Abstract : In this paper, we propose to consider the estimation of a refer-ence shape from a set of different segmentation results using both active contours and information theory. The reference shape is defined as the minimum of a criterion that benefits from both the mutual information and the joint entropy of the input segmentations and called a mutual shape. This energy criterion is here justified using similarities between informa-tion theory quantities and area measures, and presented in a continuous variational framework. This framework brings out some interesting evaluation measures such as the speci-ficity and sensitivity. In order to solve this shape optimization problem, shape derivatives are computed for each term of the criterion and interpreted as an evolution equation of an active contour. Some synthetical examples allow us to cast the light on the difference between our mutual shape and an average shape. Our framework has been considered for the estimation of a mutual shape for the evaluation of cardiac segmentation methods in MRI.