Region-based active contours with noise and shape priors

International audienceIn this paper, we propose to combine formally noise and shape priors in region-based active contours. On the one hand, we use the general framework of exponential family as a prior model for noise. On the other hand, translation and scale invariant Legendre moments are considered to incorporate the shape prior (e.g. delity to a reference shape). The combination of the two prior terms in the active contour functional yields the nal evolution equation whose evolution speed is rigorously derived using shape derivative tools. Experimental results on both synthetic images and real life cardiac echography data clearly demonstrate the robustness to initialization and noise, exibility and large potential applicability of our segmentation algorithm