57 citations · 84 across the 9 of their papers we have counts for
9 papers
Unsupervised CT Metal Artifact Reduction by Plugging Diffusion Priors in Dual Domains
Xuan Liu, Yaoqin Xie, Songhui Diao +2
During the process of computed tomography (CT), metallic implants often cause disruptive artifacts in the reconstructed images, impeding accurate diagnosis. Several supervised deep…
Diffusion Probabilistic Priors for Zero-Shot Low-Dose CT Image Denoising
Xuan Liu, Yaoqin Xie, Jun Cheng +3
Denoising low-dose computed tomography (CT) images is a critical task in medical image computing. Supervised deep learning-based approaches have made significant advancements in th…
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…
Investigation of physical dose enhancement in core-shell magnetic gold nanoparticles with TOPAS simulation
Xiaohan Xu, Yaoqin Xie, Jianan Wu +3
The application of metal nanoparticles as sensitization materials is a common strategy that is used to study dose enhancement in radiotherapy. Recent in vitro tests have revealed t…
Elastic Net based Feature Ranking and Selection
Shaode Yu, Haobo Chen, Hang Yu +5
Feature selection is important in data representation and intelligent diagnosis. Elastic net is one of the most widely used feature selectors. However, the features selected are de…
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…
A Matlab Toolbox for Feature Importance Ranking
Shaode Yu, Zhicheng Zhang, Xiaokun Liang +4
More attention is being paid for feature importance ranking (FIR), in particular when thousands of features can be extracted for intelligent diagnosis and personalized medicine. A…
Using Edge-Preserving Algorithm with Non-local Mean for Significantly Improved Image-Domain Material Decomposition in Dual Energy CT
Wei Zhao, Tianye Niu, Lei Xing +6
Increased noise is a general concern for dual-energy material decomposition. Here, we develop an image-domain material decomposition algorithm for dual-energy CT (DECT) by incorpor…
Performance Evaluation of Edge-Directed Interpolation Methods for Images
Shaode Yu, Qingsong Zhu, Shibin Wu +1
Many interpolation methods have been developed for high visual quality, but fail for inability to preserve image structures. Edges carry heavy structural information for detection,…