The use of Fourier domain model observer is challenged by iterative reconstruction (IR), because IR
algorithms are nonlinear and IR images have noise texture different from that of FBP. A modified Fourier
domain model observer, which incorporates nonlinear noise and resolution properties, has been proposed for
IR and needs to be validated with human detection performance. On the other hand, the spatial domain model
observer is theoretically applicable to IR, but more computationally intensive than the Fourier domain
method. The purpose of this study is to compare the modified Fourier domain model observer to the spatial
domain model observer with both FBP and IR images, using human detection performance as the gold
standard. A phantom with inserts of various low contrast levels and sizes was repeatedly scanned 100 times
on a third-generation, dual-source CT scanner at 5 dose levels and reconstructed using FBP and IR
algorithms. The human detection performance of the inserts was measured via a 2-alternative-forced-choice
(2AFC) test. In addition, two model observer performances were calculated, including a Fourier domain non-prewhitening
model observer and a spatial domain channelized Hotelling observer. The performance of these
two mode observers was compared in terms of how well they correlated with human observer performance.
Our results demonstrated that the spatial domain model observer correlated well with human observers across
various dose levels, object contrast levels, and object sizes. The Fourier domain observer correlated well with
human observers using FBP images, but overestimated the detection performance using IR images.