Application of weighted-majority minimum-range filters in the detection and sizing of tumors in mammograms

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Abstract
In image processing the solution is often unique to the problem. To be more specific, the importance of the filter window and sampling pattern chosen to filter, pass, or enhance a specific shape is very specific to the problem at hand. We detect suspect tumors in mammograms using a weighted majority minimum range filter and different sampling patterns and windows as a demonstration of this fact. Several methods have been developed to automate the process of detecting tumors in mammograms. We show that traditional windowing or sampling methods may be replaced by a hexagonal method that more accurately reflects the geometry of the problem and could improve the techniques already in existence. Several theorems involving a hexagonal filter window are presented, followed by the results of our application to mammograms.

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