Statistical iterative reconstruction and post-log data restoration algorithms for CT noise reduction have been widely
studied and these techniques have enabled us to reduce irradiation doses while maintaining image qualities. In low dose
scanning, electronic noise becomes obvious and it results in some non-positive signals in raw measurements. The nonpositive
signal should be converted to positive signal so that it can be log-transformed. Since conventional conversion
methods do not consider local variance on the sinogram, they have difficulty of controlling the strength of the filtering.
Thus, in this work, we propose a method to convert the non-positive signal to the positive signal by mainly controlling
the local variance. The method is implemented in two separate steps. First, an iterative restoration algorithm based on
penalized weighted least squares is used to mitigate the effect of electronic noise. The algorithm preserves the local mean
and reduces the local variance induced by the electronic noise. Second, smoothed raw measurements by the iterative
algorithm are converted to the positive signal according to a function which replaces the non-positive signal with its local
mean. In phantom studies, we confirm that the proposed method properly preserves the local mean and reduce the
variance induced by the electronic noise. Our technique results in dramatically reduced shading artifacts and can also
successfully cooperate with the post-log data filter to reduce streak artifacts.