BPGAN: Brain PET synthesis from MRI using generative adversarial network for multi-modal Alzheimer's disease diagnosis

J Zhang, X He, L Qing, F Gao, B Wang - Computer Methods and Programs …, 2022 - Elsevier
Abstract Background and Objective Multi-modal medical images, such as magnetic
resonance imaging (MRI) and positron emission tomography (PET), have been widely used …

A review of brain atrophy subtypes definition and analysis for Alzheimer's disease heterogeneity studies

B Zhang, L Lin, S Wu - Journal of Alzheimer's Disease, 2021 - content.iospress.com
Alzheimer's disease (AD) is a heterogeneous disease with different subtypes. Studying AD
subtypes from brain structure, neuropathology, and cognition are of great importance for AD …

Multi-modal cross-attention network for Alzheimer's disease diagnosis with multi-modality data

J Zhang, X He, Y Liu, Q Cai, H Chen, L Qing - Computers in Biology and …, 2023 - Elsevier
Alzheimer's disease (AD) is a neurodegenerative disorder, the most common cause of
dementia, so the accurate diagnosis of AD and its prodromal stage mild cognitive …

An approach for classification of Alzheimer's disease using deep neural network and brain magnetic resonance imaging (MRI)

RA Hazarika, AK Maji, D Kandar, E Jasinska, P Krejci… - Electronics, 2023 - mdpi.com
Alzheimer's disease (AD) is a deadly cognitive condition in which people develop severe
dementia symptoms. Neurologists commonly use a series of physical and mental tests to …

An improved LeNet-deep neural network model for Alzheimer's disease classification using brain magnetic resonance images

RA Hazarika, A Abraham, D Kandar, AK Maji - IEEE Access, 2021 - ieeexplore.ieee.org
Alzheimer's Disease (AD) is a psychological disorder in elderly people which causes severe
intellectual disabilities. Proper processing of neuro-images can provide differences in brain …

Multi-relation graph convolutional network for Alzheimer's disease diagnosis using structural MRI

J Zhang, X He, L Qing, X Chen, Y Liu… - Knowledge-Based Systems, 2023 - Elsevier
Structural magnetic resonance imaging (sMRI) is widely applied in Alzheimer's disease (AD)
diagnosis tasks by reflecting structural anomalies of the brain. Currently, most existing …

On the design of convolutional neural networks for automatic detection of Alzheimer's disease

S Liu, C Yadav, C Fernandez-Granda… - … Learning for Health …, 2020 - proceedings.mlr.press
Early detection is a crucial goal in the study of Alzheimer's Disease (AD). In this work, we
describe several techniques to boost the performance of 3D convolutional neural networks …

3d Convolutional neural networks for diagnosis of alzheimer's disease via structural mri

E Yagis, L Citi, S Diciotti, C Marzi… - 2020 IEEE 33rd …, 2020 - ieeexplore.ieee.org
Alzheimer's Disease (AD) is a widespread neurodegenerative disease caused by structural
changes in the brain and leads to deterioration of cognitive functions. Patients usually …

A CAD system for Alzheimer's disease classification using neuroimaging MRI 2D slices

M Sethi, S Rani, A Singh… - … Mathematical Methods in …, 2022 - Wiley Online Library
Developments in medical care have inspired wide interest in the current decade, especially
to their services to individuals living prolonged and healthier lives. Alzheimer's disease (AD) …

Multi-scale 3D convolution feature-based broad learning system for Alzheimer's disease diagnosis via MRI images

R Han, Z Liu, CLP Chen - Applied Soft Computing, 2022 - Elsevier
Alzheimer's disease (AD) has become a severe chronic disease that affects the health of the
elderly all over the world. And the number of patients currently suffering continues to rise …