20 citations · 22 across the 9 of their papers we have counts for
6 papers · 1 filter
Interactive Gadolinium-Free MRI Synthesis: A Transformer with Localization Prompt Learning
Linhao Li, Changhui Su, Yu Guo +3
Contrast-enhanced magnetic resonance imaging (CE-MRI) is crucial for tumor detection and diagnosis, but the use of gadolinium-based contrast agents (GBCAs) in clinical settings rai…
Realistic Restorer: artifact-free flow restorer(AF2R) for MRI motion artifact removal
Jiandong Su, Kun Shang, Dong Liang
Motion artifact is a major challenge in magnetic resonance imaging (MRI) that severely degrades image quality, reduces examination efficiency, and makes accurate diagnosis difficul…
RetinexFlow for CT metal artifact reduction
Jiandong Su, Ce Wang, Yinsheng Li +2
Metal artifacts is a major challenge in computed tomography (CT) imaging, significantly degrading image quality and making accurate diagnosis difficult. However, previous methods e…
Active CT Reconstruction with a Learned Sampling Policy
Ce Wang, Kun Shang, Haimiao Zhang +3
Computed tomography (CT) is a widely-used imaging technology that assists clinical decision-making with high-quality human body representations. To reduce the radiation dose posed…
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…