A Hybrid Approach for Automatic Classification of Brain MRI Using Genetic Algorithm and Support Vector Machine
نویسندگان
چکیده
We purpose a hybrid approach for classification of brain tissues in magnetic resonance images (MRI) based on genetic algorithm (GA) and support vector machine (SVM). A wavelet based texture feature set is derived. The optimal texture features are extracted from normal and tumor regions by using spatial gray level dependence method (SGLDM). These features are given as input to the SVM classifier. The choice of features, which constitute a big problem in classification techniques, is solved by using GA. These optimal features are used to classify the brain tissues into normal, benign or malignant tumor. The performance of the algorithm is evaluated on a series of brain tumor images.
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