Training a cnn with pseudo ground truth for ct artifact reduction

A convolutional neural network (CNN) system comprising:

• an estimated ground truth apparatus configured to generate an estimated ground truth image based, at least in part, on an initial CT image, the initial CT image comprising an artifact;
• feature addition circuitry configured to add a respective feature to each of a number, N, copies of the estimated ground truth image to create the number, N, initial training images;
• a first computed tomography (CT) simulation circuitry configured to generate a plurality of simulated training CT images based, at least in part, on at least some of the N initial training images, each of at least some of the plurality of simulated training CT images containing at least one respective simulated artifact;
• a first artifact reduction circuitry configured to generate a plurality of input training CT images based, at least in part, on the simulated training CT images;
• and
• a CNN training circuitry configured to train the CNN based, at least in part, on the input training CT images and based, at least in part, on the initial training images.