CT imaging is useful and ubiquitous. There is, however, a desire to reduce imaging artifacts, improve resolution, while reducing radiation. Iterative reconstruction algorithms have been proposed as one approach towards achieving these goals. In this paper we compare phantom images produced using commercial FBP-based reconstruction to three different iterative algorithms. We focus specifically on statistical characterizations of the noise, both at full radiation dose and at 50% dose. An iterative algorithm which segregates the image into two components (soft tissue and dense object), and imposes different constraints on these components, yielded better noise characteristics than ART, total variation, and FBP.