Segmentation of Magnetic Resonance Images of Brain Tumors using Support Vector Machine Method (Support Vector Machine)

Abstract

The Support Vector Machine (SVM) technology was used to segment a set of brain MRI images. This segmentation process is based on classifying the data and separating it linearly and non-linearly into two categories by finding perfect points that represent the boundary between the points of the two groups and through these points The remaining points are distinguished, and the data is separated by using prominent regions and separated from the background by using Fourier transform and using the new modified data in order to obtain the binary coding of the image and then training this data according to the encoding, and then using the SVM model in order to train the data Extracting the fragmentary image and identifying the tumors in it.