English
Related papers

Related papers: Dynamic Functional Connectivity and Graph Convolut…

200 papers

Alzheimer's disease (AD) is associated with local (e.g. brain tissue atrophy) and global brain changes (loss of cerebral connectivity), which can be detected by high-resolution structural magnetic resonance imaging. Conventionally, these…

Machine Learning · Computer Science 2021-05-11 Sarah C. Brüningk , Felix Hensel , Catherine R. Jutzeler , Bastian Rieck

Brain networks from functional MRI have advanced our understanding of cortical activity and its disruption in neurodegenerative disorders. Recent work has increasingly focused on dynamic (time-varying) brain networks that capture both…

Neurons and Cognition · Quantitative Biology 2026-04-14 Nicolas Rubido , Venia Batziou , Marwan Fuad , Vesna Vuksanovic

Alzheimer's disease (AD) is the only major cause of mortality in the world without an effective disease modifying treatment. Evidence supporting the so called disconnection hypothesis suggests that functional connectivity biomarkers may…

{Introduction: } Dementia is a neurological disorder associated with aging that can cause a loss of cognitive functions, impacting daily life. Alzheimer's disease (AD) is the most common cause of dementia, accounting for 50--70\% of cases,…

Neurons and Cognition · Quantitative Biology 2023-11-07 Zaineb Ajra , Binbin Xu , Gérard Dray , Jacky Montmain , Stéphane Perrey

Alzheimer s disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, where early detection is essential for timely intervention and improved patient outcomes. Traditional diagnostic methods are…

Fusing structural-functional images of the brain has shown great potential to analyze the deterioration of Alzheimer's disease (AD). However, it is a big challenge to effectively fuse the correlated and complementary information from…

Image and Video Processing · Electrical Eng. & Systems 2023-10-06 Qiankun Zuo , Junren Pan , Shuqiang Wang

Alzheimer's Disease (AD) is an irreversible neurodegenerative disease characterized by progressive cognitive decline as its main symptom. In the research field of deep learning-assisted diagnosis of AD, traditional convolutional neural…

Image and Video Processing · Electrical Eng. & Systems 2025-07-15 Yang Ming , Jiang Shi Zhong , Zhou Su Juan

Dementia is a syndrome characterised by the decline of different cognitive abilities. Alzheimer's Disease (AD) is the most common dementia affecting cognitive domains such as memory and learning, perceptual-motion or executive function.…

Computer Vision and Pattern Recognition · Computer Science 2018-10-26 Juan Manuel Fernández Montenegro

Alzheimer's disease (AD) is a neurodegenerative disorder that affects more than seven million people in the United States alone. AD currently has no cure, but there are ways to potentially slow its progression if caught early enough. In…

Computer Vision and Pattern Recognition · Computer Science 2026-04-09 Mahdi Moghaddami , Mohammad-Reza Siadat , Austin Toma , Connor Laming , Huirong Fu

Alzheimers Disease (AD) is a progressive neurodegenerative disorder that poses significant challenges in its early diagnosis, often leading to delayed treatment and poorer outcomes for patients. Traditional diagnostic methods, typically…

Machine Learning · Computer Science 2025-08-06 Tatwadarshi P Nagarhalli , Sanket Patil , Vishal Pande , Uday Aswalekar , Prafulla Patil

Alzheimer's Disease (AD) is the most widespread neurodegenerative disease, affecting over 50 million people across the world. While its progression cannot be stopped, early and accurate diagnostic testing can drastically improve quality of…

Machine Learning · Computer Science 2021-01-11 Vishnu Ram Sampathkumar

In the last decade, computer-aided early diagnostics of Alzheimer's Disease (AD) and its prodromal form, Mild Cognitive Impairment (MCI), has been the subject of extensive research. Some recent studies have shown promising results in the AD…

Computer Vision and Pattern Recognition · Computer Science 2018-09-12 Alexander Khvostikov , Karim Aderghal , Andrey Krylov , Gwenaelle Catheline , Jenny Benois-Pineau

Deep graph learning has advanced Alzheimer's (AD) disease classification from MRI, but most models remain correlational, confounding demographic and genetic factors with disease specific features. We present Causal-GCN, an interventional…

Machine Learning · Computer Science 2025-11-20 Pranay Kumar Peddi , Dhrubajyoti Ghosh

Structural MRI and PET imaging play an important role in the diagnosis of Alzheimer's disease (AD), showing the morphological changes and glucose metabolism changes in the brain respectively. The manifestations in the brain image of some…

Image and Video Processing · Electrical Eng. & Systems 2023-08-11 Yanteng Zhang , Qizhi Teng , Xiaohai He , Tong Niu , Lipei Zhang , Yan Liu , Chao Ren

Alzheimer's disease (AD) is a progressive and incurable neurodegenerative disease which destroys brain cells and causes loss to patient's memory. An early detection can prevent the patient from further damage of the brain cells and hence…

Image and Video Processing · Electrical Eng. & Systems 2021-01-11 Ali Nawaz , Syed Muhammad Anwar , Rehan Liaqat , Javid Iqbal , Ulas Bagci , Muhammad Majid

Multi-modal neuroimaging technology has greatlly facilitated the efficiency and diagnosis accuracy, which provides complementary information in discovering objective disease biomarkers. Conventional deep learning methods, e.g. convolutional…

Image and Video Processing · Electrical Eng. & Systems 2022-10-26 Yanwu Yang , Xutao Guo , Zhikai Chang , Chenfei Ye , Yang Xiang , Ting Ma

Alzheimer's disease (AD) is a neuro-degenerative disease that can cause dementia and result severe reduction in brain function inhibiting simple tasks especially if no preventative care is taken. Over 1 in 9 Americans suffer from AD induced…

Image and Video Processing · Electrical Eng. & Systems 2023-06-21 Paul K. Mandal , Rakesh Mahto

Mild cognitive impairment (MCI) is a high-risk dementia condition which progresses to probable Alzheimer's disease (AD) at approximately 10% to 15% per year. Characterization of group-level differences between two subtypes of MCI - stable…

Neurons and Cognition · Quantitative Biology 2021-06-15 Lu Zhang , Xiaowei Yu , Yanjun Lyu , Li Wang , Dajiang Zhu

The study's objective is to explore the distinctions in the functional brain network connectivity between Alzheimer's Disease (AD) patients and normal controls using Functional Magnetic Resonance Imaging (fMRI). The study included 590…

Neurons and Cognition · Quantitative Biology 2023-05-17 Yongcheng Yao