Title :
An automated supervised method for the diagnosis of Alzheimer’s disease based on fMRI data using weighted voting schemes
Author :
Tripoliti, Evathia E. ; Fotiadis, Dimitrios I. ; Argyropoulou, Maria
Author_Institution :
Dept. of Comput. Sci., Univ. of Ioannina, Ioannina
Abstract :
We present an automated supervised method which assists in the diagnosis of Alzheimerpsilas disease (AD) using fMRI data. The method consists of five stages: a) preprocessing of fMRI data to remove motion and spatial noise artifacts, b) modeling of the data using generalized linear models (GLM), c) feature extraction, d) feature selection and e) classification using majority and weighted voting schemes.
Keywords :
biomedical MRI; diseases; feature extraction; image classification; medical image processing; neurophysiology; Alzheimer disease; automated supervised method; feature classification; feature extraction; feature selection; functional magnetic resonance imaging; generalized linear models; weighted voting schemes; Alzheimer´s disease; Biomedical imaging; Data mining; Feature extraction; Magnetic resonance imaging; Medical diagnostic imaging; Positron emission tomography; Senior citizens; Testing; Voting; Alzheimer’s disease; Random Forests; functional MRI; weighted voting;
Conference_Titel :
Imaging Systems and Techniques, 2008. IST 2008. IEEE International Workshop on
Conference_Location :
Crete
Print_ISBN :
978-1-4244-2496-2
Electronic_ISBN :
978-1-4244-2497-9
DOI :
10.1109/IST.2008.4659997
