Nonlinear filtering and multiscale texture discrimination for mammograms
Walter B. Richardson · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
A general method for computer aided diagnosis (CAD) of mammograms using a multiscale decomposition is proposed and implemented using several different techniques. The first is the now classic wavelet decomposition in which the smoothed versions of the image at coarser resolutions are given by appropriate orthogonal projections. Then two distinct nonlinear filters are used to provide a decomposition into simplified resumes and corresponding details at several different `scales.' One filter uses a nonlinear partial differential equation to provide smoothing and the other uses a robust weighted majority-minimum range (WMMR) algorithm. Results indicate that these methods will prove valuable in the design of a software package to assist the radiologist.