Medical Image Segmentation Based on Markov Random Field
Bao Su-su · Journal of Beijing Union University · 2009
Image segmentation is a classical problem.With the development of medical image,it has important meaning in the application of medical.Markov Random Field(MRF)method is an extremely active research field in image segmentation.This paper introduces the relationship between a general theory based on Markov random field model and the images.And the traditional ICM algorithm is improved.After the pre-segmentation of the image,image pixels are divided into two classes:the stable points and the unstable.The unstable points are stored by a queue.Only the unstable points are dealt with in each iteration to reduce computation of load.The experiment results indicate that the improved ICM algorithm can greatly improve the computational efficiency.