46 citations · 64 across the 11 of their papers we have counts for
4 papers · 1 filter
MEPNet: A Model-Driven Equivariant Proximal Network for Joint Sparse-View Reconstruction and Metal Artifact Reduction in CT Images
Hong Wang, Minghao Zhou, Dong Wei +2
Sparse-view computed tomography (CT) has been adopted as an important technique for speeding up data acquisition and decreasing radiation dose. However, due to the lack of sufficie…
Orientation-Shared Convolution Representation for CT Metal Artifact Learning
Hong Wang, Qi Xie, Yuexiang Li +3
During X-ray computed tomography (CT) scanning, metallic implants carrying with patients often lead to adverse artifacts in the captured CT images and then impair the clinical trea…
Adaptive Convolutional Dictionary Network for CT Metal Artifact Reduction
Hong Wang, Yuexiang Li, Deyu Meng +1
Inspired by the great success of deep neural networks, learning-based methods have gained promising performances for metal artifact reduction (MAR) in computed tomography (CT) imag…
InDuDoNet: An Interpretable Dual Domain Network for CT Metal Artifact Reduction
Hong Wang, Yuexiang Li, Haimiao Zhang +4
For the task of metal artifact reduction (MAR), although deep learning (DL)-based methods have achieved promising performances, most of them suffer from two problems: 1) the CT ima…