Cited by 106Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatmentsFunctional Brain Connectivity Studies

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

Ning, Zhenyuan, Xiao, Qing, Feng, Qianjin, Chen, Wufan, Zhang, Yu·2021·IEEE Transactions on Medical Imaging

Abstract

The fusion of multi-modal data (e.g., magnetic resonance imaging (MRI) and positron emission tomography (PET)) has been prevalent for accurate identification of Alzheimer's disease (AD) by providing complementary structural and functional information. However, most of the existing methods simply concatenate multi-modal features in the original space and ignore their underlying associations which may provide more discriminative characteristics for AD identification. Meanwhile, how to overcome the overfitting issue caused by high-dimensional multi-modal data remains appealing. To this end, we propose a relation-induced multi-modal shared representation learning method for AD diagnosis. The proposed method integrates representation learning, dimension reduction, and classifier modeling into a unified framework. Specifically, the framework first obtains multi-modal shared representations by learning a bi-directional mapping between original space and shared space. Within this shared space, we utilize several relational regularizers (including feature-feature, feature-label, and sample-sample regularizers) and auxiliary regularizers to encourage learning underlying associations inherent in multi-modal data and alleviate overfitting, respectively. Next, we project the shared representations into the target space for AD diagnosis. To validate the effectiveness of our proposed approach, we conduct extensive experiments on two independent datasets (i.e., ADNI-1 and ADNI-2), and the experimental results demonstrate that our proposed method outperforms several state-of-the-art methods.

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Crossref · 10.1109/tmi.2021.3063150

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Authors
Ning, Z., Xiao, Q., Feng, Q., Chen, W., & Zhang, Y.
Affiliations
Southern Medical University (CN)
Venue
IEEE Transactions on Medical Imaging
Published
2021-06
Volume
40
Issue
6
Pages
1632-1645
ISSN
  • 0278-0062 (ISSN-L)
  • 1558-254X
OpenAlex
W3134105939
Cited by
106
References
41
Citations by year
2026: 15 · 2025: 28 · 2024: 26 · 2023: 23 · 2022: 12 · 2021: 2
FWCI
11.29
Type
journal article
Language
en
Open access
closed
Locations
  • IEEE Transactions on Medical Imaging (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Natural Science Foundation of China (61971213, 61671230)
  • Basic and Applied Basic Research Foundation of Guangdong Province (No.2019A1515010417)
  • Guangdong Provincial Key Laboratory of Medical Image Processing (2020B1212060039)
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Keywords
Alzheimer's disease diagnosis, MRI-PET fusion, overfitting, dimensionality reduction, ADNI
MeSH terms
Alzheimer Disease, Humans, Magnetic Resonance Imaging, Tomography, X-Ray Computed, Positron-Emission Tomography, Neuroimaging

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