Abstract: Objective: This study aimed to investigate the value of different iterative reconstruction algorithms for orbital computed tomography (CT). Methods: Orbital CT data from 31 patients were retrospectively collected from January to March 2024 at Beijing Tongren Hospital Capital Medical University. The images were reconstructed using both the Hybrid Iterative Reconstruction Algorithm (iDose⁴) and Iterative Model Reconstruction (IMR) techniques for the bone and standard algorithms. The average CT number, standard deviation (SD) of noise , signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and image quality scores of different reconstruction algorithms were compared. Randomized block variance analysis was used to compare differences in objective indicators, and the Wilcoxon signed-rank test for related samples was used to compare differences in subjective scores. Results: The differences in the CT number, noise, SNR, and CNR of images reconstructed using different standard algorithms were statistically significant. Compared with iDose⁴, the noise reduction of the IMR standard algorithm-reconstructed images ranged from 25% to 67%, with an SNR increase of 1.3~1.5 times, and a CNR increase of 2 to 3 times. Compared with iDose⁴, the noise reduction of the IMR bone algorithm-reconstructed images ranged from 70% to 96%, with an SNR increase of 5~15 times and a CNR increase of 4~31 times. The differences in the image quality scores of the images reconstructed using different bone and standard algorithms were statistically significant. The highest scores were 5 (5, 5) for the iDose⁴ Level 3 Y-Detail (YD) bone algorithm group and 5 (4, 5) for the IMR Level 1 Brain Routine standard algorithm group. The consistency of the scores evaluated by the two observers was strong, with weighted kappa coefficients ranging from 0.644 to 1. Conclusion: In orbital CT, we recommend using a hybrid iterative reconstruction technique (iDose⁴ Level 3) to reconstruct bone algorithm images and the iterative model reconstruction technique (IMR-Level 1) to reconstruct standard algorithm images.