5 papers
Restoration Adaptation for Semantic Segmentation on Low Quality Images
Kai Guan, Rongyuan Wu, Shuai Li +3
In real-world scenarios, the performance of semantic segmentation often deteriorates when processing low-quality (LQ) images, which may lack clear semantic structures and high-freq…
Enhancing Medical Image Segmentation via Heat Conduction Equation
Rong Wu, Yim-Sang Yu
Medical image segmentation models struggle to achieve efficient global context modeling and long-range dependency reasoning under practical computational budgets. In this work, we…
Unleashing Diffusion and State Space Models for Medical Image Segmentation
Rong Wu, Ziqi Chen, Liming Zhong +2
Existing segmentation models trained on a single medical imaging dataset often lack robustness when encountering unseen organs or tumors. Developing a robust model capable of ident…
Nonlinear Sparse Generalized Canonical Correlation Analysis for Multi-view High-dimensional Data
Rong Wu, Ziqi Chen, Gen Li +1
Motivation: Biomedical studies increasingly produce multi-view high-dimensional datasets (e.g., multi-omics) that demand integrative analysis. Existing canonical correlation analys…
Semi-supervised Medical Image Segmentation via Query Distribution Consistency
Rong Wu, Dehua Li, Cong Zhang
Semi-supervised learning is increasingly popular in medical image segmentation due to its ability to leverage large amounts of unlabeled data to extract additional information. How…