Minimally invasive surgery in combination with ultrasound (US) imaging imposes high demands on the sur geon’s hand-eye-coordination capabilities. A possible solution to reduce these requirements is minimally invasive robotic surgery in which the instrument is guided by visual servoing towards the goal defined by the surgeon in the US image. This approach requires robust tracking of the instrument in the US image sequences which is known to be difficult due to poor image quality. This paper presents computer vision algorithms and results of visual servoing experiments. Adaptive thresholding according to Otsu’s method allows to cope with large intensity variations of the instrument echo. Subsequently applied morphological operations suppress noise and echo artefacts. A fast labelling algorithm based on run length coding allows for realtime labelling of the regions. A heuristic exploiting region size and region velocity helps to overcome ambiguities. The overall computation time is less than 10 ms per frame on a standard PC. The tracking algorithm requires no information about texture and shape which are known to be very unreliable in US image sequences. Experimental results for different instrument materials (polyvinyl chloride, polyurethane, nylon, and plexiglas) are given, illustrating the performance of the proposed approach: when chosing the appropriate material the reconstructed trajectories are smooth and only few outliers occur. As a consequence, the visual servoing loop showed to be robust and stable.