1. A computer-implemented method of segmenting imaging data of at least one subject, comprising: receiving imaging data comprising a plurality of image elements of the region of interest of the at least one subject; segmenting, using at least one data processor, the imaging data of the region of interest of the at least one subject into a plurality of sub-regions corresponding to various structures at a plurality of levels of granularity, the plurality of levels of granularity having a relationship such that a level of granularity has fewer structures at a lower level of granularity; calculating at each of the plurality of levels of granularity an abnormality factor or risk factor for the segmented various structures of said region of interest, to provide a segmented said region of interest of said subject with at least one of said abnormality factor or risk factor associated therewith; providing at least one template atlas for said region of interest of the at least one subject; providing other segmented imaging data having other structures of regions of interest of other subjects; and identifying a substantially same region of interest in the other imaging data as the region of interest of the at least one subject by comparing one or more anatomical features, at multiple levels of granularity, in at least one of sizes, shapes and intensities of the structures of the segmented imaging data and the other structures of the other segmented imaging data based on similarities of the structures and the other structures, to associate said abnormality factor or risk factor with said identified region of interest of said other imaging data, wherein the various structures at each level of granularity are predefined in said at least one template atlas; wherein said segmenting includes applying said at least one template atlas to said received imaging data at each level of granularity; wherein the segmenting includes: measuring at least one of sizes, shapes and intensities of the various structures at each level of granularity, and performing single-subject or population-based labeling of the various structures to characterize anatomical features of the region of interest; and wherein the anatomical feature is at least one of an abnormality, a disease, a condition, a diagnosis, or any combination thereof.