17 citations · 18 across the 12 of their papers we have counts for
6 papers · 1 filter
Skill-Evolving Grounded Reasoning for Free-Text Promptable 3D Medical Image Segmentation
Tongrui Zhang, Chenhui Wang, Yongming Li +3
Free-text promptable 3D medical image segmentation offers an intuitive and clinically flexible interaction paradigm. However, current methods are highly sensitive to linguistic var…
LangMamba: A Language-driven Mamba Framework for Low-dose CT Denoising with Vision-language Models
Zhihao Chen, Tao Chen, Chenhui Wang +5
Low-dose computed tomography (LDCT) reduces radiation exposure but often degrades image quality, potentially compromising diagnostic accuracy. Existing deep learning-based denoisin…
Unified Medical Image Tokenizer for Autoregressive Synthesis and Understanding
Chenglong Ma, Yuanfeng Ji, Jin Ye +9
Autoregressive modeling has driven major advances in multimodal AI, yet its application to medical imaging remains constrained by the absence of a unified image tokenizer that simu…
Autoregressive Medical Image Segmentation via Next-Scale Mask Prediction
Tao Chen, Chenhui Wang, Zhihao Chen +1
While deep learning has significantly advanced medical image segmentation, most existing methods still struggle with handling complex anatomical regions. Cascaded or deep supervisi…
Low-dose CT Denoising with Language-engaged Dual-space Alignment
Zhihao Chen, Tao Chen, Chenhui Wang +3
While various deep learning methods were proposed for low-dose computed tomography (CT) denoising, they often suffer from over-smoothing, blurring, and lack of explainability. To a…
HOPE: Hybrid-granularity Ordinal Prototype Learning for Progression Prediction of Mild Cognitive Impairment
Chenhui Wang, Yiming Lei, Tao Chen +3
Mild cognitive impairment (MCI) is often at high risk of progression to Alzheimer's disease (AD). Existing works to identify the progressive MCI (pMCI) typically require MCI subtyp…