature. Representing physical phenomena and, more speci cally the realistic modeling of soft tissue will not only improve current medical simulation systems but will considerably enlarge the set of applications and the credibility of medical simulation, from neurosurgery planning to laparoscopic surgery simulation. In order to achieve realistic tissue deformation, it is necessary to combine deformation accuracy with computer e ciency. On the one hand, biomechanics has studied complex mathematical models and produced a large amount of experimental data for representing the deformation of soft tissue. On the other hand, computer graphics has proposed many algorithms for the real-time computation of deformable bodies, often at the cost of ignoring the physics principles. In this paper, we survey existing models of deformation in medical simulation and we analyze the impediments to combining computer-graphics representations with biomechanical models. In particular, the di erent geometric representations of deformable tissue are compared in relation to the tasks of real-time deformation, tissue cutting and force-feedback interaction. Finally, we inspect the potential of medical simulation under the development ofthiskey technology. 1

This paper introduces a methodology to simulate the dynamics of deformable visco-elastic 3-dimensional bodies in real-time for haptic interaction. The method is based upon a finite element approach. The central idea in this scheme is to reduce the computation requiredinregions which are to the periphery of the region of interaction between the virtual haptic device and the virtual body. This is accomplished by implementing a multi-layer finite element mesh. The top layer, or parent, consists of a coarse mesh of the entire body# child meshes represent sub-regions of the coarse mesh, but have a much finer resolution. By using equivalent impedances to relate the two meshes, it is possible to decouple the coarse and fine regions# this enables the system to not only to have different resolutions in different regions, but also allows the parent and child meshes to be updated at different frequencies. The multi-layer mesh also addresses numerical integration issues.

Modeling and animation of cloth has experienced important developments in recent years. As a consequence, complex textile models can be used to realistically drape objects or human characters in a fairly efficient way. However, real-time realistic simulation remains a major challenge, even if applications are numerous, from rapid prototyping to e-commerce. In this paper, we present a stable, real-time algorithm for animating cloth-like materials. Using a hybrid explicit/implicit algorithm, we perform fast and stable time integration of a physically-based model with rapid collision detection and response, as well as wind or liquid drag effects to enhance realism. We demonstrate our approach through a series of examples in VR environments, proving that real-time animation of cloth, even on low-end computers, is now achievable.

This paper describes the prototype of a facial expression editor. In contrast to existing systems the presented editor takes advantage of both medical data for the simulation and the consideration of facial anatomy during the definition of muscle groups. The C¹-continuous geometry and the high degree of abstraction for the expression editing sets this system apart from others. Using finite elements we achieve a better precision in comparison to particle systems. Furthermore, a precomputing of facial action units enables us to compose facial expressions by a superposition of facial action geometries in real-time. The presented model is based on a generic facial model using a thin plate and membrane approach for the surface and elastic springs for facial tissue modeling. It has been used successfully for performing facial surgery simulation. We illustrate features of our system with examples from the Visible Human Dataset.

In this paper, we propose a new approach to simulate the small intestine in a context of laparoscopic surgery. The ultimate aim of this work is to simulate the training of a basic surgical gesture in real-time: moving aside the intestine to reach hidden areas of the abdomen. The main problem posed by this kind of simulation is animating the intestine. The problem comes from the nature of the intestine: a very long tube which is not isotropically elastic, and is contained in a volume that is small when compared to the intestine's length. It coils extensively and collides with itself in many places.

Interactive surgery simulations have conicting requirements of speed and accuracy. In this paper we show how to combine a relatively accurate deformation model|the Finite Element (FE) method| and interactive cutting without requiring expensive matrix updates or precomputation. Our approach uses an iterative algorithm for an interactive linear FE deformation simulation. The iterative process requires no global precomputation, so runtime changes of the mesh, i.e. cuts, can be simulated eciently. Cuts are performed along faces of the mesh; this prevents growth of the mesh. We present a provably correct method for changing the mesh topology, and a satisfactory heuristic for determining along which faces to perform cuts. Nodes within the mesh are relocated to align the mesh with a virtual scalpel. This prevents a jagged surface appearance, but also generates degeneracies, which are removed afterwards.

In this paper, we present a recurrent neural network which was designed for the description and simulation of dynamic spring models. The network simulates the physical behavior of deformable or elastic solids like stiffness, viscosity and inertia. The physical parameters of the real model can be used to initialize the network parameters. Besides, it is possible to learn the deformation behavior of a real solid. Using a neural network structure, local changes to the system like collisions or cuts can be easily performed during simulation. Furthermore, it is possible to speed up the simulation by parallel hardware.

Volume transformations of medical images play an important role for many applications such as registration of different modalities, mapping atlases onto clinical data, or simulation of surgical procedures. While registration and atlas mapping can for the major number of applications be performed without tight time constraints, it is essential for simulation systems that they allow real-time interaction. As any computational method in volumes is usually very time consuming, current approaches do mainly concentrate on surface manipulations instead of transforming the entire volume. This paper describes an approach, whichovercomes this problem by first defining the volume manipulation on basis of surface models, which ensure real time performance, and in a second step the transformation is applied to the entire volume by interpolating the mapping parameters using scattered data interpolation methods.

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