A low-dose CT reconstruction method using sub-pixel anisotropic diffusion

TANG Shizhou; SU Ruolan; LI Shuting; LAI Zhenzhen; HUANG Jinhong; NIU Shanzhou

doi:10.12122/j.issn.1673-4254.2025.01.19

Abstract：Objective We present a new low-dose CT reconstruction method using sub-pixel and anisotropic diffusion.Methods The sub-pixel intensity values and their second-order differences were obtained using linear interpolation techniques,and the new gradient information was then embedded into an anisotropic diffusion process,which was introduced into a penalty-weighted least squares model to reduce the noise in low-dose CT projection data.The high-quality CT image was finally reconstructed using the classical filtered back-projection(FBP)algorithm from the estimated data.Results In the Shepp-Logan phantom experiments,the structural similarity(SSIM)index of the CT image reconstructed by the proposed algorithm,as compared with FBP,PWLS-Gibbs and PWLS-TV algorithms,was increased by 28.13％,5.49％,and 0.91％,the feature similarity(FSIM)index was increased by 21.08％,1.78％,and 1.36％,and the root mean square error(RMSE)was reduced by 69.59％,18.96％,and 3.90％,respectively.In the digital XCAT phantom experiments,the SSIM index of the CT image reconstructed by the proposed algorithm,as compared with FBP,PWLS-Gibbs and PWLS-TV algorithms,was increased by 14.24％,1.43％and 7.89％,the FSIM index was increased by 9.61％,1.78％and 5.66％,and the RMSE was reduced by 26.88％,9.41％and 18.39％,respectively.In clinical experiments,the SSIM index of the image reconstructed using the proposed algorithm was increased by 19.24％,15.63％and 3.68％,the FSIM index was increased by 4.30％,2.92％and 0.43％,and the RMSE was reduced by 44.60％,36.84％and 15.22％in comparison with FBP,PWLS-Gibbs and PWLS-TV algorithms,respectively.Conclusion The proposed method can effectively reduce the noises and artifacts while maintaining the structural details in low-dose CT images.