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In this paper, we propose an energy functional to segment objects whose global shape is a priori known thanks to a statistical model. Our work aims at extending the variational approach of Chen et al. [Y. Chen, et al., 2002] by integrating the statistical shape model of Leventon et al. [M. Leventon, et al., 2000]. The proposed energy functional allows us to capture an object that exhibits high image gradients and a shape compatible with the statistical model which best fits the segmented object. The minimization of the functional provides a system of coupled equations whose steady-state solution is the solution of the segmentation problem. Results are presented on synthetic and medical images.