1 citations · 1 across the 3 of their papers we have counts for
4 papers
Adaptive Clinical-Aware Latent Diffusion for Multimodal Brain Image Generation and Missing Modality Imputation
Rong Zhou, Houliang Zhou, Yao Su +4
Multimodal neuroimaging provides complementary insights for Alzheimer's disease diagnosis, yet clinical datasets frequently suffer from missing modalities. We propose ACADiff, a fr…
Spatio-Temporal Graph Deep Learning with Stochastic Differential Equations for Uncovering Alzheimer's Disease Progression
Houliang Zhou, Rong Zhou, Yangying Liu +6
Identifying objective neuroimaging biomarkers to forecast Alzheimer's disease (AD) progression is crucial for timely intervention. However, this task remains challenging due to the…
Multi-layer 5D Optical Data Storage: Mathematical Modeling and Deep Learning-Based Reconstruction of Birefringent Parameters
Ye Zhang, Qiao Zhu, Rongkuan Zhou +2
Five-dimensional (5D) optical data storage has emerged as a promising technology for ultra-high-density, long-term data archiving. However, its practical realization is hindered by…
ClusMFL: A Cluster-Enhanced Framework for Modality-Incomplete Multimodal Federated Learning in Brain Imaging Analysis
Xinpeng Wang, Rong Zhou, Han Xie +3
Multimodal Federated Learning (MFL) has emerged as a promising approach for collaboratively training multimodal models across distributed clients, particularly in healthcare domain…