Alzheimer's disease diagnostics by a 3D deeply supervised adaptable convolutional network

Early diagnosis is playing an important role in preventing progress of the Alzheimer's disease (AD). This paper proposes to improve the prediction of AD with a deep 3D Convolutional Neural Network (3D-CNN), which can show generic features capturing AD biomarkers extracted from brain images, ada...

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Bibliographic Details

Published in:	Frontiers in bioscience (Landmark. Print) Vol. 23; no. 3; p. 584
Main Authors:	Hosseini-Asl, Ehsan, Ghazal, Mohammed, Mahmoud, Ali, Aslantas, Ali, Shalaby, Ahmed M, Casanova, Manual F, Barnes, Gregory N, Gimel'farb, Georgy, Keynton, Robert, El-Baz, Ayman
Format:	Journal Article
Language:	English
Published:	Singapore 01.01.2018
Subjects:	Algorithms Alzheimer Disease - diagnostic imaging Humans Imaging, Three-Dimensional - methods Magnetic Resonance Imaging - methods Neural Networks, Computer Reproducibility of Results Sensitivity and Specificity
ISSN:	2768-6698, 2768-6698
Online Access:	Get more information
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