Intelligent grid enabled services for neuroimaging analysis

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. © 2013 Elsevier B.V.

• Journal Article Type: Article
• Publication Date: Dec 25, 2013
• Deposit Date: Aug 8, 2013
• Journal: Neurocomputing
• Print ISSN: 0925-2312
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 122
• Pages: 88-99
• DOI: https://doi.org/10.1016/j.neucom.2013.01.042
• Keywords: intelligent services, machine learning and genetic algorithms, grid enabled planning and execution,; service oriented architecture, neuroimaging analysis
• Public URL: https://uwe-repository.worktribe.com/output/925568
• Publisher URL: http://dx.doi.org/10.1016/j.neucom.2013.01.042
• Contract Date: Apr 13, 2016