Constructing consistent longitudinal brain networks by group-wise graph learning
Mounting evidence shows that many neuro-disorders can be understood as a dysfunction
syndrome where the structural and functional connectivities of the large-scale network are …
syndrome where the structural and functional connectivities of the large-scale network are …
[PDF][PDF] Constructing Consistent Longitudinal Brain Networks by Group-Wise Graph Learning
M Styner - academia.edu
Mounting evidence shows that many neuro-disorders can be understood as a dysfunction
syndrome where the structural and functional connectivities of the large-scale network are …
syndrome where the structural and functional connectivities of the large-scale network are …
How much to aggregate: Learning adaptive node-wise scales on graphs for brain networks
Brain connectomes are heavily studied to characterize early symptoms of various
neurodegenerative diseases such as Alzheimer's Disease (AD). As the connectomes over …
neurodegenerative diseases such as Alzheimer's Disease (AD). As the connectomes over …
Recurrent brain graph mapper for predicting time-dependent brain graph evaluation trajectory
Several brain disorders can be detected by observing alterations in the brain's structural and
functional connectivities. Neurological findings suggest that early diagnosis of brain …
functional connectivities. Neurological findings suggest that early diagnosis of brain …
[HTML][HTML] A comprehensive survey of complex brain network representation
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 …
structural and functional changes, as well as its relationship to different neurodegenerative …
Learning Signal Subgraphs from Longitudinal Brain Networks with Symmetric Bilinear Logistic Regression
L Wang, Z Zhang - arXiv preprint arXiv:1908.05627, 2019 - arxiv.org
Modern neuroimaging technologies, combined with state-of-the-art data processing
pipelines, have made it possible to collect longitudinal observations of an individual's brain …
pipelines, have made it possible to collect longitudinal observations of an individual's brain …
Predicting the evolution trajectory of population-driven connectional brain templates using recurrent multigraph neural networks
O Demirbilek, I Rekik… - Medical Image …, 2023 - Elsevier
The mapping of the time-dependent evolution of the human brain connectivity using
longitudinal and multimodal neuroimaging datasets provides insights into the development …
longitudinal and multimodal neuroimaging datasets provides insights into the development …
Recurrent multigraph integrator network for predicting the evolution of population-driven brain connectivity templates
O Demirbilek, I Rekik - Medical Image Computing and Computer Assisted …, 2021 - Springer
Learning how to estimate a connectional brain template (CBT) from a population of brain
multigraphs, where each graph (eg, functional) quantifies a particular relationship between …
multigraphs, where each graph (eg, functional) quantifies a particular relationship between …
Multi-resolution graph neural network for identifying disease-specific variations in brain connectivity
Convolution Neural Network (CNN) recently have been adopted in several neuroimaging
studies for diagnosis capturing disease-specific changes in the brain. While many of these …
studies for diagnosis capturing disease-specific changes in the brain. While many of these …
BrainUSL: U nsupervised Graph S tructure L earning for Functional Brain Network Analysis
The functional connectivity (FC) between brain regions is usually estimated through a
statistical dependency method with functional magnetic resonance imaging (fMRI) data. It …
statistical dependency method with functional magnetic resonance imaging (fMRI) data. It …