Mammograms Feature Extraction using Fuzzy Surface

Mammography is the most contemporary option for the premature detection of breast cancer in women. The principal feature within the breast region is the breast contour. Extraction of the breast region and delineation of the breast contour is an essential pre-processing step in the process of computer aided detection. Primarily it allows the search for abnormalities to be limited to the region of the breast without undue influence from the background of the mammogram. The methodology involves the use of fuzzy surface for selecting the features of mammograms. Feature extraction is an essential pre-processing step to pattern recognition and machine learning problems. It is often decomposed into feature construction and feature selection. It is well known that mammographic images have some degrees of fuzziness such as indistinct borders, ill-defined shapes, and different densities. Due to the nature of mammography and breast structure, fuzzy logic would be a better choice to handle the fuzziness of mammograms than traditional methods. There are many features such as shape features, texture features etc. The surface viewer is used to display the dependency of one of the outputs on any one or two of the inputs — that is, it generates and plots an output surface map for the system. A variety of samples has been tried out to generate and plot the surface maps.