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Title:Computation cloud to enable high throughput neuroimaging
Author(s):Wetter Taylor, Nathaniel Craig
Advisor(s):Sutton, Bradley P.
Department / Program:Bioengineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Cloud computing
Magnetic resonance imaging
Image processing
Multiple sclerosis
Abstract:Neuroimaging studies require significant computational power in order to perform non-linear registrations, 3D volumetric segmentations, and statistical analysis across a large group of subjects. In addition to the need for this large computational infrastructure, the large number of open-source programs being used to process data has increased in recent years making it standard for several packages, each one frequently and independently updated, to be used in a single analysis. Due to these needs, the focus of computational infrastructure in neuroimaging is transitioning from user-owned hardware, to virtualized, shared, and scalable “cloud”-based hardware. We have implemented such a “private cloud” for neuroimaging and deployed it to users of the Beckman Institute Bioimaging Center. This thesis aims to demonstrate the scientific advantage for neuroimaging from such a system, to serve as a guide for users and administrators, and to provide implementation details to other groups who may wish to build a similar cloud of their own. In the final chapter, we present a sample application—a novel, open source method for the detection and quantification of multiple sclerosis lesions on MRI images. Like many neuroimaging applications, this method takes a great deal of time to process all subjects, highlighting the practicality of the flexible, shared infrastructure of the private cloud for bioimaging research.
Issue Date:2015-07-14
Rights Information:Copyright 2015 Nathaniel C Wetter Taylor
Date Available in IDEALS:2015-09-29
Date Deposited:August 201

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