Automated Classification and Detection of Brain Tumor using Wavelet Transform and Machine Learning
Abstract
The abnormal development of tissues within the brain that affects its activity is referred to as a brain tumor. The accurate detection of brain tumors is an important diagnosis function. The proposed work can classify the given MRI image into the presence of a tumor or the absence of a tumor. Initially, the given MRI image undergoes to prepossessing to remove noise using various filters, then segmentation using OTSU method, the features of segmented MRI image extracted using Discrete Wavelet Transform. The effective features from a bunch of features obtained by using Principle Component Analysis. These features are used to train Support Vector Machine with Radial Basis Function as well as test. The results of the proposed tumor detection method are efficient over literature.