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. To do this, we use a layered model to animate the intestine. The intestine's axis is animated as a linear mechanical component. A specific sphere-based model handles contacts and self-collisions. A skinning model is used to create the intestine's volume around the axis. This paper discusses and compares three different representations for skinning the intestine: a parametric surface model and two implicit surface models. The first implicit surface model uses point skeletons while the second uses local convolution surfaces. Using these models, we obtained good-looking results in real-time. Some videos of this work can be found in the online version at doi: 10.1016/j.media.2004.11.006 and at www-imagis.imag.fr/Publications/2004/FLAMCFC04.

This research work is aimed toward the development of a VR-based trainer for colon cancer removal. It enables the surgeons to interactively view and manipulate the concerned virtual organs as during a real surgery. First, we present a method for animating the small intestine and the mesentery (the tissue that connects it to the main vessels) in real-time, thus enabling user interaction through virtual surgical tools during the simulation. We present a stochastic approach for fast collision detection in highly deformable, self-colliding objects. A simple and efficient response to collisions is also introduced in order to reduce the overall animation complexity. Second, we describe a new method based on generalized cylinders for fast rendering of the intestine. An efficient curvature detection method, along with an adaptive sampling algorithm, is presented. This approach, while providing improved tessellation without the classical self-intersection problem, also allows for high-performance rendering thanks to the new 3D skinning feature available in recent GPUs. The rendering algorithm is also designed to ensure a guaranteed frame rate. Finally, we present the quantitative results of the simulations and describe the qualitative feedback obtained from the surgeons.

In this paper, we propose a surgical thread model for suture training and in a more general way thread manipulation. This model is based on dynamic Lagrangian splines constrained by Lagrangian multipliers and penalty-based self-collisions, allowing tying knots simulation in interactive time.