Image segmentation is one of the most challenging issues in image computing. In this work, we focus on region-based active contour techniques (snakes) as they seem to achieve a high level of robustness and fit with a large range of applications. Some algorithmic optimizations provide significant speedups, but even so, execution times are still non-neglectable with the continuing increase of image sizes. Moreover, these algorithms are not well suited for running on multi-core CPU's. At the same time, recent developments of Graphical Processing Units (GPU) suggest that higher speedups could be obtained by use of their specific design. We have managed to adapt a specially efficient snake algorithm that fits recent Nvidia GPU architecture and takes advantage of its massive multi-threaded execution capabilities. The speedup obtained is most often around 7.