Medical-image Segmentation Arithmetic Based On Fuzzy Cellular Automata

First this paper briefly introduces the basic theory and the development of cellular automata. In this paper, we introduce the origin and history of cellular automata systematically, elaborate the theory model of cellular automata and its main characteristics and advantages as the complicated system model. Moreover, we make the introduction to the present research and application of cellular automata.Cellular automata (CA) are dynamical systems in which space and time are discrete. As a discrete model to realize complex system, cellular automata had generated many interests because of its usefulness for resolving many factual problems.The medical-image segmentation is a very important region in the medical-image processing, is also a typical difficult problem. It has already various segmentation methods now. This paper introduces some segmentation methods and these methods have been already accepted. Moreover, this paper also introduces the application of cellular automata theory model in the medical-image segmentation.In addition, This paper try to put the fuzzy logic into cellular automata model and build up fuzzy cellular automata in order to handle many uncertain aspects and problems of imprecise and vague data of the real world, thereby made the ability of simulation of cellular automata stronger and more intelligent and enrich the theory of cellular automata. Applying the cellular automata model given in this paper, we handled the problem of medical-image segmentation, the pixels whose grey level is between object and background can be handled well, and good result of image segmentation can be got.