〔Abstract〕 Obj ective To evaluate the feasibility of various strength levels of deep learning image reconstruction (DLIR) algorithms for improving non-contrast abdominal CT image quality at ultra-low radiation doses, by comparing ultra-low-dose DLIR images with low-dose filtered back projection FBP images. Methods A prospective collection of 85 patients undergoing non-contrast abdominal CT scans was performed, and a self-controlled study method was employed to conduct low-dose (LD) group and ultra-low-dose (ULD) group scans. The LD group used a noise index of 10 and employed FBP for image reconstruction (LD-FBP group). The ULD group used a noise index of 30 and employed DLIR at different levels (low, medium, high), resulting in three subgroups of reconstructed images: ULD-DLIR-L, ULD-DLIR-M, and ULD-DLIR-H. For each group, CT values, standard deviation (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were measured and calculated for the liver, spleen, kidneys, aorta, psoas major, and subcutaneous fat. Effective dose (ED) was also recorded. Two radiologists independently performed subjective evaluations of image quality using a 5-point scale. ResultsCompared with the LD-FBP group, the ULD-DLIR-L group showed significantly lower SNR and CNR values in the liver, spleen, kidneys, aorta, and psoas major ( P<0.001), while the ULD-DLIR-H group exhibited significantly higher values ( P<0.001). The difference of SNR and CNR values for the ULD-DLIR-M group showed no statistically significant difference. For subjective evaluation, the scores of the ULD-DLIR-L and ULD-DLIR-M groups were lower than those of the LD-FBP group, while there was no statistically significant difference in scores between the ULD-DLIR-H group and the LD-FBP group. The ED value of the ULD group was approximately 88% lower than that of the LD group. ConclusionCompared with the LD-FBP group, the ULD-DLIR-H group significantly reduces SD values while increasing SNR and CNR values, effectively improving the image quality of non-contrast abdominal CT scans.