Low contrast detection tasks, such as the detection of subtle ground glass nodules, are low signal to noise (SNR) situations that can be greatly influenced by choice of reconstruction filter. The goal of this work is to examine tradeoffs in noise, resolution, and dose on the SNR of low contrast test objects, resembling spherical lung nodules, to potentially improve reconstruction filter selection for a given nodule detection task. To perform these experiments, the Modulation Transfer Function (MTF) was calculated for each reconstruction filter available. Next, simulated signal images were created using 2mm section thicknesses of 1 cm diameter spheres of varying contrast levels. The Noise Power Spectra (NPS) were then calculated for each reconstruction filter to be examined. The signal to noise metric used is the ideal Bayesian observer SNR metric, which takes into account the spatial correlations in noise introduced by the filter (and described by the NPS). The IBO SNR was calculated under a variety of reconstruction conditions: (a) varying mAs so that each reconstruction filter results in the same standard deviation; (b) constant mAs and varying reconstruction filter; (c) one reconstruction filter using varying mAs. These measurements provide an opportunity to examine the important tradeoffs in SNR with noise, resolution, and dose that occur with selection of a reconstruction filter and can potentially lead to a quantitative basis for filter selection, improving lesion detectability.