Image Processing based Brain Tumor Detection

Abstract

The formation of abnormal cells within the brain is referred to as a "brain tumor." There are numerous types of brain tumors. Some of the brain tumors are cancer causing (Malignant) and others are non cancerous (benign). Magnetic resonance imaging (MRI) is a technology that is used to identify and classify brain cancers. After an MRI establishes the existence of a brain tumor, the most frequent method for determining the kind of tumor is to biopsy or operate on a sample of tumor tissue. Though the first process is done by a really experienced person as brain tumors are a very serious issue and need an experienced person to confirm that. In this whole process MRI can’t confirm about any tumor. It shows only the image of the internal image of brain tissue. Image processing is a very powerful tool to analyze MRI images with the help of different algorithms and using some other data. In this there are many parameters used to finalize whether there is tumor or not some of the parameters are accuracy. This paper discusses the many approaches and procedures used to identify brain cancers, as well as the accuracy of detecting the tumor in the brain using Image processing, which includes steps: Pre-processing, Segmentation, Threshold segmentation, Feature extraction, Classification using SVM (Support Vector Machine).