249 citations · 275 across the 4 of their papers we have counts for
4 papers
PDS-MAR: a fine-grained Projection-Domain Segmentation-based Metal Artifact Reduction method for intraoperative CBCT images with guidewires
Tianling Lyu, Zhan Wu, Gege Ma +5
Since the invention of modern CT systems, metal artifacts have been a persistent problem. Due to increased scattering, amplified noise, and insufficient data collection, it is more…
CTformer: Convolution-free Token2Token Dilated Vision Transformer for Low-dose CT Denoising
Dayang Wang, Fenglei Fan, Zhan Wu +3
Low-dose computed tomography (LDCT) denoising is an important problem in CT research. Compared to the normal dose CT (NDCT), LDCT images are subjected to severe noise and artifacts…
TED-net: Convolution-free T2T Vision Transformer-based Encoder-decoder Dilation network for Low-dose CT Denoising
Dayang Wang, Zhan Wu, Hengyong Yu
Low dose computed tomography is a mainstream for clinical applications. How-ever, compared to normal dose CT, in the low dose CT (LDCT) images, there are stronger noise and more ar…
Dual-energy CT imaging from single-energy CT data with material decomposition convolutional neural network
Tianling Lyu, Zhan Wu, Yikun Zhang +3
Dual-energy computed tomography (DECT) is of great significance for clinical practice due to its huge potential to provide material-specific information. However, DECT scanners are…