Title: A cloud infrastructure for scalable computing on population imaging databanks

Authors: Ignacio Blanquer; Miguel Caballer; Luis Martí-Bonmatí; Ángel Alberich-Bayarri; María De la Iglesia; Jacobo Martínez

Addresses: Institute of Instrumentation for Molecular Imaging (I3M), Universitat Politècnica de València, Spain; GIBI230, Polytechnic University Hospital La Fe (HUPLF), Valencia, Spain ' Institute of Instrumentation for Molecular Imaging (I3M), Universitat Politècnica de València, Spain ' Biomedical Imaging Research Group (GIBI230) and Radiology Department, Hospital Universitario y Politécnico La Fe, Valencia, Spain ' Biomedical Imaging Research Group (GIBI230), La Fe Health Research Institute, Spain ' Centre of Excellence in Biomedical Image (CEIB), Regional Ministry of Health in the Valencia Region (CS), Brain Connectivity Lab. Unidad Mixta FISABIO/CIPF, Spain ' Valencian Biobank Network, Foundation for the Promotion of Health and Biomedical Research of Valencian Region (FISABIO), Valencia, Spain

Abstract: This article describes the software architecture designed to cope with the computing demand of research usage of complex data from the imaging biobank of the Regional Ministry of Health in the Valencia Region (CS). It proposes the use of self-configured virtual clusters on top of on-premise and public cloud infrastructures. It uses a model based on recipes and autoconfiguration to deploy virtual elastic clusters that adjust themselves to the actual workload of the study, therefore reducing operating costs and preventing the need of up-front investments both at the level of the imaging biobank or the final user. All the software used is released under open-source licenses.

Keywords: population imaging; cloud computing; virtual clusters; cloud infrastructure; imaging biobanks; scalable computing; software architecture; open source software; OSS; medical images; imaging biomarkers; metadata; Spain.

DOI: 10.1504/IJIM.2015.073015

International Journal of Image Mining, 2015 Vol.1 No.2/3, pp.175 - 188

Received: 29 Jan 2015
Accepted: 29 Jan 2015
Published online: 12 Nov 2015 *

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