Overview of Medical Image Segmentation Process of Selected Magnetic Resonance Images; Manual Segmentation and Active Contour/Snake Model

Image segmentation is the procedure which differentiating a digital image into segments and enables meaningful images. Image segmentation also locates objects and boundaries by labeling each pixel. Image segmentation is part of image processing and it is a fundamental step to analyze images. This is mid-level technique in image processing event. It is a fundamental step and overall quality of the image directly depends on image segmentation. There is a different type of methods available for image segmentation such as manual segmentation, intensity-based methods, discontinuity based methods, similarity-based methods, clustering methods, graph-based methods, Pixon based methods and hybrid methods. Different types of segmentation techniques are used for segmentation. Based on the application, a single or a combination of segmentation techniques can be applied to solve the problem effectively. This report evaluates the manual and active counter/snake methods in a medical imaging context by use of commercially available MATALB.