CLASSIFICATION OF MAMMOGRAPHIC MASSES USING FUZZY INFERENCE SYSTEM
AbstractComputer aided detection (CAD) intends to provide assistance to the mammography detection, reducing breast cancer misdiagnosis, thus allowing better diagnosis and more efficient treatments. In this work the task of automatically classifying the mass tissue into Breast Imaging Reporting and Data System (BI-RADS) shape categories: round, oval, lobular, irregular and also as benign or malignant is investigated. Geometrical shape and margin features based on maximum and minimum radius of mass are used in this work to classify the masses. These geometric features are found to be good in discriminating regular shapes from irregular shapes. For the purpose of classification, the masses are segmented from the mammogram using gray level thresholding. Finally, the classification is performed using fuzzy inference system. The fuzzy rules are used to construct the generalized fuzzy membership function for classifying the shape and severity of masses. The images were collected from Mammographic Image Analysis Society (MIAS) Database and Digital Database for Screening Mammography (DDSM). The experiments were implemented in MATLAB.
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