Optimized Convolutional Fusion for Multimodal Neuroimaging in Alzheimer’s Disease Diagnosis: Enhancing Data Integration and Feature Extraction

Optimized Convolutional Fusion for Multimodal Neuroimaging in Alzheimer’s Disease Diagnosis: Enhancing Data Integration and Feature Extraction

Multimodal neuroimaging has gained traction in Alzheimer’s Disease (AD) diagnosis by integrating information from multiple imaging modalities to enhance classification accuracy. However, effectively handling heterogeneous data sources and overcoming the challenges posed by multiscale transform metho...

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Bibliographic Details
Main Authors: Modupe Odusami, Rytis Maskeliūnas, Robertas Damaševičius
Format: Article
Language:English
Published: MDPI AG 2023-10-01
Series:Journal of Personalized Medicine
Subjects:
Alzheimer’s disease
data integration
feature extraction
multimodal neuroimaging
optimized convolution
Online Access:https://www.mdpi.com/2075-4426/13/10/1496

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