Image Pre-processing and Feature Extraction Techniques for Magnetic Resonance Brain Image Analysis

Abstract

Image pre-processing and feature extraction techniques are mandatory for any image based applications. The accuracy and convergence rate of such techniques must be significantly high in order to ensure the success of the subsequent steps. But, most of the time, the significance of these techniques remain unnoticed which results in inferior results. In this work, the importance of such approaches is highlighted in the context of Magnetic Resonance (MR) brain image classification and segmentation. In this work, suitable pre-processing techniques are developed to remove the skull portion surrounding the brain tissues. Also, texture based feature extraction techniques are also illustrated in this paper. The experimental results are analyzed in terms of segmentation efficiency for pre-processing and distance measure for feature extraction techniques. The convergence rate of these approaches is also discussed in this work. Experimental results show promising results for the proposed approaches.