Abstract:In view of the potential risks of X-ray radiation to patients,the issue of reducing the radiation dose exposed by patients has attracted widespread attention among scientific researchers.This paper proposes a new image reconstruction algorithm based on nonlinear compressed sensing for the reconstruction scheme of sparse angle scan CT images.In this algorithm,the nonlinear filter is added to the regularization term of the cost function,and the joint bilateral filter is added to the reconstruction process to further improve the image quality.At the same time,the proximal point algorithm in the field of convex optimization is used to minimize the cost function and construct a row acceleration iterative algorithm.In the experiment,root mean square error (RMSE)and peak signal-to-noise ratio(PSNR)were selected as evaluation indexes,and the new algorithm was compared with the three algorithms proposed before.The peak signal to noise ratio is increased by 5.75~6.33 dB,and the root-mean-square erroris reduced by 0.002~0.023.The results of digital image model and actual clinical abdominal image reconstruction show that the new algorithm can effectively remove the artifact noise in the image while preserving the image details to the maximum extent.