249 citations · 280 across the 10 of their papers we have counts for
10 papers
Physics-informed Score-based Diffusion Model for Limited-angle Reconstruction of Cardiac Computed Tomography
Shuo Han, Yongshun Xu, Dayang Wang +5
Cardiac computed tomography (CT) has emerged as a major imaging modality for the diagnosis and monitoring of cardiovascular diseases. High temporal resolution is essential to ensur…
LoMAE: Low-level Vision Masked Autoencoders for Low-dose CT Denoising
Dayang Wang, Yongshun Xu, Shuo Han +4
Low-dose computed tomography (LDCT) offers reduced X-ray radiation exposure but at the cost of compromised image quality, characterized by increased noise and artifacts. Recently,…
DSFNet: Dual-GCN and Location-fused Self-attention with Weighted Fast Normalized Fusion for Polyps Segmentation
Juntong Fan, Debesh Jha, Tieyong Zeng +1
Polyps segmentation poses a significant challenge in medical imaging due to the flat surface of polyps and their texture similarity to surrounding tissues. This similarity gives ri…
Simulation of Arbitrary Level Contrast Dose in MRI Using an Iterative Global Transformer Model
Dayang Wang, Srivathsa Pasumarthi, Greg Zaharchuk +1
Deep learning (DL) based contrast dose reduction and elimination in MRI imaging is gaining traction, given the detrimental effects of Gadolinium-based Contrast Agents (GBCAs). Thes…
Masked Autoencoders for Low dose CT denoising
Dayang Wang, Yongshun Xu, Shuo Han +1
Low-dose computed tomography (LDCT) reduces the X-ray radiation but compromises image quality with more noises and artifacts. A plethora of transformer models have been developed r…
SQ-Swin: a Pretrained Siamese Quadratic Swin Transformer for Lettuce Browning Prediction
Dayang Wang, Boce Zhang, Yongshun Xu +2
Packaged fresh-cut lettuce is widely consumed as a major component of vegetable salad owing to its high nutrition, freshness, and convenience. However, enzymatic browning discolora…
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…
Manifoldron: Direct Space Partition via Manifold Discovery
Dayang Wang, Feng-Lei Fan, Bo-Jian Hou +6
A neural network with the widely-used ReLU activation has been shown to partition the sample space into many convex polytopes for prediction. However, the parameterized way a neura…
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…
On a Sparse Shortcut Topology of Artificial Neural Networks
Fenglei Fan, Dayang Wang, Hengtao Guo +4
In established network architectures, shortcut connections are often used to take the outputs of earlier layers as additional inputs to later layers. Despite the extraordinary effe…