Much work has been done in the field of Image segmentation but still there is a room for improvement. Medical image segmentation is a sub field of image segmentation in digital image processing that has many important applications in the prospect of medical image analysis and diagnostics. Here in this paper different approaches of medical image segmentation will be classified along with their sub fields and sub methods. Recent techniques proposed in each category will also be discussed followed by a comparison of these methods.
Keywords: Atlas guided methods, Bayesian method, classifiers, clustering, deformable models, Markov random field, Medical image segmentation, modalities, neural networks, region growing, thresholding.