METHODS FOR SEGMENTATION OF IVUS ATHEROSCLEROSIS IMAGES

Segmentation is an important aspect of medical image processing. Segmentation of coronary arteries of atherosclerosis is one important process prior to many analyses and visualization tasks for intravascular ultrasound (IVUS) images. It is also helpful in the finding of the disease and its progressive treatment. Different methods are used for medical image segmentation such as Clustering methods, Thresholding method, Classifier, Region Growing, Deformable Model, Markov Random Model etc. The main purpose of this survey is to provide a comprehensive reference source for the researchers involved in Expectation-Maximization based medical image processing. There are different types of Expectation-Maximization algorithms for medical image. Their advantages and disadvantages are discussed.