In this project, we investigate the use of deep learning to remove noise from clinical CT images. We aim to reduce the noise content more than in iterative reconstruction techniques. However, we aim to include known operations into the learning pprocesses, to denoise more accurately. We also aim to keep the number of free parameters low, for future regulatory approval for use in clinical settings.