Brain MRI Image Classification using Image Mining Algorithms

Nowadays, diagnosis and treatment of deadly cancer diseases are based on symptoms and radiological appearance. There are many modalities for capturing brain images like CT scan (Computed tomography), PET scan (Positron emission tomography) and MRI (Magnetic resonance imaging). MRI is a most important controlled tool for the anatomical judgement of the brain. The classification of cancer in brain MRI is an important task. In the present investigation, there are various techniques used for classification of brain cancer. Under this available image processing technique, classification and feature extraction of brain cancer from MRI images is successfully done. In an initial stage, features are extracted using GLCM technique and features are given as input to SVM classifier. It is observed from the literature that SVM-RBF approach gives better result compare to SVM. Also, SVM-KNN hybrid approach may give a better result because SVM and KNN classifiers give maximum accuracy amongst all image mining approaches. This proposed system is for intellectual classification system for knowledge gathering form MRI image for normal and abnormal brains.