There are several advantages to the local scale-based approach. For instance, boundary-and region-based representations of objects are explicitly contained in the scale-based methods. Based on continuity of homogeneous regions, geometric properties of objects (i.e., size information) can be identified, and this new representation is called scale images, i.e., b-scale, tensor-scale (t-scale), generalized-scale (g-scale) images [16] , [18] , [19] . The b-scale model has been shown to be extremely useful in object recognition [17] , image segmentation [9] , [41] , filtering [16] , inhomogeneity correction [20] , and image registration [20] , [21] . In this study, on the other hand, we show how to use b-scale encoding together with a proper scale selection method for detecting candidate abnormality patterns. The main idea in b-scale encoding is to determine the size of local structures at every voxel as the radius of the largest ball centered at the voxel within which intensities are homogeneous under a prespecified region-homogeneity criterion.