This paper presents a method to register a pre-operative Computed-Tomography (CT) volume to a sparse set of intra-operative Ultra-Sound (US) slices. In the context of percutaneous renal puncture, the aim is to transfer planning information to an intra-operative coordinate system. The spatial position of the US slices is measured by optically localizing a calibrated probe. Assuming the reproducibility of kidney motion during breathing, and no deformation of the organ, the method consists in optimizing a rigid 6 Degree Of Freedom (DOF) transform by evaluating at each step the similarity between the set of US images and the CT volume. The correlation between CT and US images being naturally rather poor, the images have been preprocessed in order to increase their similarity. Among the similarity measures formerly studied in the context of medical image registration, Correlation Ratio (CR) turned out to be one of the most accurate and appropriate, particularly with the chosen non-derivative minimization scheme, namely Powell-Brent's. The resulting matching transforms are compared to a standard rigid surface registration involving segmentation, regarding both accuracy and repeatability. The obtained results are presented and discussed.