Search Results for author:
Found 2 papers, 0 papers with code
A Two-Step Framework for Multi-Material Decomposition of Dual Energy Computed Tomography from Projection Domain
Deep learning (DL) methods have shown promise to improve the MMD performance, but typical approaches of conducing DL-MMD in the image domain fail to fully utilize projection information or under iterative setup are computationally inefficient in both training and prediction.
To what extent can Plug-and-Play methods outperform neural networks alone in low-dose CT reconstruction
The Plug-and-Play (PnP) framework was recently introduced for low-dose CT reconstruction to leverage the interpretability and the flexibility of model-based methods to incorporate various plugins, such as trained deep learning (DL) neural networks.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
