59 citations · 130 across the 15 of their papers we have counts for
15 papers
Volumetric Radiology AI in the Era of Multimodal Large Language Models
Zanting Ye, Shengyuan Liu, Xin Liu +16
Advances in multimodal large language models (MLLMs) are extending radiological artificial intelligence (AI) beyond task-specific image analysis toward multimodal understanding and…
Bridging Brain and Semantics: A Hierarchical Framework for Semantically Enhanced fMRI-to-Video Reconstruction
Yujie Wei, Chenglong Ma, Jianxiong Gao +6
Reconstructing dynamic visual experiences as videos from functional magnetic resonance imaging (fMRI) is pivotal for advancing the understanding of neural processes. However, curre…
Hierarchical Codec Diffusion for Video-to-Speech Generation
Jiaxin Ye, Gaoxiang Cong, Chenhui Wang +4
Video-to-Speech (VTS) generation aims to synthesize speech from a silent video without auditory signals. However, existing VTS methods disregard the hierarchical nature of speech,…
Brain-WM: Brain Glioblastoma World Model
Chenhui Wang, Boyun Zheng, Liuxin Bao +4
Precise prognostic modeling of glioblastoma (GBM) under varying treatment interventions is essential for optimizing clinical outcomes. While generative AI has shown promise in simu…
UniField: A Unified Field-Aware MRI Enhancement Framework
Yiyang Lin, Chenhui Wang, Zhihao Peng +1
Magnetic Resonance Imaging (MRI) field-strength enhancement holds immense value for both clinical diagnostics and advanced research. However, existing methods typically focus on is…
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…
Dynamic Differential Linear Attention: Enhancing Linear Diffusion Transformer for High-Quality Image Generation
Boyuan Cao, Xingbo Yao, Chenhui Wang +3
Diffusion transformers (DiTs) have emerged as a powerful architecture for high-fidelity image generation, yet the quadratic cost of self-attention poses a major scalability bottlen…
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…
HiDiff: Hybrid Diffusion Framework for Medical Image Segmentation
Tao Chen, Chenhui Wang, Zhihao Chen +2
Medical image segmentation has been significantly advanced with the rapid development of deep learning (DL) techniques. Existing DL-based segmentation models are typically discrimi…
FLDM-VTON: Faithful Latent Diffusion Model for Virtual Try-on
Chenhui Wang, Tao Chen, Zhihao Chen +4
Despite their impressive generative performance, latent diffusion model-based virtual try-on (VTON) methods lack faithfulness to crucial details of the clothes, such as style, patt…
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…
BerDiff: Conditional Bernoulli Diffusion Model for Medical Image Segmentation
Tao Chen, Chenhui Wang, Hongming Shan
Medical image segmentation is a challenging task with inherent ambiguity and high uncertainty, attributed to factors such as unclear tumor boundaries and multiple plausible annotat…