Noises and artifacts are introduced to medical images in the process of acquisit ion and transmission,which causes image degradation and further seriously affect s the clinical diagnoses.Therefore,in order to solve this problem,a medical imag es enhancement method based on shearlet transformation and improved gamma correctio n is proposed in this paper.First,the original image is decomposed into the shearlet domain with low-frequency component and high-frequency component.Then,the improved gamma correction is adopted for the low-frequency component to improve the global contrast of the image,and an adap tive threshold method is used for the removal of high-frequency image noise.Finally,the improved fu zzy contrast is used to enhance the details of the reconstruct image which is obtained by the sh earlet inverse transformation.The experimental results show that the proposed method is super ior to other comparative methods in peak signal to noise ratio (PSNR) ,structural similarity (SSIM) and mean absolute error (MAE),especially the PSNR is increased observably.These objective criterions indicate that the proposed method not only can remove image noise efficiently, but also significantly improve the contrast of image.In the subjective aspect, the proposed method can get better visual effect than other methods.