2 citations · 2 across the 4 of their papers we have counts for
6 papers
MOSAIC-Flow: Orthogonal-Axis and Status-Conditioned Fusion for Missing-Sequence Completion in Brain Tumor MRI
Pengli Zhu, Zhihao Peng, Yixuan Yuan
Missing-sequence completion is important for comprehensive brain tumor characterization, but cross-modal fusion can obscure sequence-specific contrast and lose fine-grained three-d…
BRIDGE: Learning Brain-Gut Metabolic Evidence for Alzheimer's Disease Diagnosis
Pengli Zhu, Ruxi Chang, Tianliang Yao +7
Alzheimer's disease (AD) diagnosis may benefit from gut metabolic information associated with brain-gut interactions, yet existing models largely analyze cerebral glucose metabolis…
Task-Adaptive 3D Cross-Field MRI Translation via Field-Conditioned Content-Style Pretraining
Haowen Pang, Yingqi Hao, Pengli Zhu
Magnetic field strength is a major source of domain shift in magnetic resonance imaging (MRI), affecting signal-to-noise ratio, tissue contrast, spatial detail, and the visibility…
IHF-Harmony: Multi-Modality Magnetic Resonance Images Harmonization using Invertible Hierarchy Flow Model
Pengli Zhu, Yitao Zhu, Haowen Pang +1
Retrospective MRI harmonization is limited by poor scalability across modalities and reliance on traveling subject datasets. To address these challenges, we introduce IHF-Harmony,…
Q-space Guided Collaborative Attention Translation Network for Flexible Diffusion-Weighted Images Synthesis
Pengli Zhu, Yingji Fu, Nanguang Chen +1
This study, we propose a novel Q-space Guided Collaborative Attention Translation Networks (Q-CATN) for multi-shell, high-angular resolution DWI (MS-HARDI) synthesis from flexible…
Advancing Graph Neural Networks with HL-HGAT: A Hodge-Laplacian and Attention Mechanism Approach for Heterogeneous Graph-Structured Data
Jinghan Huang, Qiufeng Chen, Yijun Bian +4
Graph neural networks (GNNs) have proven effective in capturing relationships among nodes in a graph. This study introduces a novel perspective by considering a graph as a simplici…