  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.
