Computerized detection of clustered microcalcifications: a modular approach with non-linear filters.

The ideal computerized mammogram processing system still needs to be developed. In order to achieve maximum flexibility we suggest a modular scheme, dividing the processing sequence into functionally autonomous modules. This paper provides a general scheme for detection and/or automated recognition of microcalcifications. Some modules that perform ROI selection are introduced, using special non-linear filters designed for microcalcification detection. A first type of filter selects pixels with specific statistical local features, as compared to the local mean. Among these, only pixels satisfying particular constraints on the local standard deviation are kept. Another type of filter then checks the local mean values of gradient components, so that sharp variations, unrelated to small close objects, can be eliminated. The scheme thus applies different non-linear filters in combination, making precise identification of clustered microcalcifications possible. This modular approach seems greatly to simplify system maintenance and consistency, as well as affording a comparison of different processing techniques and parameters.