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dc.contributor.authorSchwinger, Eyram A. Kojoeng
dc.date.accessioned2010-02-02T09:00:42Z
dc.date.available2010-02-02T09:00:42Z
dc.date.issued2009-06-02eng
dc.date.submitted2009-06-02eng
dc.identifier.urihttps://hdl.handle.net/1956/3770
dc.description.abstractThis study is aimed at testing the use of Magnetic Resonance (MR) images and mathematical models for renal parameter estimation. The study was based on four models; the Patlak model, Cortical Compartment model, Separable Compartment/Sourbron model and Deconvolution method. The project included the mathematical derivation of the model. The models were then applied to whole Kidney MRI images in order to get and compare parameters. Part of the project also included the visualization of the parameters produced by the models on a voxel-by-voxel basis. The project showed that of the four models the Deconvolution method produces the highest parameter values followed by the Patlak model. The Cortical Compartment and Sourbron models produce almost similar results. The voxel-by-voxel visualization also showed that only the renal cortex produces high flow results.en_US
dc.format.extent1949732 byteseng
dc.format.mimetypeapplication/pdfeng
dc.language.isoengeng
dc.publisherThe University of Bergenen_US
dc.titleRenal Function Estimation using Magnetic Resonance Imagesen_US
dc.typeMaster thesis
dc.rights.holderThe authoren_US
dc.rights.holderCopyright the author. All rights reserveden_US
dc.description.localcodeMAMN-MAB
dc.description.localcodeMAB399
dc.subject.nus753109eng
dc.subject.nsiVDP::Matematikk og Naturvitenskap: 400::Matematikk: 410nob
fs.subjectcodeMAB399


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