Yilin Leng

A Novel Dynamic Neural Network for Heterogeneity-Aware Structural Brain Network Exploration and Alzheimer’s Disease Diagnosis

Wenju Cui, Yilin Leng, Yunsong Peng, Chen Bai et autres

Heterogeneity is a fundamental characteristic of brain diseases, distinguished by variability not only in brain atrophy but also in the complexity of neural connectivity and brain networks. However, existing data-driven methods fail to provide a comprehensive analysis of brain heterogeneity. Recently, dynamic …

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A deep-learning model for predicting post-stroke cognitive impairment based on brain network damage

Chen Bai, Yilin Leng, Haixing Xiao, Lei Li et autres

Background: Post-stroke cognitive impairment (PSCI) is a common and severe complication following acute lacunar stroke (ALS). Due to the limitations of current assessment tools and imaging methods, the early diagnosis of PSCI within 3 months of ALS remaining challenging. This study aimed …

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Adaptive critical subgraph mining for cognitive impairment conversion prediction with T1-MRI-based brain network

Yilin Leng, Wenju Cui, Bai Chen, Xi Jiang et autres

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

Yilin Leng, Wenju Cui, Bai Chen, Xi Jiang et autres

Prediction the conversion to early-stage dementia is critical for mitigating its progression but remains challenging due to subtle cognitive impairments and structural brain changes. Traditional T1-weighted magnetic resonance imaging (T1-MRI) research focus on identifying brain atrophy regions but often fails to address …

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Adaptive Critical Subgraph Mining for Cognitive Impairment Conversion Prediction with T1-Mri-Based Brain Network

Yilin Leng, Wenju Cui, Chen Bai, Xi Jiang et autres

DB-DCAFN: dual-branch deformable cross-attention fusion network for bacterial segmentation

Jingkun Wang, Xinyu Ma, Long Cao, Yilin Leng et autres

Sputum smear tests are critical for the diagnosis of respiratory diseases. Automatic segmentation of bacteria from sputum smear images is important for improving diagnostic efficiency. However, this remains a challenging task owing to the high interclass similarity among different categories of bacteria …

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

Yilin Leng, Wenju Cui, Chen Bai, Zheng Yanyan et autres

Constructing structural brain networks using T1-weighted magnetic resonance imaging (T1-MRI) presents a significant challenge due to the lack of direct regional connectivity information. Current methods with T1-MRI rely on predefined regions or isolated pretrained location modules to obtain atrophic regions, which neglects …

Multimodal cross enhanced fusion network for diagnosis of Alzheimer’s disease and subjective memory complaints

Yilin Leng, Wenju Cui, Yunsong Peng, Caiying Yan et autres

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Multimodal Cross Enhanced Fusion Network for Diagnosis of Alzheimer's Disease and Subjective Memory Complaints

Yilin Leng, Wenjun Cui, Yunsong Peng, Caiying Yan et autres

Deep learning methods using multimodal imagings have been proposed for the diagnosis of Alzheimer’s disease (AD) and its early stages (SMC, subjective memory complaints), which may help to slow the progression of the disease through early intervention. However, current fusion methods for …

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

Yilin Leng, Wenju Cui, Chen Bai, Zirui Chen et autres

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BMNet: A New Region-Based Metric Learning Method for Early Alzheimer’s Disease Identification With FDG-PET Images

Wenju Cui, Caiying Yan, Zhuangzhi Yan, Yunsong Peng et autres

18F-fluorodeoxyglucose (FDG)-positron emission tomography (PET) reveals altered brain metabolism in individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD). Some biomarkers derived from FDG-PET by computer-aided-diagnosis (CAD) technologies have been proved that they can accurately diagnosis normal control (NC), MCI, and …

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[Glasses-free Three Dimensional Endoscopic Display System with Multi-face Detection].

Yilin Leng, Zhaohui Xu

The glasses-free three dimensional(3D) endoscopic display system provides the surgeon with the depth information of the minimally invasive surgery scene obtained from the binocular perspective, which can effectively relieve the surgeon's posture fatigue and visual fatigue during the long-term surgery, and assist …

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