Efficient approximation of a neural filter for quantum noise removal in X-ray images

An efficient filter approximating the neural filter (NF) trained to remove quantum noise from X-ray images has been realized. A novel analysis method is proposed for making the characteristics of the trained NF clear. It analyses a nonlinear system with plural inputs by using its outputs when the specific input signals are fed to it. The experimental results have demonstrated that the approximate filter, which is realized by using the results of the analysis, is sufficient for approximation of the trained NF, and efficient at computational cost.