Construction of MRI-Based Alzheimer’s Disease Score Based on Efficient 3D Convolutional Neural Network: Comprehensive Validation on 7,902 Images from a Multi-Center Dataset | Zendy

Evangeline Yee | Zendy; Da Ma | Zendy; Karteek Popuri | Zendy; Lei Wang | Zendy; Mirza Faisal Beg | Zendy

Open Access

Construction of MRI-Based Alzheimer’s Disease Score Based on Efficient 3D Convolutional Neural Network: Comprehensive Validation on 7,902 Images from a Multi-Center Dataset

Author(s) -

Evangeline Yee,

Da Ma,

Karteek Popuri,

Lei Wang,

Mirza Faisal Beg

Publication year - 2020

Publication title -

journal of alzheimer s disease

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.677

H-Index - 139

eISSN - 1875-8908

pISSN - 1387-2877

DOI - 10.3233/jad-200830

Subject(s) - generalizability theory , convolutional neural network , computer science , artificial intelligence , dementia , generalization , alzheimer's disease neuroimaging initiative , neuroimaging , pattern recognition (psychology) , test set , set (abstract data type) , machine learning , disease , neuroscience , pathology , medicine , mathematics , psychology , statistics , mathematical analysis , programming language

In recent years, many convolutional neural networks (CNN) have been proposed for the classification of Alzheimer's disease. Due to memory constraints, many of the proposed CNNs work at a 2D slice-level or 3D patch-level.

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