Since the introduction of ASiR, its potential in noise reduction has been reported in various clinical applications.
However, the influence of different scan and reconstruction parameters on the trade off between ASiR's blurring
effect and noise reduction in low contrast imaging has not been fully studied. Simple measurements on low
contrast images, such as CNR or phantom scores could not explore the nuance nature of this problem. We
tackled this topic using a method which compares the performance of ASiR in low contrast helical imaging
based on an assumed filter layer on top of the FBP reconstruction. Transfer functions of this filter layer were
obtained from the noise power spectra (NPS) of corresponding FBP and ASiR images that share the same scan
and reconstruction parameters. 2D transfer functions were calculated as sqrt[NPSASiR(u, v)/NPSFBP(u, v)].
Synthesized ACR phantom images were generated by filtering the FBP images with the transfer functions of
specific (FBP, ASiR) pairs, and were compared with the ASiR images. It is shown that the transfer functions
could predict the deterministic blurring effect of ASiR on low contrast objects, as well as the degree of noise
reductions. Using this method, the influence of dose, scan field of view (SFOV), display field of view (DFOV),
ASiR level, and Recon Mode on the behavior of ASiR in low contrast imaging was studied. It was found that
ASiR level, dose level, and DFOV play more important roles in determining the behavior of ASiR than the other