A strategy for reduction of streak artifacts in low-dose CT

Streak artifacts have been one of the major classes of image artifacts resulting from excessive quantum noise in low-dose x-ray CT. It has been shown that, to treat the noise in low-dose CT more accurately, both the analysis of the noise properties of the projection data and the development of a corresponding efficient filtering method are necessary. From our previous analysis of the calibrated low-dose CT projection data, it was clearly seen that the data could be regarded as approximately Gaussian distributed with nonlinear signal-dependent variance. Based on this observation, a penalized weighted least square (WLS) statistic framework was chosen for an optimal solution. In this work, we further incorporated a novel a priori idea into the framework, which can accurately preserve more information in high-noise regions with a significant reduction of the streak artifacts. This new penalty term was directly calculated from the sinogram. The method was tested by experimental data acquired at 120 kVp and 10 mA protocols, demonstrating a significant reduction on streak artifacts and noise suppression without sacrificing the spatial resolution.