Locally linear embedding (LLE) for MRI based Alzheimer's disease classification

• Published in: NeuroImage (Orlando, Fla.) Vol. 83; pp. 148 - 157
• Main Authors: Liu, Xin, Tosun, Duygu, Weiner, Michael W., Schuff, Norbert
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.12.2013; Elsevier Limited
• Subjects: Accuracy; Aged; Algorithms; Alzheimer Disease - pathology; Alzheimer's disease; Artificial Intelligence; Brain - pathology; Brain research; Classification; Classification of AD; Computer Simulation; Discriminant analysis; Female; Humans; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Linear Models; Locally linear embedding; Magnetic Resonance Imaging - methods; Male; Medical imaging; Methods; Middle Aged; MRI; NMR; Nuclear magnetic resonance; Pattern Recognition, Automated - methods; Remote sensing; Reproducibility of Results; Sensitivity and Specificity; Statistical learning; Statistical learning; MRI; Alzheimer's disease; Classification of AD; Locally linear embedding

Modern machine learning algorithms are increasingly being used in neuroimaging studies, such as the prediction of Alzheimer's disease (AD) from structural MRI. However, finding a good representation for multivariate brain MRI features in which their essential structure is revealed and easily ex...