OBJECTIVE: To investigate the impact of two reconstruction techniques, Filtered Back Projection (FBP) and Clear View (CV) iterative algorithm, on the image quality of low-dose thin-slice chest CT. METHODS: A retrospective study of 42 patients undergoing low-dose chest CT at Mzuzu Central Hospital from Feb-Apr 2024 used automatic tube current modulation at 120 kV Raw data were reconstructed with FBP, 20% CV, 40% CV, 60% CV, and 80% CV, with 1 mm slice thickness and 0.625 mm spacing. Image noise, Signal-to-Noise Ratio (SNR), and Contrast-to-Noise Ratio (CNR) were measured, and image quality was rated on a 5-point scale for lung and mediastinal windows. Qualitative and quantitative parameters of the two different reconstruction algorithms in the five groups were comparatively analyzed. RESULTS: (1) Objective evaluation showed noise decreased in lung parenchyma, aorta, and erector spinae muscle with increasing CV weight. Mean noise reductions in lung parenchyma were 23.34% and 27.69% in 60% CV and 80% CV (P <
0.05). Aorta noise decreased by 23.43%, 37.16%, and 46.18% in 40% CV, 60% CV, and 80% CV (P <
0.05, P <
0.001, P <
0.001). Erector spinae muscle noise decreased by 35.91% and 44.78% in 60% CV and 80% CV (P <
0.05, P <
0.001). SNR and CNR were higher in CV groups than FBP. Among them, the differences in SNR between the 60% CV and 80% CV groups and the FBP group were statistically significant (P <
0.05). (2) Subjective scores for all groups were >
3, meeting diagnostic standards, with 60% CV yielding the highest lung and mediastinal window image quality (P <
0.05). CONCLUSION: Compared to FBP, CV iterative reconstruction reduces noise and improves chest CT image quality under low-dose conditions as the weight increases, with 60% CV showing optimal performance.