Hdl Handle:
http://hdl.handle.net/10545/621406
Title:
Intelligent grid enabled services for neuroimaging analysis
Authors:
McClatchey, Richard; Habib, Irfan; Anjum, Ashiq; Munir, Kamran; Branson, Andrew; Bloodsworth, Peter; Kiani, Saad Liaquat
Abstract:
This paper reports our work in the context of the neuGRID project in the development of intelligent services for a robust and efficient Neuroimaging analysis environment. neuGRID is an EC-funded project driven by the needs of the Alzheimer's disease research community that aims to facilitate the collection and archiving of large amounts of imaging data coupled with a set of services and algorithms. By taking Alzheimer's disease as an exemplar, the neuGRID project has developed a set of intelligent services and a Grid infrastructure to enable the European neuroscience community to carry out research required for the study of degenerative brain diseases. We have investigated the use of machine learning approaches, especially evolutionary multi-objective meta-heuristics for optimising scientific analysis on distributed infrastructures. The salient features of the services and the functionality of a planning and execution architecture based on an evolutionary multi-objective meta-heuristics to achieve analysis efficiency are presented. We also describe implementation details of the services that will form an intelligent analysis environment and present results on the optimisation that has been achieved as a result of this investigation.
Affiliation:
University of West England; University of Derby; National University of Science and Technology
Citation:
McClatchey, R. et al (2013) 'Intelligent grid enabled services for neuroimaging analysis', Neurocomputing, 122:88
Publisher:
Elsevier
Journal:
Neurocomputing
Issue Date:
Dec-2013
URI:
http://hdl.handle.net/10545/621406
DOI:
10.1016/j.neucom.2013.01.042
Additional Links:
http://linkinghub.elsevier.com/retrieve/pii/S0925231213005559
Type:
Article
Language:
en
ISSN:
09252312
Sponsors:
European Commission
Appears in Collections:
Department of Electronics, Computing & Maths

Full metadata record

DC FieldValue Language
dc.contributor.authorMcClatchey, Richarden
dc.contributor.authorHabib, Irfanen
dc.contributor.authorAnjum, Ashiqen
dc.contributor.authorMunir, Kamranen
dc.contributor.authorBranson, Andrewen
dc.contributor.authorBloodsworth, Peteren
dc.contributor.authorKiani, Saad Liaquaten
dc.date.accessioned2017-02-17T11:48:56Z-
dc.date.available2017-02-17T11:48:56Z-
dc.date.issued2013-12-
dc.identifier.citationMcClatchey, R. et al (2013) 'Intelligent grid enabled services for neuroimaging analysis', Neurocomputing, 122:88en
dc.identifier.issn09252312-
dc.identifier.doi10.1016/j.neucom.2013.01.042-
dc.identifier.urihttp://hdl.handle.net/10545/621406-
dc.description.abstractThis paper reports our work in the context of the neuGRID project in the development of intelligent services for a robust and efficient Neuroimaging analysis environment. neuGRID is an EC-funded project driven by the needs of the Alzheimer's disease research community that aims to facilitate the collection and archiving of large amounts of imaging data coupled with a set of services and algorithms. By taking Alzheimer's disease as an exemplar, the neuGRID project has developed a set of intelligent services and a Grid infrastructure to enable the European neuroscience community to carry out research required for the study of degenerative brain diseases. We have investigated the use of machine learning approaches, especially evolutionary multi-objective meta-heuristics for optimising scientific analysis on distributed infrastructures. The salient features of the services and the functionality of a planning and execution architecture based on an evolutionary multi-objective meta-heuristics to achieve analysis efficiency are presented. We also describe implementation details of the services that will form an intelligent analysis environment and present results on the optimisation that has been achieved as a result of this investigation.en
dc.description.sponsorshipEuropean Commissionen
dc.language.isoenen
dc.publisherElsevieren
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S0925231213005559en
dc.rightsArchived with thanks to Neurocomputingen
dc.subjectIntelligent servicesen
dc.subjectMachine learningen
dc.subjectGrid enabled planning and executionen
dc.subjectService oriented architectureen
dc.subjectNeuroimagingen
dc.titleIntelligent grid enabled services for neuroimaging analysisen
dc.typeArticleen
dc.contributor.departmentUniversity of West Englanden
dc.contributor.departmentUniversity of Derbyen
dc.contributor.departmentNational University of Science and Technologyen
dc.identifier.journalNeurocomputingen
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