A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages

Neuroimaging has made it possible to measure pathological brain changes associated with Alzheimer's disease (AD) in vivo. Over the past decade, these measures have been increasingly integrated into imaging signatures of AD by means of classification frameworks, offering promising tools for indi...

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Vydané v:	NeuroImage (Orlando, Fla.) Ročník 155; s. 530 - 548
Hlavní autori:	Rathore, Saima, Habes, Mohamad, Iftikhar, Muhammad Aksam, Shacklett, Amanda, Davatzikos, Christos
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States Elsevier Inc 15.07.2017 Elsevier Limited
Predmet:	Algorithms Alzheimer Disease - classification Alzheimer Disease - diagnostic imaging Alzheimer's disease Brain research Classification Cognitive ability Cognitive Dysfunction - classification Cognitive Dysfunction - diagnosis Cortex Diagnosis Feature extraction Functional magnetic resonance imaging Hippocampus Humans Machine Learning Medical imaging Metabolic rate Mild cognitive impairment Neural networks Neurodegenerative diseases Neuroimaging NMR Nuclear magnetic resonance Positron emission tomography Prodromal Symptoms Reviews Substantia alba ADNI FDG-PET Neuroimaging sMRI MRI Mild cognitive impairment LR rs-fMRI LDA RVM RAVENS SVM DMAF AUC OASIS sMCI WM CSF Classification mRMR RLR Alzheimer's disease VBM AD DMN GM CN AAL LPBM ROI fMRI MCI SVM-RFE pMCI Machine learning DTI Feature extraction VAF SPARE-AD
ISSN:	1053-8119, 1095-9572, 1095-9572
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