Description

Medical image classification play an important role in medical research field.Classification depends on the features extracted from the images.We mainly concentrating on feature extraction stage to yield better classification performance.Texture based features such as GLCM(Gray Level Co-occurrence Matrix)features play an important role in medical image analysis.Totally 14 different statistical features were extracted.To select the discriminative features among them we use sequential forward selection algorithm.Afterwards we prefer Support vector Machine(SVM) for the classification stage.Classifier performance will be analysed further.