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Renal Function Estimation using Magnetic Resonance Images

Schwinger, Eyram A. Kojo
Master thesis
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URI
https://hdl.handle.net/1956/3770
Date
2009-06-02
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  • Department of Mathematics [656]
Abstract
This 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.
Publisher
The University of Bergen
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