196 citations · 232 across the 7 of their papers we have counts for
8 papers
Incomplete Data Multi-Source Static Computed Tomography Reconstruction with Diffusion Priors and Implicit Neural Representation
Ziju Shen, Haimiao Zhang, Bin Dong +3
The dose of X-ray radiation and the scanning time are crucial factors in computed tomography (CT) for clinical applications. In this work, we introduce a multi-source static CT ima…
A Comparative Study of Deep Learning and Iterative Algorithms for Joint Channel Estimation and Signal Detection in OFDM Systems
Haocheng Ju, Haimiao Zhang, Lin Li +2
Joint channel estimation and signal detection (JCESD) is crucial in orthogonal frequency division multiplexing (OFDM) systems, but traditional algorithms perform poorly in low sign…
DuDoTrans: Dual-Domain Transformer Provides More Attention for Sinogram Restoration in Sparse-View CT Reconstruction
Ce Wang, Kun Shang, Haimiao Zhang +3
While Computed Tomography (CT) reconstruction from X-ray sinograms is necessary for clinical diagnosis, iodine radiation in the imaging process induces irreversible injury, thereby…
Improving Generalizability in Limited-Angle CT Reconstruction with Sinogram Extrapolation
Ce Wang, Haimiao Zhang, Qian Li +4
Computed tomography (CT) reconstruction from X-ray projections acquired within a limited angle range is challenging, especially when the angle range is extremely small. Both analyt…
MetaInv-Net: Meta Inversion Network for Sparse View CT Image Reconstruction
Haimiao Zhang, Baodong Liu, Hengyong Yu +1
X-ray Computed Tomography (CT) is widely used in clinical applications such as diagnosis and image-guided interventions. In this paper, we propose a new deep learning based model f…
A Review on Deep Learning in Medical Image Reconstruction
Haimiao Zhang, Bin Dong
Medical imaging is crucial in modern clinics to guide the diagnosis and treatment of diseases. Medical image reconstruction is one of the most fundamental and important components…
JSR-Net: A Deep Network for Joint Spatial-Radon Domain CT Reconstruction from incomplete data
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. This work proposes…
A Re-weighted Joint Spatial-Radon Domain CT Image Reconstruction Model for Metal Artifact Reduction
Haimiao Zhang, Bin Dong, Baodong Liu
High density implants such as metals often lead to serious artifacts in the reconstructed CT images which hampers the accuracy of image based diagnosis and treatment planning. In t…