Detection and Classification Brain Tumor of Magnetic Resonance Imaging Using 2D Gabor Wavelet Transform and Artificial Neural Network: A Review

Abstract

Human system is made up of many organs, brain is the first and the leading controller of the human system. Abnormal growth of the Overload cells in brain is called as brain tumor. In medical field brain tumor detection and classification is one of the difficult tasks. Early detection and classification of brain tumor obviously increases the chances of proper treatment. In this review paper specially focus on detection and classification of the brain tumor from MRI images of brain. Nowadays Medical Image Processing is a complex and challenging field. This review paper proposed the techniques this techniques is very useful to give the information about brain tumor which is very helpful to the doctor for giving the proper treatment.. This review paper proposed the 2D Gabor wavelet transform technique for detection of brain tumor. Proposed technique perform the systematic evaluation of the database of MRI brain images. Artificial neural network use for the Automated and accurate classification of MRI images of brain tumor. Artificial neural network Classify the Brain Tumor into three types that is benign, malignant or normal. Probabilistic Neural Network is the part of the artificial neural network. The performance of the Probabilistic Neural Network classifier evaluation is based on training set and accuracy of classification. Probabilistic Neural Network gives proper result of classification than other artificial neural networks and it is a optimistic tool for classification of the brain Tumors .