1. A method for automated segmentation of lesions within a region of interest of a patient, comprising: producing at least one magnetic resonance imaging (MRI) image of the region of interest; generating at least one probability map from the at least one MRI image, a given probability map representing, for each pixel, a likelihood that a lesion is present at the location represented by the pixel given the at least one MRI image of the region of interest, the at least one probability map comprising a first probability map in which the likelihood for each pixel is determined via classification of intensity values of the at least one MRI image of the region of interest at the pixel; combining the at least one probability map with a plurality of additional probability maps to provide a composite probability map, such that each pixel of the composite probability map is a weighted linear combination of the likelihood values of the corresponding pixels in the at least one probability map and the at least one additional probability map and a set of weights for the weighted linear combination is determined using an expert system trained on prior datasets; and identifying lesions from the composite probability map.