## 4 Discussion
On average, they found a noise reduction of 37% (ASiR-V 50%) and 72% (ASiR-V 100%) relative to FBP. Another phantom study by [PERSON] and [PERSON] [55] compared the noise levels of FBP-, ASiR-V-, and ASiR-reconstructed images (blending levels of 40%, 60%, and 100%) acquired on two different CT scanners (i.e., ASiR-V- and ASiR-reconstructed images were not obtained from the same sinogram data). Specifically, this study assessed the effect of convolution kernel (standard, soft, and bone), slice thickness, and radiation exposure on noise level for all the used reconstruction algorithms. When compared with FBP, ASiR-Vshowed a greater noise (estimated as the SD of CT numbers within a square ROI in a homogeneous phantom) reduction than ASiR with noise reduction values of 12%-28%, 18%-41%, and 29%-64% for ASiR-V 40%, 60%, and 100%, respectively. For both ASiR-V and ASiR, noise reduction relative to FBP was almost independent of dose exposure. To the best of our knowledge, this is the first study that performed, for different blending levels of reconstruction and contrast objects, a voxel-based assessment of noise properties in CT imaging with ASiR-V and ASiR algorithms as compared with conventional FBP. This approach, which can allow a better characterization of noise properties in CT imaging with IR algorithms, is based on spatial noise maps (Figures 1 and 2). In general, we found that, when compared with FBP, ASiR-V presents a greater noise reduction than ASiR for a homogeneous medium, except for the lowest blending level of 20% (Figure 6). In particular, the noise reduction value ranged up to 52.9% and 63.7% for pure ASiR and pure ASiR-V, respectively. This finding has also been confirmed for various contrast objects (i.e., PMP, LDPE, polystyrene, acrylic, Delrin) (Figure 7) with noise reduction values rather independent of contrast objects and ranging up to approximately 50% and 60% for pure ASiR and pure ASiR-V, respectively. On the other hand, for higher contrast objects (i.e., air and Teflon) and all blending levels, ASiR-V showed a lower noise reduction capability than ASiR. In this case, the noise reduction values of ASiR-V-/ASiR-reconstructed images were lower and ranged up to 33.8%/39.9% and 31.2%/35.5% for air and Teflon contrast objects, respectively. In this work, unlike a few previous studies on the characterization of noise in CT imaging with ASiR-V and ASiR [50; 51; 52; 54; 55], voxelwise noise maps allow an assessment of the spatial uniformity of noise, which might be affected by the nonlinearity and non-stationarity effects of IR algorithms. For the homogeneous medium, FBP-reconstructed images showed a rather low level of the spatial nonuniformity of noise with an _NUI_ value of 5.2%. The _NUI_ values of ASiR-V- and ASiR-reconstructed CT images were lower than the _NUI_ value of FBP-reconstructed images and slightly decreased with an increasing blending level of reconstruction (Figure 5a). This could be partly associated with a shift of noise power spectrum curves toward lower spatial frequencies, which has been observed for CT imaging with ASiR-V and ASiR mostly at higher blending levels of reconstruction [24; 29; 35; 55]. Notably, for the nonhomogeneous medium with contrast objects, both ASiR-V and ASiR-reconstructed CT images showed _NUI_ values greater than the _NUI_ value of FBP-reconstructed CT images (approximately 7%), increasing with the blending level of reconstruction (Figure 5b). In particular, the _NUI_ values of CT imaging with pure ASiR-V and pure ASiR were approximately three and two times, respectively, that of CT imaging with FBP. This is likely to derive from a noise reduction capability of ASiR-V and ASiR reconstruction algorithms that does not seem so effective at the boundary between different media (Figures 2 and 4). While this effect has been reported for other IR algorithms [68; 69; 70], no previous study has observed it for CT imaging with ASiR-V and ASiR.