Hengyong Yu
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View article: Sparse-view CT Reconstruction via Implicit Neural Representation Learning Powered by Dual-Domain Vision Foundation Models
Sparse-view CT Reconstruction via Implicit Neural Representation Learning Powered by Dual-Domain Vision Foundation Models Open
View article: ILViT: An Inception-Linear Attention-Based Lightweight Vision Transformer for Microscopic Cell Classification
ILViT: An Inception-Linear Attention-Based Lightweight Vision Transformer for Microscopic Cell Classification Open
Microscopic cell classification is a fundamental challenge in both clinical diagnosis and biological research. However, existing methods still struggle with the complexity and morphological diversity of cellular images, leading to limited …
View article: ResPF: Residual Poisson Flow for Efficient and Physically Consistent Sparse-View CT Reconstruction
ResPF: Residual Poisson Flow for Efficient and Physically Consistent Sparse-View CT Reconstruction Open
Sparse-view computed tomography (CT) is a practical solution to reduce radiation dose, but the resulting ill-posed inverse problem poses significant challenges for accurate image reconstruction. Although deep learning and diffusion-based m…
View article: Patch-based dual-domain photon-counting CT data correction with residual-based WGAN-ViT
Patch-based dual-domain photon-counting CT data correction with residual-based WGAN-ViT Open
Objective. x-ray photon-counting detectors have recently gained popularity due to their capabilities in energy discrimination power, noise suppression, and resolution refinement. The latest extremity photon-counting computed tomography (PC…
View article: Co-Retention FeaturePyramid Network for Low-dose CTDenoising via Spatialand and Frequency Domain Learning
Co-Retention FeaturePyramid Network for Low-dose CTDenoising via Spatialand and Frequency Domain Learning Open
View article: ρ-NeRF: Leveraging Attenuation Priors in Neural Radiance Field for 3D Computed Tomography Reconstruction
ρ-NeRF: Leveraging Attenuation Priors in Neural Radiance Field for 3D Computed Tomography Reconstruction Open
This paper introduces \(\rho\)-NeRF, a self-supervised approach that sets a new standard in novel view synthesis (NVS) and computed tomography (CT) reconstruction by modeling a continuous volumetric radiance field enriched with physics-bas…
View article: $ρ$-NeRF: Leveraging Attenuation Priors in Neural Radiance Field for 3D Computed Tomography Reconstruction
$ρ$-NeRF: Leveraging Attenuation Priors in Neural Radiance Field for 3D Computed Tomography Reconstruction Open
This paper introduces $ρ$-NeRF, a self-supervised approach that sets a new standard in novel view synthesis (NVS) and computed tomography (CT) reconstruction by modeling a continuous volumetric radiance field enriched with physics-based at…
View article: Physics-Informed Score-Based Diffusion Model for Limited-Angle Reconstruction of Cardiac Computed Tomography
Physics-Informed Score-Based Diffusion Model for Limited-Angle Reconstruction of Cardiac Computed Tomography Open
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 ensure diagnostic accuracy. Limited-angle data acquisition can r…
View article: A Two-Stage Tone Mapping Network Based on Attention Mechanism for High Dynamic Range Images
A Two-Stage Tone Mapping Network Based on Attention Mechanism for High Dynamic Range Images Open
View article: Physics-informed Score-based Diffusion Model for Limited-angle Reconstruction of Cardiac Computed Tomography
Physics-informed Score-based Diffusion Model for Limited-angle Reconstruction of Cardiac Computed Tomography Open
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 ensure diagnostic accuracy. Limited-angle data acquisition can r…
View article: Hybrid U-Net and Swin-transformer network for limited-angle cardiac computed tomography
Hybrid U-Net and Swin-transformer network for limited-angle cardiac computed tomography Open
Objective. Cardiac computed tomography (CT) is widely used for diagnosis of cardiovascular disease, the leading cause of morbidity and mortality in the world. Diagnostic performance depends strongly on the temporal resolution of the CT ima…
View article: Passive Aggressive Ensemble for Online Portfolio Selection
Passive Aggressive Ensemble for Online Portfolio Selection Open
Developing effective trend estimators is the main method to solve the online portfolio selection problem. Although the existing portfolio strategies have demonstrated good performance through the development of various trend estimators, it…
View article: Deep Few-view High-resolution Photon-counting Extremity CT at Halved Dose for a Clinical Trial.
Deep Few-view High-resolution Photon-counting Extremity CT at Halved Dose for a Clinical Trial. Open
The latest X-ray photon-counting computed tomography (PCCT) for extremity allows multi-energy high-resolution (HR) imaging for tissue characterization and material decomposition. However, both radiation dose and imaging speed need improvem…
View article: Spectrum learning for super-resolution tomographic reconstruction
Spectrum learning for super-resolution tomographic reconstruction Open
Objective . Computed Tomography (CT) has been widely used in industrial high-resolution non-destructive testing. However, it is difficult to obtain high-resolution images for large-scale objects due to their physical limitations. The objec…
View article: Passive Aggressive Ensemble for Online Portfolio Selection
Passive Aggressive Ensemble for Online Portfolio Selection Open
Developing effective trend estimators is a main method to solve the online portfolio selection problem. Although the existing portfolio strategies have demonstrated good performance through the development of various trend estimators, it i…
View article: Enhancing Pathogen Identification in Cheese with High Background Microflora Using an Artificial Neural Network-Enabled Paper Chromogenic Array Sensor Approach
Enhancing Pathogen Identification in Cheese with High Background Microflora Using an Artificial Neural Network-Enabled Paper Chromogenic Array Sensor Approach Open
View article: Iterative Residual Optimization Network for Limited-Angle Tomographic Reconstruction
Iterative Residual Optimization Network for Limited-Angle Tomographic Reconstruction Open
Limited-angle tomographic reconstruction is one of the typical ill-posed inverse problems, leading to edge divergence with degraded image quality. Recently, deep learning has been introduced into image reconstruction and achieved great res…
View article: LoMAE: Low-level Vision Masked Autoencoders for Low-dose CT Denoising
LoMAE: Low-level Vision Masked Autoencoders for Low-dose CT Denoising Open
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, transformer models emerged as a promising avenue to enhance…
View article: Two-and-a-half Order Score-based Model for Solving 3D Ill-posed Inverse Problems
Two-and-a-half Order Score-based Model for Solving 3D Ill-posed Inverse Problems Open
Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) are crucial technologies in the field of medical imaging. Score-based models have proven to be effective in addressing different inverse problems encountered in CT and MRI, such…
View article: HCformer: Hybrid CNN-Transformer for LDCT Image Denoising
HCformer: Hybrid CNN-Transformer for LDCT Image Denoising Open
View article: No-Reference Image Quality Assessment Based on a Multitask Image Restoration Network
No-Reference Image Quality Assessment Based on a Multitask Image Restoration Network Open
When image quality is evaluated, the human visual system (HVS) infers the details in the image through its internal generative mechanism. In this process, the HVS integrates both local and global information about the image, utilizes conte…
View article: Using HVS Dual-Pathway and Contrast Sensitivity to Blindly Assess Image Quality
Using HVS Dual-Pathway and Contrast Sensitivity to Blindly Assess Image Quality Open
Blind image quality assessment (BIQA) aims to evaluate image quality in a way that closely matches human perception. To achieve this goal, the strengths of deep learning and the characteristics of the human visual system (HVS) can be combi…
View article: Using HVS Dual-Pathway and Contrast Sensitivity to Blindly Assess Image Quality
Using HVS Dual-Pathway and Contrast Sensitivity to Blindly Assess Image Quality Open
Blind image quality assessment (BIQA) aims to evaluate image quality in a way that closely matches human perception. To achieve this goal, the strengths of deep learning and the characteristics of human visual system (HVS) can be combined.…
View article: Detection of Air Pollution in Urban Areas Using Monitoring Images
Detection of Air Pollution in Urban Areas Using Monitoring Images Open
Air quality monitoring in polluted environments is of great significance to human health. Traditional methods use various pieces of meteorological equipment, which have limited applications in complex terrains and high costs. In this paper…
View article: No-Reference Image Quality Assessment based on a Multitask Image Restoration Network
No-Reference Image Quality Assessment based on a Multitask Image Restoration Network Open
When the image quality is evaluated, the human visual system (HVS) infers the details in the image through its internal generative mechanism. In this process, the HVS integrates both local and global information of the image, utilizes cont…
View article: Regional perception and multi-scale feature fusion network for cardiac segmentation
Regional perception and multi-scale feature fusion network for cardiac segmentation Open
Objective. Cardiovascular disease (CVD) is a group of diseases affecting cardiac and blood vessels, and short-axis cardiac magnetic resonance (CMR) images are considered the gold standard for the diagnosis and assessment of CVD. In CMR ima…
View article: CTformer: convolution-free Token2Token dilated vision transformer for low-dose CT denoising
CTformer: convolution-free Token2Token dilated vision transformer for low-dose CT denoising Open
Objective . Low-dose computed tomography (LDCT) denoising is an important problem in CT research. Compared to the normal dose CT, LDCT images are subjected to severe noise and artifacts. Recently in many studies, vision transformers have s…
View article: SQ-Swin: Siamese Quadratic Swin Transformer for Lettuce Browning Prediction
SQ-Swin: Siamese Quadratic Swin Transformer for Lettuce Browning Prediction Open
Enzymatic browning is a major quality defect of packaged “ready-to-eat” fresh-cut lettuce salads. While there have been many research and breeding efforts to counter this problem, progress is hindered by the lack of a technology to identif…
View article: Sq-Swin: Siamese Quadratic Swin Transformer for Lettuce Browning Prediction
Sq-Swin: Siamese Quadratic Swin Transformer for Lettuce Browning Prediction Open
View article: Surveillance of Pathogenic Bacteria on a Food Matrix Using Machine-Learning-Enabled Paper Chromogenic Arrays
Surveillance of Pathogenic Bacteria on a Food Matrix Using Machine-Learning-Enabled Paper Chromogenic Arrays Open