1 code implementation • 7 Mar 2023 • Haocheng Ju, Haimiao Zhang, Lin Li, Xiao Li, Bin Dong
Joint channel estimation and signal detection (JCESD) in wireless communication systems is a crucial and challenging task, especially since it inherently poses a nonlinear inverse problem.
no code implementations • 3 Nov 2022 • Ce Wang, Kun Shang, Haimiao Zhang, Shang Zhao, Dong Liang, S. Kevin Zhou
Experiments on the VerSe dataset demonstrate this ability of our sampling policy, which is difficult to achieve based on uniform sampling.
1 code implementation • 23 Dec 2021 • Hong Wang, Yuexiang Li, Haimiao Zhang, Deyu Meng, Yefeng Zheng
To alleviate these issues, in the paper, we construct a novel deep unfolding dual domain network, termed InDuDoNet+, into which CT imaging process is finely embedded.
no code implementations • 21 Nov 2021 • Ce Wang, Kun Shang, Haimiao Zhang, Qian Li, Yuan Hui, S. Kevin Zhou
While Computed Tomography (CT) reconstruction from X-ray sinograms is necessary for clinical diagnosis, iodine radiation in the imaging process induces irreversible injury, thereby driving researchers to study sparse-view CT reconstruction, that is, recovering a high-quality CT image from a sparse set of sinogram views.
1 code implementation • 11 Sep 2021 • Hong Wang, Yuexiang Li, Haimiao Zhang, Jiawei Chen, Kai Ma, Deyu Meng, Yefeng Zheng
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 imaging geometry constraint is not fully embedded into the network during training, leaving room for further performance improvement; 2) the model interpretability is lack of sufficient consideration.
no code implementations • 9 Mar 2021 • Ce Wang, Haimiao Zhang, Qian Li, Kun Shang, Yuanyuan Lyu, Bin Dong, S. Kevin Zhou
More importantly, we show that using such a sinogram extrapolation module significantly improves the generalization capability of the model on unseen datasets (e. g., COVID-19 and LIDC datasets) when compared to existing approaches.
no code implementations • 30 May 2020 • Haimiao Zhang, Baodong Liu, Hengyong Yu, Bin Dong
Other components, such as image priors and hyperparameters, are kept as the original design.
no code implementations • 23 Jun 2019 • Haimiao Zhang, Bin Dong
More recently, as more data and computation resources are made available, deep learning based models (or deep models) pushed data-driven modeling to the extreme where the models are mostly based on learning with minimal human designs.
no code implementations • 3 Dec 2018 • Haimiao Zhang, Bin Dong, Baodong Liu
CT image reconstruction from incomplete data, such as sparse views and limited angle reconstruction, is an important and challenging problem in medical imaging.