[en] Tridimensional image analysis provides a set of methods for the intelligent extraction of information in order to visualize, recognize or inspect objects in volumetric images. In this field of research, we are interested in algorithmic and methodological aspects to extract surface visual information embedded in volume ultrasonic images. The aim is to help a non-acoustician operator, possibly the system itself, to inspect surfaces of vessel and internals in Fast Breeder Reactors (FBR). Those surfaces are immersed in liquid metal, what justifies the ultrasonic technology choice. We expose firstly a state of the art on the visualization of volume ultrasonic images, the methods of noise analysis, the geometrical modelling for surface analysis and finally curves and surfaces matching. These four points are then inserted in a global analysis strategy that relies on an acoustical analysis (echoes recognition), an object analysis (object recognition and reconstruction) and a surface analysis (surface defects detection). Few literature can be found on ultrasonic echoes recognition through image analysis. We suggest an original method that can be generalized to all images with structured and non-structured noise. From a technical point of view, this methodology applied to echoes recognition turns out to be a cooperative approach between morphological mathematics and snakes (active contours). An entropy maximization technique is required for volumetric data binarization. (author)