Alzheimer’s Disease Early Detection Using a Low Cost Three-Dimensional Densenet-121 Architecture
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Authors
Solano Rojas, Braulio José
Villalón Fonseca, Ricardo
Marín Raventós, Gabriela
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Abstract
The objective of this work is to detect Alzheimer’s disease using Magnetic Resonance Imaging. For this, we use a three-dimensional densenet-121 architecture. With the use of only freely available tools, we obtain good results: a deep neural network showing metrics of 87% accuracy, 87% sensitivity (micro-average), 88% specificity (micro-average), and 92% AUROC (micro-average) for the task of classifying five different classes (disease stages). The use of tools available for free means that this work can be replicated in developing countries.
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Keywords
Alzheimer, Deep learning, MRI, Computer-aided detection, Computer-aided diagnosis
Citation
https://link.springer.com/chapter/10.1007/978-3-030-51517-1_1