Type-2 fuzzy inference system design for computer aided detection in mammogram image

Nowadays the detection of cancer of the breast mass X-ray mammography is widely used by radiologists. This computer-aided system images used by physicians in the interpretation raises the accomplishments of physicians identified masses. Work on computer-aided detection systems consisting of basic image processing and classification section is still in progress. Different methods such as artificial neural networks and support vector machine structure is widely used in mass classification. Previous work in our open access has MIAS containing mass from the database and free mammogram images on image processing techniques and three texture attribute in the second degree by using statistical analysis and derived value statistics of these attributes, attributes, and type-1 fuzzy using Matlab fuzzy toolbox with statistical values inference system is designed. In this study, the standard deviation of the data set using a statistical method on each attribute data set used for type-1 system is calculated. These values are used as the footprint of the uncertainty of the type-2 system parameters. These data sets and data sets related to each piece of histogram chart with type-2 fuzzy inference system was conducted as separate software. We have tested our system type-2 fuzzy inference system has produced more successful than type-1 fuzzy inference system.