GLM Analysis for fMRI using Connex Array

In the last decades, magnetic resonance imaging gained lot of popularity, and also functional magnetic resonance imaging (fMRI), due to the fact that MRI is a harmless and efficient technique for human cerebral activity studies; fMRI aims to determine and to locate different brain activities when th...

Full description

Saved in:
Bibliographic Details
Published inInternational journal of computers, communications & control Vol. 9; no. 6; p. 768
Main Author Ţugui, Andrei
Format Journal Article
LanguageEnglish
Published Oradea Agora University of Oradea 01.12.2014
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:In the last decades, magnetic resonance imaging gained lot of popularity, and also functional magnetic resonance imaging (fMRI), due to the fact that MRI is a harmless and efficient technique for human cerebral activity studies; fMRI aims to determine and to locate different brain activities when the subject is doing a predetermined task. In addition, using fMRI analysis, nowadays we can make prediction on several diseases. This paper’s purpose is to describe the General Linear Model for fMRI statistical analysis algorithm, for a 64 x 64 x 22 voxels dataset on a revolutionary parallel computing machine, Connex Array. We make a comparison to other computing machines used in the same purpose, in terms of algorithm time execution (statistical analysis speed). We will show that by taking advantage on its specific parallel computation each step in GLM analysis, Connex Array is able to answer successfully to computational challenge launched by fMRI computation: thespeed-up.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1841-9836
1841-9844
DOI:10.15837/ijccc.2014.6.1482