Image Processing Techniques for Brain Tumor Extraction from MRI Images using SVM Classifier

Abstract

Abstract— Brain tumor extraction and analysis of it are challenging tasks in medical image processing by the use of Magnetic resonance imaging (MRI) because brain image and its structure is complicated that can be analyzed only by expert radiologists. Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. A tumor may lead to cancer, which is a major leading cause of death and responsible for around 13% of all deaths world-wide. Magnetic Resonance images are used to find the presence of brain tumor in brain. Magnetic resonance imaging (MRI) is an imaging technique that has played an important role in neuro science research for studying brain images. In this paper we propose an automatic brain tumor detection that can detect and localize brain tumor in magnetic resonance imaging. The proposed method work in follows manner: Firstly we extract the feature of an image and then classifies it. First stage is used to extract the features from images using Grey level Co-occurrence matrix. In the second step the features which are extracted are used as input for Support Vector machine (SVM).
DOI: 10.17762/ijritcc2321-8169.150543