1. A computer implemented method of segmenting a digitized medical image, the method performed by the computer comprising the steps of: providing a digitized image of an anatomical region, said image comprising a diffusion tensor field corresponding to a domain of points on a 3-dimensional grid; partitioning said image into 2 regions, wherein each point is initially assigned to one of said regions; initializing an energy defined as a functional of said diffusion tensor field, wherein said energy functional includes the terms 
 (1−β)∫ Ω (log p d,1 (d 2 (T(x),T 1 ))H ε (φ)+log p d,2 (d 2 (T(x),T 2 ))(1−H ε (φ)))dx wherein φ:Ω→R 3 denotes the level set function defined on the image domain Ω whose zero isosurface coincides with a curve enclosing one of said 2 regions, T 1 and T 2 are mean values of the tensor field in each of the two regions, H ε (φ) is the regularized version of the Heaviside function of the level set function, p d,1 and p d,2 are probability distribution functions of the tensor distance in each of the two regions, β is a weighting parameter, and d 2 (.,.) is a tensor distance; changing the region membership of each point in said image if the energy functional value decreases as a result of said region membership change and updating said mean value of said diffusion tensor field over each of said 2 regions; and obtaining a segmentation of said image when the magnitude of the change of said energy function value resulting from changing the region membership of a point is less then a predetermined threshold.