iDose4 provides an innovative solution in which iterative processing
is performed in both the projection and image domains. The
reconstruction algorithm starts first with projection data where it
identifies and corrects the noisiest CT measurements – those with
very poor signal to noise ratio, or very low photon counts. Each
projection is examined for points that have likely resulted from very
noisy measurements using a model that includes the true photons
statistics. Through an iterative diffusion process, the noisy data is
penalized and edges are preserved. This process ensures that the
gradients of underlying structures are retained, thus preserving
spatial resolution while allowing a significant noise reduction. In
doing so, this process prevents the primary cause of low signal
streaks. Also, since the corrections are performed on the acquisition
data (unlogged projections); this method successfully prevents bias
error.