Search Results for author: Guorong Wu

Found 11 papers, 1 papers with code

DeepGraphDMD: Interpretable Spatio-Temporal Decomposition of Non-linear Functional Brain Network Dynamics

1 code implementation5 Jun 2023 Md Asadullah Turja, Martin Styner, Guorong Wu

In this work, we apply GraphDMD -- an extension of the DMD for network data -- to extract the dynamic network modes and their temporal characteristics from the fMRI time series in an interpretable manner.

Time Series

Groupwise Registration via Graph Shrinkage on the Image Manifold

no code implementations CVPR 2013 Shihui Ying, Guorong Wu, Qian Wang, Dinggang Shen

Specifically, we first use a graph to model the distribution of all image data sitting on the image manifold, with each node representing an image and each edge representing the geodesic pathway between two nodes (or images).

Image Registration

Multi-resolution Graph Neural Network for Identifying Disease-specific Variations in Brain Connectivity

no code implementations3 Dec 2019 Xin Ma, Guorong Wu, Won Hwa Kim

As there is significant interest in understanding the altered interactions between different brain regions that lead to neuro-disorders, it is important to develop data-driven methods that work with a population of graph data for traditional prediction tasks.

Graph Learning

Learning Common Harmonic Waves on Stiefel Manifold -- A New Mathematical Approach for Brain Network Analyses

no code implementations1 Jul 2020 Jiazhou Chen, Guoqiang Han, Hongmin Cai, Defu Yang, Paul J. Laurienti, Martin Styner, Guorong Wu, Alzheimer's Disease Neuroimaging Initiative ADNI

To that end, we propose a novel connectome harmonic analysis framework to provide enhanced mathematical insights by detecting frequency-based alterations relevant to brain disorders.

A Network-Guided Reaction-Diffusion Model of AT[N] Biomarkers in Alzheimer's Disease

no code implementations10 Sep 2020 Jingwen Zhang, Defu Yang, wei he, Guorong Wu, Minghan Chen

Currently, many studies of Alzheimer's disease (AD) are investigating the neurobiological factors behind the acquisition of beta-amyloid (A), pathologic tau (T), and neurodegeneration ([N]) biomarkers from neuroimages.

Analyzing the Spatiotemporal Interaction and Propagation of ATN Biomarkers in Alzheimer's Disease using Longitudinal Neuroimaging Data

no code implementations7 Mar 2021 Qing Liu, Defu Yang, Jingwen Zhang, Ziming Wei, Guorong Wu, Minghan Chen

Three major biomarkers: beta-amyloid (A), pathologic tau (T), and neurodegeneration (N), are recognized as valid proxies for neuropathologic changes of Alzheimer's disease.

valid

Uncovering the System Vulnerability and Criticality of Human Brain under Dynamical Neuropathological Events in Alzheimer's Disease

no code implementations22 Jan 2022 Jingwen Zhang, Qing Liu, Haorui Zhang, Michelle Dai, Qianqian Song, Defu Yang, Guorong Wu, Minghan Chen

Background: Despite the striking efforts in investigating neurobiological factors behind the acquisition of amyloid-\b{eta} (A), protein tau (T), and neurodegeneration ([N]) biomarkers, the mechanistic pathways of how AT[N] biomarkers spreading throughout the brain remain elusive.

Pathology Steered Stratification Network for Subtype Identification in Alzheimer's Disease

no code implementations12 Oct 2022 Enze Xu, Jingwen Zhang, Jiadi Li, Qianqian Song, Defu Yang, Guorong Wu, Minghan Chen

Alzheimer's disease (AD) is a heterogeneous, multifactorial neurodegenerative disorder characterized by beta-amyloid, pathologic tau, and neurodegeneration.

Learning to Approximate Adaptive Kernel Convolution on Graphs

no code implementations22 Jan 2024 Jaeyoon Sim, Sooyeon Jeon, InJun Choi, Guorong Wu, Won Hwa Kim

As setting different number of hidden layers per node is infeasible, recent works leverage a diffusion kernel to redefine the graph structure and incorporate information from farther nodes.

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