Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis

HI Suk, SW Lee, D Shen… - NeuroImage, 2014 - Elsevier
For the last decade, it has been shown that neuroimaging can be a potential tool for the
diagnosis of Alzheimer's Disease (AD) and its prodromal stage, Mild Cognitive Impairment …

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 …

[HTML][HTML] An effective multimodal image fusion method using MRI and PET for Alzheimer's disease diagnosis

J Song, J Zheng, P Li, X Lu, G Zhu, P Shen - Frontiers in digital health, 2021 - frontiersin.org
Alzheimer's disease (AD) is an irreversible brain disease that severely damages human
thinking and memory. Early diagnosis plays an important part in the prevention and …

Multi-modality cascaded convolutional neural networks for Alzheimer's disease diagnosis

M Liu, D Cheng, K Wang, Y Wang… - Neuroinformatics, 2018 - Springer
Accurate and early diagnosis of Alzheimer's disease (AD) plays important role for patient
care and development of future treatment. Structural and functional neuroimages, such as …

Ensemble of deep convolutional neural networks based multi‐modality images for Alzheimer's disease diagnosis

X Fang, Z Liu, M Xu - IET Image Processing, 2020 - Wiley Online Library
Alzheimer's disease (AD) is one of the most common progressive neurodegenerative
diseases. Structural magnetic resonance imaging (MRI) would provide abundant information …

[HTML][HTML] Explainable deep-learning-based diagnosis of Alzheimer's disease using multimodal input fusion of PET and MRI Images

M Odusami, R Maskeliūnas, R Damaševičius… - Journal of Medical and …, 2023 - Springer
Purpose Alzheimer's disease (AD) is a progressive, incurable human brain illness that
impairs reasoning and retention as well as recall. Detecting AD in its preliminary stages …

Latent feature representation with stacked auto-encoder for AD/MCI diagnosis

HI Suk, SW Lee, D Shen… - Brain Structure and …, 2015 - Springer
Recently, there have been great interests for computer-aided diagnosis of Alzheimer's
disease (AD) and its prodromal stage, mild cognitive impairment (MCI). Unlike the previous …

Multi-modal neuroimaging feature selection with consistent metric constraint for diagnosis of Alzheimer's disease

X Hao, Y Bao, Y Guo, M Yu, D Zhang, SL Risacher… - Medical image …, 2020 - Elsevier
The accurate diagnosis of Alzheimer's disease (AD) and its early stage, eg, mild cognitive
impairment (MCI), is essential for timely treatment or possible intervention to slow down AD …

Relation-induced multi-modal shared representation learning for Alzheimer's disease diagnosis

Z Ning, Q Xiao, Q Feng, W Chen… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The fusion of multi-modal data (eg, magnetic resonance imaging (MRI) and positron
emission tomography (PET)) has been prevalent for accurate identification of Alzheimer's …

Leveraging coupled interaction for multimodal Alzheimer's disease diagnosis

Y Shi, HI Suk, Y Gao, SW Lee… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
As the population becomes older worldwide, accurate computer-aided diagnosis for
Alzheimer's disease (AD) in the early stage has been regarded as a crucial step for …