1 citations · 1 across the 15 of their papers we have counts for
15 papers
FrequencyCT: Frequency Domain Self-supervised Low-dose CT Denoising
Guoquan Wei, Liu Shi, Chong Chen +1
Despite extensive research on computed tomography (CT) denoising, few studies exploit projection-domain data characteristics to mitigate noise correlation. To bridge this gap, this…
SCOUT: Fast Spectral CT Imaging in Ultra LOw-data Regimes via PseUdo-label GeneraTion
Guoquan Wei, Liu Shi, Shaoyu Wang +3
Noise and artifacts during computed tomography (CT) scans are a fundamental challenge affecting disease diagnosis. However, current methods either involve excessively long reconstr…
AS-Mamba: Asymmetric Self-Guided Mamba Decoupled Iterative Network for Metal Artifact Reduction
Bowen Ning, Zekun Zhou, Xinyi Zhong +5
Metal artifact significantly degrades Computed Tomography (CT) image quality, impeding accurate clinical diagnosis. However, existing deep learning approaches, such as CNN and Tran…
Visible Singularities Guided Correlation Network for Limited-Angle CT Reconstruction
Yiyang Wen, Liu Shi, Zekun Zhou +2
Limited-angle computed tomography (LACT) offers the advantages of reduced radiation dose and shortened scanning time. Traditional reconstruction algorithms exhibit various inherent…
Anatomy Aware Cascade Network: Bridging Epistemic Uncertainty and Geometric Manifold for 3D Tooth Segmentation
Bing Yu, Liu Shi, Haitao Wang +4
Accurate three-dimensional (3D) tooth segmentation from Cone-Beam Computed Tomography (CBCT) is a prerequisite for digital dental workflows. However, achieving high-fidelity segmen…
LaminoDiff: Generative Computed Laminography via Near-Isotropic Spectral Supervision and Anisotropic Geometry
Tan Liu, Liu Shi, Binghuang Peng +4
Computed Laminography (CL) is widely used for nondestructive inspection of extended planar objects, but its restricted angular coverage produces an anisotropic point spread functio…
Physics-Guided Null-Space Diffusion with Sparse Masking for Corrective Sparse-View CT Reconstruction
Zekun Zhou, Yanru Gong, Liu Shi +1
Diffusion models have demonstrated remarkable generative capabilities in image processing tasks. We propose a Sparse condition Temporal Rewighted Integrated Distribution Estimation…
Extendable Generalization Self-Supervised Diffusion for Low-Dose CT Reconstruction
Guoquan Wei, Liu Shi, Zekun Zhou +4
Current methods based on deep learning for self-supervised low-dose CT (LDCT) reconstruction, while reducing the dependence on paired data, face the problem of significantly decrea…
PWD: Prior-Guided and Wavelet-Enhanced Diffusion Model for Limited-Angle CT
Yi Liu, Yiyang Wen, Zekun Zhou +5
Generative diffusion models have received increasing attention in medical imaging, particularly in limited-angle computed tomography (LACT). Standard diffusion models achieve high-…
FD-DiT: Frequency Domain-Directed Diffusion Transformer for Low-Dose CT Reconstruction
Qiqing Liu, Guoquan Wei, Zekun Zhou +3
Low-dose computed tomography (LDCT) reduces radiation exposure but suffers from image artifacts and loss of detail due to quantum and electronic noise, potentially impacting diagno…
ESDiff: Encoding Strategy-inspired Diffusion Model with Few-shot Learning for Color Image Inpainting
Junyan Zhang, Yan Li, Mengxiao Geng +2
Image inpainting is a technique used to restore missing or damaged regions of an image. Traditional methods primarily utilize information from adjacent pixels for reconstructing mi…
Virtual-mask Informed Prior for Sparse-view Dual-Energy CT Reconstruction
Zini Chen, Yao Xiao, Junyan Zhang +3
Sparse-view sampling in dual-energy computed tomography (DECT) significantly reduces radiation dose and increases imaging speed, yet is highly prone to artifacts. Although diffusio…
Physics-informed DeepCT: Sinogram Wavelet Decomposition Meets Masked Diffusion
Zekun Zhou, Tan Liu, Bing Yu +3
Diffusion model shows remarkable potential on sparse-view computed tomography (SVCT) reconstruction. However, when a network is trained on a limited sample space, its generalizatio…
RED: Residual Estimation Diffusion for Low-Dose PET Sinogram Reconstruction
Xingyu Ai, Bin Huang, Fang Chen +4
Recent advances in diffusion models have demonstrated exceptional performance in generative tasks across vari-ous fields. In positron emission tomography (PET), the reduction in tr…
MSDiff: Multi-Scale Diffusion Model for Ultra-Sparse View CT Reconstruction
Junyan Zhang, Mengxiao Geng, Pinhuang Tan +4
Computed Tomography (CT) technology reduces radiation haz-ards to the human body through sparse sampling, but fewer sampling angles pose challenges for image reconstruction. Score-…