Abstract: This article discusses the application of Markov Random Field （MRF） based on Particle Swarm Optimization （PSO） for Magnetic Resonance Image（MRI） segmentation.Imagery segmentation of MRF-PSO model based on MRF is proposed.The Maximum A Posteriori （MAP） global best solution of segmentations will be got though MRF by using the method of PSO，which describes image data relations by local correlations instead of global image possibility distributions.Finally，results are given.It shows that the MRF-PSO method is an effective method in image segmentation.

摘要： 研究了应用粒子群优化算法（PSO）优化Markov随机场方法对磁共振图像进行分割的算法。建立了基于马尔可夫随机场的图像分割模型，针对马尔可夫随机场图像模型的局部相关特性和最大后验概率估计，将粒子群优化算法应用于该模型，快速获得图像分割目标的全局最优解。实验数据表明该方法的高效性。