Motion artifact suppression is a very difficult problem in magnetic resonance imaging.Patient motion including physiological motion and physical motion causes the phase distortion in the collected signals and induces motion artifacts in the reconstructed image for the 2-dimension Fourier Transform imaging method.As the result of these motion artifacts

the quality of image is degraded and the precise orientation to the focus in clinic is affected.A motion artifact reduction method based on genetic algorithm is presented in this paper.Genetic algorithm has the characteristics of parallel

randomicity and adaptive matching pursuit.In the image reconstruction

before taking the inverse Fourier Transform

the phase distortion of K-space signals is compensated step by step through searching for the optimizing phase values.The experiments show that the phase distortion can be estimated using the information implied by the motion artifacts and a significant amount of motion artifact suppression is achieved.Using this algorithm

the corrected image is satisfied when motion is slight

and the quality of the image is still improved greatly in the conditions of noise and significant motion comparing with using classical iterative algorithms.