Half2Half: deep neural network based CT image denoising without independent reference data

Reducing radiation dose of x-ray computed tomography (CT) and thereby decreasing the potential risk to patients are desirable in CT imaging. Deep neural network (DNN) has been proposed to reduce noise in low-dose CT (LdCT) images and showed promising results. However, most existing DNN-based methods require training a neural network using high-quality CT images as the reference. Lack of high-quality reference data has therefore been the...