2 citations · 5 across the 4 of their papers we have counts for
4 papers
Multi-layer Clustering-based Residual Sparsifying Transform for Low-dose CT Image Reconstruction
Xikai Yang, Zhishen Huang, Yong Long +1
The recently proposed sparsifying transform models incur low computational cost and have been applied to medical imaging. Meanwhile, deep models with nested network structure revea…
Two-layer clustering-based sparsifying transform learning for low-dose CT reconstruction
Xikai Yang, Yong Long, Saiprasad Ravishankar
Achieving high-quality reconstructions from low-dose computed tomography (LDCT) measurements is of much importance in clinical settings. Model-based image reconstruction methods ha…
Multi-layer Residual Sparsifying Transform (MARS) Model for Low-dose CT Image Reconstruction
Xikai Yang, Yong Long, Saiprasad Ravishankar
Signal models based on sparse representations have received considerable attention in recent years. On the other hand, deep models consisting of a cascade of functional layers, com…
Learned Multi-layer Residual Sparsifying Transform Model for Low-dose CT Reconstruction
Xikai Yang, Xuehang Zheng, Yong Long +1
Signal models based on sparse representation have received considerable attention in recent years. Compared to synthesis dictionary learning, sparsifying transform learning involve…