[HTML][HTML] A comprehensive survey of complex brain network representation

H Tang, G Ma, Y Zhang, K Ye, L Guo, G Liu, Q Huang… - Meta-Radiology, 2023 - Elsevier
Recent years have shown great merits in utilizing neuroimaging data to understand brain
structural and functional changes, as well as its relationship to different neurodegenerative …

Federated multi-task learning for joint diagnosis of multiple mental disorders on MRI scans

ZA Huang, Y Hu, R Liu, X Xue, Z Zhu… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Objective: Deep learning (DL) techniques have been introduced to assist doctors in the
interpretation of medical images by detecting image-derived phenotype abnormality. Yet the …

Multi-band brain network analysis for functional neuroimaging biomarker identification

R Hu, Z Peng, X Zhu, J Gan, Y Zhu… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
The functional connectomic profile is one of the non-invasive imaging biomarkers in the
computer-assisted diagnostic system for many neuro-diseases. However, the diagnostic …

Brain network analysis of schizophrenia patients based on hypergraph signal processing

X Song, K Wu, L Chai - IEEE Transactions on Image …, 2023 - ieeexplore.ieee.org
Since high-order relationships among multiple brain regions-of-interests (ROIs) are helpful
to explore the pathogenesis of neurological diseases more deeply, hypergraph-based brain …

Modularity-Constrained Dynamic Representation Learning for Interpretable Brain Disorder Analysis with Functional MRI

Q Wang, M Wu, Y Fang, W Wang, L Qiao… - … Conference on Medical …, 2023 - Springer
Resting-state functional MRI (rs-fMRI) is increasingly used to detect altered functional
connectivity patterns caused by brain disorders, thereby facilitating objective quantification …

Constructing hierarchical attentive functional brain networks for early AD diagnosis

J Zhang, Y Guo, L Zhou, L Wang, W Wu, D Shen - Medical Image Analysis, 2024 - Elsevier
Analyzing functional brain networks (FBN) with deep learning has demonstrated great
potential for brain disorder diagnosis. The conventional construction of FBN is typically …

Ordinal Pattern Tree: A New Representation Method for Brain Network Analysis

K Ma, X Wen, Q Zhu, D Zhang - IEEE Transactions on Medical …, 2023 - ieeexplore.ieee.org
Brain networks, describing the functional or structural interactions of brain with graph theory,
have been widely used for brain imaging analysis. Currently, several network representation …

OCD diagnosis via smooth sparse network and fused sparse auto-encoder learning

P Yang, Z Wei, Q Yang, X Xiao, T Wang, B Lei… - Expert Systems with …, 2023 - Elsevier
Obsessive-compulsive disorder (OCD) brings many problems to patients. Redundant
information in the OCD data can be removed to preserve valuable biological functions …

[HTML][HTML] A joint subspace mapping between structural and functional brain connectomes

S Ghosh, A Raj, SS Nagarajan - NeuroImage, 2023 - Elsevier
Understanding the connection between the brain's structural connectivity and its functional
connectivity is of immense interest in computational neuroscience. Although some studies …

Learning robust hierarchical patterns of human brain across many fmri studies

D Sahoo, C Davatzikos - Advances in Neural Information …, 2021 - proceedings.neurips.cc
Multi-site fMRI studies face the challenge that the pooling introduces systematic non-
biological site-specific variance due to hardware, software, and environment. In this paper …