title: Hyperbolic Space Sparse Coding with Its Application on Prediction of Alzheimer's Disease in Mild Cognitive Impairment.
abstract: Mild Cognitive Impairment (MCI) is a transitional stage between normal age-related cognitive decline and Alzheimer's disease (AD). Here we introduce a hyperbolic space sparse coding method to predict impending decline of MCI patients to dementia using surface measures of ventricular enlargement. First, we compute diffeomorphic mappings between ventricular surfaces using a canonical hyperbolic parameter space with consistent boundary conditions and surface tensor-based morphometry is computed to measure local surface deformations. Second, ring-shaped patches of TBM features are selected according to the geometric structure of the hyperbolic parameter space to initialize a dictionary. Sparse coding is then applied on the patch features to learn sparse codes and update the dictionary. Finally, we adopt max-pooling to reduce the feature dimensions and apply Adaboost to predict AD in MCI patients (N= 133) from the Alzheimer's Disease Neuroimaging Initiative baseline dataset. Our work achieved an accuracy rate of 96.7% and outperformed some other morphometry measures. The hyperbolic space sparse coding method may offer a more sensitive tool to study AD and its early symptom.
authors.affiliation: School of Computing, Informatics, and Decision Systems Engineering, Arizona State Univ., Tempe, AZ.
authors.forename: Jie
authors.initials: J
authors.lastname: Zhang
authors.affiliation: School of Computing, Informatics, and Decision Systems Engineering, Arizona State Univ., Tempe, AZ.
authors.forename: Jie
authors.initials: J
authors.lastname: Shi
authors.affiliation: Dept. of Psychiatry and Psychology, Mayo Clinic Arizona, Scottsdale, AZ.
authors.forename: Cynthia
authors.initials: C
authors.lastname: Stonnington
authors.affiliation: School of Computing, Informatics, and Decision Systems Engineering, Arizona State Univ., Tempe, AZ.
authors.forename: Qingyang
authors.initials: Q
authors.lastname: Li
authors.affiliation: Imaging Genetics Center, Institute for Neuroimaging and Informatics, Univ. of Southern California, Marina del Rey, CA.
authors.forename: Boris A
authors.initials: BA
authors.lastname: Gutman
authors.affiliation: Banner Alzheimer's Institute and Banner Good Samaritan PET Center, Phoenix, AZ.
authors.forename: Kewei
authors.initials: K
authors.lastname: Chen
authors.affiliation: Banner Alzheimer's Institute and Banner Good Samaritan PET Center, Phoenix, AZ.
authors.forename: Eric M
authors.initials: EM
authors.lastname: Reiman
authors.affiliation: Dept. of Neurology, Mayo Clinic Arizona, Scottsdale, AZ.
authors.forename: Richard J
authors.initials: RJ
authors.lastname: Caselli
authors.affiliation: Imaging Genetics Center, Institute for Neuroimaging and Informatics, Univ. of Southern California, Marina del Rey, CA.
authors.forename: Paul M
authors.initials: PM
authors.lastname: Thompson
authors.affiliation: Dept. of Computational Medicine and Bioinformatics, Univ. of Michigan, Ann Arbor, MI.
authors.forename: Jieping
authors.initials: J
authors.lastname: Ye
authors.affiliation: School of Computing, Informatics, and Decision Systems Engineering, Arizona State Univ., Tempe, AZ.
authors.forename: Yalin
authors.initials: Y
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D000544:Alzheimer Disease / Q000473:pathology*; D002552:Cerebral Ventricles / Q000473:pathology*; D060825:Cognitive Dysfunction / Q000473:pathology*; D018450:Disease Progression; D006801:Humans; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Hyperbolic Parameter Space; Mild Cognitive Impairment; Ring-shaped Patches; Sparse Coding and Dictionary Learning