The future of Alzheimer's disease: the next 10 years

H Hampel, D Prvulovic, S Teipel, F Jessen… - Progress in …, 2011 - Elsevier
Alzheimer's disease (AD) is a fast growing world-wide epidemic. AD is a genetically
complex, slowly progressive, and irreversible neurodegenerative disease of the brain …

Fusing DTI and fMRI data: a survey of methods and applications

D Zhu, T Zhang, X Jiang, X Hu, H Chen, N Yang, J Lv… - NeuroImage, 2014 - Elsevier
The relationship between brain structure and function has been one of the centers of
research in neuroimaging for decades. In recent years, diffusion tensor imaging (DTI) and …

Predicting brain structural network using functional connectivity

L Zhang, L Wang, D Zhu… - Medical image …, 2022 - Elsevier
Uncovering the non-trivial brain structure–function relationship is fundamentally important
for revealing organizational principles of human brain. However, it is challenging to infer a …

Sparse representation of whole-brain fMRI signals for identification of functional networks

J Lv, X Jiang, X Li, D Zhu, H Chen, T Zhang… - Medical image …, 2015 - Elsevier
There have been several recent studies that used sparse representation for fMRI signal
analysis and activation detection based on the assumption that each voxel's fMRI signal is …

Representing and retrieving video shots in human-centric brain imaging space

J Han, X Ji, X Hu, D Zhu, K Li, X Jiang… - … on Image Processing, 2013 - ieeexplore.ieee.org
Meaningful representation and effective retrieval of video shots in a large-scale database
has been a profound challenge for the image/video processing and computer vision …

Dynamic functional connectomics signatures for characterization and differentiation of PTSD patients

X Li, D Zhu, X Jiang, C Jin, X Zhang, L Guo… - Human brain …, 2014 - Wiley Online Library
Functional connectomes (FCs) have been recently shown to be powerful in characterizing
brain conditions. However, many previous studies assumed temporal stationarity of FCs …

Multimodal hyper-connectivity of functional networks using functionally-weighted LASSO for MCI classification

Y Li, J Liu, X Gao, B Jie, M Kim, PT Yap, CY Wee… - Medical image …, 2019 - Elsevier
Recent works have shown that hyper-networks derived from blood-oxygen-level-dependent
(BOLD) fMRI, where an edge (called hyper-edge) can be connected to more than two nodes …

DICCCOL: dense individualized and common connectivity-based cortical landmarks

D Zhu, K Li, L Guo, X Jiang, T Zhang, D Zhang… - Cerebral …, 2013 - academic.oup.com
Is there a common structural and functional cortical architecture that can be quantitatively
encoded and precisely reproduced across individuals and populations? This question is still …

[HTML][HTML] Research on early diagnosis of Alzheimer's disease based on dual fusion cluster graph convolutional network

L Meng, Q Zhang - Biomedical Signal Processing and Control, 2023 - Elsevier
Abstract Objective Mild Cognitive Impairment (MCI) is an early stage of Alzheimer's Disease
(AD), often mistaken for natural aging. Early detection and treatment of MCI are crucial for …

Fiber clustering versus the parcellation-based connectome

LJ O'Donnell, AJ Golby, CF Westin - NeuroImage, 2013 - Elsevier
We compare two strategies for modeling the connections of the brain's white matter: fiber
clustering and the parcellation-based connectome. Both methods analyze diffusion …