Novel approach for segmentation of brain magnetic resonance imaging using intensity based thresholding

Magnetic resonance imaging (MRI) is an advanced medical imaging technique providing rich information about the human soft tissue anatomy. The goal of brain MRI segmentation is to accurately identify the principal tissue structures in these image volumes. There are many methods that exist to segment the brain. One of these, conventional methods that use pure image processing techniques are not preferred because they need human interaction for accurate and reliable segmentation. Unsupervised methods, on the other hand, do not require any human interference and can segment the brain with high precision. In the light to this fact, A novel approach is developed. Our approach is based on intensity based thresholding to get boundaries between cerebrospinal fluid (CSF), Gray Matter (GM), White Matter (WM) and others. After the brain extraction by mathematical morphology algorithm, we proceed to brain segmentation. The CSF is segmented by using orthogonal polynomial transform. Finally the gray matter and white matter regions in the MRI are segmented based up on the intensity values. Experimental results show that the proposed method achieves reasonable good segmentation.