activity
20242026
collaborators

11 papers

eess.IV2026

From Coarse to Continuous: Progressive Refinement Implicit Neural Representation for Motion-Robust Anisotropic MRI Reconstruction

Zhenxuan Zhang, Lipei Zhang, Yanqi Cheng +10

In motion-robust magnetic resonance imaging (MRI), slice-to-volume reconstruction is critical for recovering anatomically consistent 3D brain volumes from 2D slices, especially und…

cs.CV2026

ProSMA-UNet: Decoder Conditioning for Proximal-Sparse Skip Feature Selection

Chun-Wun Cheng, Yanqi Cheng, Peiyuan Jing +4

Medical image segmentation commonly relies on U-shaped encoder-decoder architectures such as U-Net, where skip connections preserve fine spatial detail by injecting high-resolution…

eess.IV2026

Implicit U-KAN2.0: Dynamic, Efficient and Interpretable Medical Image Segmentation

Chun-Wun Cheng, Yining Zhao, Yanqi Cheng +3

Image segmentation is a fundamental task in both image analysis and medical applications. State-of-the-art methods predominantly rely on encoder-decoder architectures with a U-shap…

cs.CV2025

DNA-Prior: Unsupervised Denoise Anything via Dual-Domain Prior

Yanqi Cheng, Chun-Wun Cheng, Jim Denholm +5

Medical imaging pipelines critically rely on robust denoising to stabilise downstream tasks such as segmentation and reconstruction. However, many existing denoisers depend on larg…

cs.CV2025

Deep Spectral Prior

Yanqi Cheng, Xuxiang Zhao, Tieyong Zeng +3

We introduce the Deep Spectral Prior (DSP), a new framework for unsupervised image reconstruction that operates entirely in the complex frequency domain. Unlike the Deep Image Prio…

eess.IV2025

D2SA: Dual-Stage Distribution and Slice Adaptation for Efficient Test-Time Adaptation in MRI Reconstruction

Lipei Zhang, Rui Sun, Zhongying Deng +3

Variations in Magnetic resonance imaging (MRI) scanners and acquisition protocols cause distribution shifts that degrade reconstruction performance on unseen data. Test-time adapta…