Streak Artifact Reduction using Convolutional Neural Network: Clinical Feasibility Study in Liver MR Imaging

Radial sampling enables free free-breathing abdominal MR imaging. Meanwhile, while it suffers from streak artifacts. We propose streak artifact reduction using convolutional neural network (SARC) which utilize Hough domain. In Hough domain, a streak becomes like a dot which is more localized compared with image domain. The network was trained in end-to-end manner. The SARC was show better image quality in objective image quality metrics and visual evaluation by a radiologist. SARC showed feasibility for clinical MR imaging.