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Data analysis for quantitative MR relaxometry
 Páralová, Hana ; Jiřík, Radovan (oponent) ; Mézl, Martin (vedoucí práce)
This work deals with the implementation of an algorithm for data analysis for quantitative magnetic resonance relaxometry. Magnetic resonance (MR) is a non-invasive imaging technique using the magnetic properties of atomic nuclei. The motivation for the use of relaxation parameters of tissue is scanner-independent diagnostics. The work describes the essential theoretical foundations of MR mechanisms and the contrast mechanisms. Using them, an algorithm in Python is designed for fitting the relaxation parameters of the sample. Fitting is done according to an exponential model functions for three different combinations of parameters - individual fitting of T1 or T2 relaxation time and simultaneous fitting of both times. A locally linearized model and Cramer-Rao lower bounds are used to calculate the standard deviation of the fitted parameters. The results of the work were successfully verified on a fixed rat brain relaxometry.
Úplný záznam
Data analysis for quantitative MR relaxometry
 Páralová, Hana ; Jiřík, Radovan (oponent) ; Mézl, Martin (vedoucí práce)
This work deals with the implementation of an algorithm for data analysis for quantitative magnetic resonance relaxometry. Magnetic resonance (MR) is a non-invasive imaging technique using the magnetic properties of atomic nuclei. The motivation for the use of relaxation parameters of tissue is scanner-independent diagnostics. The work describes the essential theoretical foundations of MR mechanisms and the contrast mechanisms. Using them, an algorithm in Python is designed for fitting the relaxation parameters of the sample. Fitting is done according to an exponential model functions for three different combinations of parameters - individual fitting of T1 or T2 relaxation time and simultaneous fitting of both times. A locally linearized model and Cramer-Rao lower bounds are used to calculate the standard deviation of the fitted parameters. The results of the work were successfully verified on a fixed rat brain relaxometry.
Úplný záznam

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