Diaz, C., Eliuk, S., Boulanger, P.,Trefftz, H. (2010) Soft Tissues using a GPU Approach of the Mass-Spring Model. In 3IA International Conference on Computer Graphics and Artificial Intelligence, 8 pages, Athens, Greece, Springer.
The recent advances in the fields such as modelling bio-mechanics of living tissues, haptic technologies, computational capacity, and virtual environments have created conditions necessary in order to develop effective surgical training and learning methods. Simulation environments for surgical training have no limitations on the number of times a procedure can be executed, and most importantly have no risk to patients. Moreover, these simulations allow for quantitative evaluation of a surgeons performance, leading to the ability to create performance standards in order to determine a surgeons current surgical expertise. Virtual simulators need to meet two requirements in order to be useful in a training environment: good interactivity (real-time FPS) and high realism. The most expensive computational task in a surgical simulator is that of the physical model. The physical model is the component responsible to simulate the deformation of the anatomical structures and the most important factor in order to obtain realism. In this paper we present a novel approach to virtual surgery. The novelty comes in two forms: specifically a highly realistic mass-spring model, and a GPU based technique, and analysis, that provides a nearly 80x speedup over serial execution and 20x speedup over CPU based parallel execution.
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