Gray Level Co- Occurrence Matrix Features Based Classification of Tumor in Medical Images
نویسندگان
چکیده
In this paper, the classification of Brain Magnetic Resonance Images (MRI) and Liver Computed Tomography (CT) images has been analysed using supervised technique. The proposed method includes four stages pre-processing, fuzzy clustering, feature extraction and classification. For extracting the features Gray Level Co-occurrence Matrix (GLCM) method has been used. The main features regarding shape, texture and feature statistics have been considered. Then the classifier has been used to classify the brain MRI and the CT liver images into normal and abnormal. The classifier used was Radial Basis Function Support Vector Machine (RBF-SVM). Finally, the performance of the classifier was evaluated in terms of True Positive (TP), True Negative (TN), False Positive (FP), False Negative (FN) and the accuracy was found to be good.
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