1 citations · 1 across the 15 of their papers we have counts for
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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…
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…
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…
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…