1. An image processing method for segmenting a novel image data set to mark an object of interest therein, the method comprising: (a) providing a computer with a multi-atlas data set comprising a plurality of atlases, each atlas containing a reference image data set and segmentation data which marks an object of interest within the reference image data set; (b) inputting into the computer a novel image data set for segmentation; (c) registering in the computer the novel image data set with each of the atlases; (d) selecting in the computer at least one atlas of the plurality of atlases to use for segmentation based on the registration performed in the registering step; (e) segmenting in the computer the novel image data set based on the selected at least one atlas; and (f) outputting in the computer the novel image data set with the associated segmentation data, so that the object of interest in the novel image data set is marked, wherein each atlas of the plurality of atlases further comprises regression parameters representing results of a regression analysis between (i) real overlap between the atlas and a set of training image data sets, and (ii) a similarity measure between the atlas and the set of training image data sets; and wherein the segmentation performed in the segmentation step is carried out by: (a) computing a value of the similarity measure for each of the registrations, and (b) obtaining a predicted overlap for each of the registrations by applying the respective regression parameters to the respective values of the similarity measure; and the selecting step includes selecting the at least one atlas of the plurality of atlases to use for the segmentation step based on the predicted overlaps.