Scale-based image filtering of magnetic resonance data

Abstract

The invention provides novel scale-based filtering methods that use local structure size or 'object scale' information to arrest smoothing around fine structures and across even low-gradient boundaries. One method teaches a weighted average over a scale-dependent neighborhood; while another employs scale-dependent diffusion conductance to perform filtering. Both methods adaptively modify the degree of filtering at any image location depending on local object scale. This permits a restricted homogeneity parameter to be accurately used for filtering in regions with fine details and in the vicinity of boundaries, while at the same time, a generous filtering parameter is used in the interiors of homogeneous regions.