Adaptive Critical Subgraph Mining for Cognitive Impairment Conversion Prediction with T1-MRI-based Brain Network

no code implementations • 20 Mar 2024 • Yilin Leng, Wenju Cui, Bai Chen, Xi Jiang, Shuangqing Chen, Jian Zheng

These are essential for developing high-quality feature representations that reveal critical spatial impacts of structural brain changes and its topology.

Dynamic Structural Brain Network Construction by Hierarchical Prototype Embedding GCN using T1-MRI

no code implementations • 17 May 2023 • Yilin Leng, Wenju Cui, Chen Bai, Zheng Yanyan, Jian Zheng

Besides, existing methods capture global structural context only on the whole-image-level, which weaken correlation between regions and the hierarchical distribution nature of brain connectivity. We hereby propose a novel dynamic structural brain network construction method based on T1-MRI, which can dynamically localize critical regions and constrain the hierarchical distribution among them for constructing dynamic structural brain network.

Specificity

Bilinear pooling and metric learning network for early Alzheimer's disease identification with FDG-PET images

no code implementations • 9 Nov 2021 • Wenju Cui, Caiying Yan, Zhuangzhi Yan, Yunsong Peng, Yilin Leng, Chenlu Liu, Shuangqing Chen, Xi Jiang

FDG-PET reveals altered brain metabolism in individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD).

Metric Learning Specificity