1. A method of segmenting an object in a digital image, comprising the steps of: acquiring an N-dimensional digital image, said image comprising a plurality of data items associated with an N-dimensional domain of points, wherein said digital image is represented as a graph wherein each point of said image is associated with a vertex of said graph and said graph includes an edge connecting each pair of vertices corresponding to adjacent points in said image; computing, for each vertex v i in said graph, weights w ijk of a curvature clique v j v i v k for each successive pair of edges e ij , e ik incident on said vertex v i , taken clockwise, wherein v i and v j are connected by edge e ij , and v i and v k are connected by edge e ik ; decomposing each curvature clique into pairwise edge weights to form a new set of edges by adding, for all vertices v j , v k such that v i and v j are connected by edge e ij , and v i and v k are connected by edge e ik , an edge e ij with weight w ij , an edge w ik with weight w ik , and an edge e jk with weight w jk , wherein weight w ij for edge e ij equals weight w ik for edge e ik equals ½ w ijk , and weight w jk for edge e jk connecting vertices v j and v k equals −½ w ijk ; computing an indicator function x of the points of the image indicative of whether each point belongs to an object of interest by minimizing a functional E curvature ⁡ ( x ) = ∑ e mn ∈ E * ⁢ w mn ⁢  x m - x n  of said indicator function, wherein e mn is an edge in the new set of edges E*; and segmenting said object of interest from said image based on the value of the indicator function x at each image point, wherein a point v i belongs to the object of interest if x i =1, and belongs to a background if x i =0.