抽象的

An Enhanced Mammogram Image Classification Using Fuzzy Association Rule Mining

Dr.K.Meenakshi Sundaram , P.Aarthi Rani , D.Sasikala

Digital mammogram becomes the most effective technique for early breast cancer detection modality. Processing images require high computational capabilities. Computer image processing techniques will be applied to enhance images. This paper discusses about Data mining is a technique to dig the data from large database for analysis and execution and the image mining technique deals with extracting implicit knowledge with data relationship. This paper, applies image mining technique on mammogram to classify the cancer diseases. It can be classified into normal, benign and malignant. In existing method used association rule mining, decision tree classify a mammogram image and the Fuzzy Association Rule Mining is applied. Experiments have been taken dataset with 300 images taken from MIAS of various types to improve accuracy using minimum number of rules to patterns. The experiments and results of the FARM gives better performance compared with existing method.