37 citations · 100 across the 12 of their papers we have counts for
6 papers · 1 filter
A Hybrid Deep Feature-Based Deformable Image Registration Method for Pathology Images
Chulong Zhang, Yuming Jiang, Na Li +9
Pathologists need to combine information from differently stained pathology slices for accurate diagnosis. Deformable image registration is a necessary technique for fusing multi-m…
Metal Artifact Reduction in 2D CT Images with Self-supervised Cross-domain Learning
Lequan Yu, Zhicheng Zhang, Xiaomeng Li +3
The presence of metallic implants often introduces severe metal artifacts in the X-ray CT images, which could adversely influence clinical diagnosis or dose calculation in radiatio…
TransCT: Dual-path Transformer for Low Dose Computed Tomography
Zhicheng Zhang, Lequan Yu, Xiaokun Liang +2
Low dose computed tomography (LDCT) has attracted more and more attention in routine clinical diagnosis assessment, therapy planning, etc., which can reduce the dose of X-ray radia…
CT Super Resolution via Zero Shot Learning
Zhicheng Zhang, Shaode Yu, Wenjian Qin +3
Computed Tomography (CT) is an advanced imaging technology used in many important applications. Here we present a deep-learning (DL) based CT super-resolution (SR) method that can…
Noise2Context: Context-assisted Learning 3D Thin-layer Low Dose CT Without Clean Data
Zhicheng Zhang, Xiaokun Liang, Wei Zhao +1
Computed tomography (CT) has played a vital role in medical diagnosis, assessment, and therapy planning, etc. In clinical practice, concerns about the increase of X-ray radiation e…
Deep Sinogram Completion with Image Prior for Metal Artifact Reduction in CT Images
Lequan Yu, Zhicheng Zhang, Xiaomeng Li +1
Computed tomography (CT) has been widely used for medical diagnosis, assessment, and therapy planning and guidance. In reality, CT images may be affected adversely in the presence…