End-to-End Deep Learning Architectures Using 3D Neuroimaging Biomarkers for Early Alzheimer’s Diagnosis

End-to-End Deep Learning Architectures Using 3D Neuroimaging Biomarkers for Early Alzheimer’s Diagnosis

This study uses magnetic resonance imaging (MRI) data to propose end-to-end learning implementing volumetric convolutional neural network (CNN) models for two binary classification tasks: Alzheimer’s disease (AD) vs. cognitively normal (CN) and stable mild cognitive impairment (sMCI) vs. AD. The bas...

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Bibliographic Details
Main Authors: Deevyankar Agarwal, Manuel Alvaro Berbis, Teodoro Martín-Noguerol, Antonio Luna, Sara Carmen Parrado Garcia, Isabel de la Torre-Díez
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Mathematics
Subjects:
Alzheimer’s disease
CNN
deep learning
end-to-end learning
MCI
MRI
Online Access:https://www.mdpi.com/2227-7390/10/15/2575

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