Enhancement of SVM based MRI Brain Image Classification using Pre-Processing Techniques

Background/Objectives: The cases related to Brain Tumor has increased with respect to time owing to various reasons. One of the major challenging issues can be defined by integrating image processing along with data mining algorithms such as classification and clustering. Methods/Statistical Analysis: Artificial Intelligence and Machine Learning techniques are very useful for identifying and visualizing the tumor in the MRI brain image, which can be classified using Support Vector Machines (SVM). Findings: In this paper, we proposed SVM algorithm for classifying the images into two categories Benign and Malignant. SVM classifier model is implemented with RBF and SVM Kernels like linear and non-linear techniques. Application/Improvements: We also proposed for enhancing SVM based MRI Brain image classification by identifying the location and size of the tumor by using different segmentation techniques. The experiments are conducted for evaluating accuracy and the results are compared with existing and proposed work.