Research of Sparse Representation Medical CT Image Denoising  using Pixels Classification by Fuzzy Neural Network

 In medical CT imaging procedure, the unavoidable noise, results in image degradation, and has an influence on clinical diagnosis. Therefore, the study of medical CT image denoising method has great significance in the diagnosis and treatment services. In this paper, combined with the idea of image segmentation, image pixels are divided into edge region, texture smooth area using fuzzy neural network. Threshold denoising was present in wavelet sparse representation for different images. It better preserves the details of medical CT image. Experimental results show that The algorithm can effectively remove noise. The peak signal to noise ratio (PSNR) and structural similarity index (SSIM) have been improved. It well preserved edge details of the CT image.