The current IEC standard method for characterizing noise in CT scanners is based on the pixel standard deviation of the CT image of a water-equivalent uniform phantom. However, the standard deviation does not account for correlations in the noise, potentially generating misleading results about image quality. With this paper we investigate a method for estimating the Fourier based noise power spectrum (NPS) for the characterization of noise in CT, for CT scanners with linear, non-adaptive reconstruction algorithms. The IEC currently evaluates the deterministic properties of CT scanners with the Fourier based modulation transfer function (MTF). By accounting for the spatial correlations in both the stochastic and deterministic description of an imaging system, the system signal-to-noise ratio (SNR) can be determined more accurately. In this paper we investigate a method for estimating the MTF and the NPS of a CT scanner in the axial plane. Furthermore, we present examples of the Fourier SNR calculated from the MTF and the NPS in order to demonstrate that it gives more reasonable results than the pixel SNR. The MTF was estimated by following methods available in current literature. For the characterization of noise we used a standard water phantom, while for the point spread function (PSF) we used a tungsten wire phantom in air. Images were taken at four different source current settings and reconstructed with four different lters. We showed that the pixel SNR ranks the reconstruction lters differently from the Fourier SNR.