A
Alzheimer's Disease Neuroimaging Initiative
Researcher at University of Granada
Publications - 6
Citations - 95
Alzheimer's Disease Neuroimaging Initiative is an academic researcher from University of Granada. The author has contributed to research in topics: Alzheimer's Disease Neuroimaging Initiative & Analysis of covariance. The author has an hindex of 5, co-authored 6 publications receiving 76 citations. Previous affiliations of Alzheimer's Disease Neuroimaging Initiative include University of Málaga.
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Journal ArticleDOI
Exploratory graphical models of functional and structural connectivity patterns for Alzheimer's Disease diagnosis.
Andrés Ortiz,Jorge Munilla,Ignacio Alvarez-Illán,Juan Manuel Górriz,Javier Ramírez,Alzheimer's Disease Neuroimaging Initiative,Alzheimer's Disease Neuroimaging Initiative +6 more
TL;DR: Sarse Inverse Covariance Estimation methods are used to learn undirected graphs in order to derive functional and structural connectivity patterns from Fludeoxyglucose (18F-FDG) Position Emission Tomography (PET) data and segmented Magnetic Resonance images (MRI) for Control, MCI (Mild Cognitive Impairment Subjects), and AD subjects.
Journal ArticleDOI
Construction and Analysis of Weighted Brain Networks from SICE for the Study of Alzheimer's Disease
Jorge Munilla,Andrés Ortiz,Juan Manuel Górriz,Javier Ramírez,Alzheimer's Disease Neuroimaging Initiative,Alzheimer's Disease Neuroimaging Initiative +5 more
TL;DR: In this article, the authors used sparse inverse covariance estimates (SICE) for deriving functional connectivity patterns from Positron Emission Tomography (PET) of brains affected by Alzheimer's Disease.
Journal ArticleDOI
Fusing Heterogeneous Data for Alzheimer's Disease Classification.
TL;DR: This work combines the features from neuroimaging and cerebrospinal fluid studies to distinguish Alzheimer's disease patients from healthy subjects and results indicate that multimodal data fusion improves classification accuracy.
Journal ArticleDOI
A Deep Learning Approach to Neuroanatomical Characterisation of Alzheimer's Disease.
TL;DR: This work uses ensemble learning methods and deep neural networks to identify salient structural correlations among brain regions that degenerate together in AD and provides an understanding of how AD progresses in the brain.
Journal ArticleDOI
Projecting MRI brain images for the detection of Alzheimer’s Disease
Francisco Jesús Martínez-Murcia,Juan Manuel Górriz,Javier Ramírez,Ignacio A. Illán,Diego Salas-Gonzalez,Fermín Segovia,Alzheimer's Disease Neuroimaging Initiative +6 more
TL;DR: A new method that simplifies the process of analysing 3D MRI brain images using a two dimensional projection is proposed, which outperforms other methods that use MRI, achieving up to a 86% of accuracy and significantly reducing the computational load.