Abstract: This study investigated the application of filtered back-projection (FBP) and algebraic iterative reconstruction algorithms in CT imaging of nuclear fuel assemblies, with a focus on the impact of scan frame count, noise, and artifact correction on image quality. First, CT scan results for pressurized water reactor (PWR) nuclear fuel assemblies were simulated, and the image quality of FBP under varying scan frames was analyzed. The results indicated that image quality improved significantly with an increasing number of frames, with streak artifacts gradually diminishing. For common ring artifacts in CT images, bilateral filtering and Gaussian filtering were evaluated for correction effectiveness; it was found that bilateral filtering performed better in edge preservation than Gaussian filtering. Additionally, an iterative reconstruction algorithm was applied to images with background noise, confirming its inherent filtering capability and effectiveness in noise suppression. By adjusting the iteration step size (relaxation factor) and regularization parameters, image quality was further enhanced while preserving structural details. This study demonstrated that iterative algorithms were advantageous in noise and ring artifact suppression, though they were less effective detail preservation compared to FBP. These findings provided valuable references for high-precision CT imaging of nuclear fuel assemblies.