Electrical impedance tomography (EIT) has many advantages in practical application，but image reconstruction of EIT is a highly ill-posed, non-linear inverse problem. Newton-Raphson algorithms are widely used in EIT, which have to calculate the Jacobian matrix and use regularization techniques. So this kind of algorithms is complex and less stable. To address the problem, a new static image reconstruction method for EIT is proposed based on particle swarm optimization (PSO) algorithm. PSO is a population-based, adaptive search optimization technique. It is simple in concept, few in parameters, quick in convergence and easy in implementation. The model of EIT forward problem is given and some appropriate improvements in PSO are made to accommodate the solution of EIT. Compared with Newton-Raphson(MNR) algorithms, PSO only uses an iterative processing to get the best solution instead of using a complicated Jacobian matrix. The experimental results indicate that using PSO-based algorithm to solve image reconstruction of EIT, the position of mutation region is more accurate and graphics space resolution is much higher.