6 papers
Unified Multi-Site Multi-Sequence Brain MRI Harmonization Enriched by Biomedical Semantic Style
Mengqi Wu, Yongheng Sun, Qianqian Wang +2
Aggregating multi-site brain MRI data can enhance deep learning model training, but also introduces non-biological heterogeneity caused by site-specific variations (e.g., differenc…
Learning from Heterogeneous Structural MRI via Collaborative Domain Adaptation for Late-Life Depression Assessment
Yuzhen Gao, Qianqian Wang, Yongheng Sun +3
Accurate identification of late-life depression (LLD) using structural brain MRI is essential for monitoring disease progression and facilitating timely intervention. However, exis…
Hyperbolic Kernel Graph Neural Networks for Neurocognitive Decline Analysis from Multimodal Brain Imaging
Meimei Yang, Yongheng Sun, Qianqian Wang +3
Multimodal neuroimages, such as diffusion tensor imaging (DTI) and resting-state functional MRI (fMRI), offer complementary perspectives on brain activities by capturing structural…
Topology-Aware Graph Augmentation for Predicting Clinical Trajectories in Neurocognitive Disorders
Qianqian Wang, Wei Wang, Yuqi Fang +3
Brain networks/graphs derived from resting-state functional MRI (fMRI) help study underlying pathophysiology of neurocognitive disorders by measuring neuronal activities in the bra…
Augmentation-based Unsupervised Cross-Domain Functional MRI Adaptation for Major Depressive Disorder Identification
Yunling Ma, Chaojun Zhang, Xiaochuan Wang +4
Major depressive disorder (MDD) is a common mental disorder that typically affects a person's mood, cognition, behavior, and physical health. Resting-state functional magnetic reso…
ACTION: Augmentation and Computation Toolbox for Brain Network Analysis with Functional MRI
Yuqi Fang, Junhao Zhang, Linmin Wang +2
Functional magnetic resonance imaging (fMRI) has been increasingly employed to investigate functional brain activity. Many fMRI-related software/toolboxes have been developed, prov…