Noise propagation in SPECT images reconstructed using an iterative maximum-likelihood algorithm

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Abstract
The effects of photon noise in the emission projection data and uncertainty in the attenuation map on the image noise in attenuation-corrected SPECT images reconstructed using a maximum-likelihood expectation-maximization algorithm were investigated. Emission projection data of a physical Hoffman brain phantom and a thorax-like phantom were acquired from a prototype emission-transmission computed tomography (ETCT) scanner being developed at UCSF. Computer-simulated emission projection data from a head-like phantom and a thorax-like phantom were also obtained using a fan-beam geometry consistent with the ETCT system. The simulation assumed a 99Tcm source, included collimator blurring but ignored photon scatter. For each phantom, a region of interest (ROI) at the centre of the reconstructed image was chosen for the purpose of noise analysis. In all cases, the mean value (m) in the ROI approached a constant value after approximately 20 iterations. The standard deviation (sigma) generally increased with the number of iterations. The ratio (sigma/m) was found to be inversely proportional to the square root of the total detected counts and proportional to the relative uncertainty in the attenuation maps. These two noise components contributed independently towards the noise in the reconstructed image. In the ETCT system employing an x-ray tube for attenuation map acquisition, the uncertainty in the reconstructed radionuclide distribution is limited mainly by photon noise in the emission projection data. Our results are expected to be generally applicable to other emission-transmission systems, including those using external radionuclide sources for the acquisition of attenuation maps.