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Advanced Methods of Perfusion Analysis in MRI
Macíček, Ondřej ; Frollo, Ivan (referee) ; Mikl, Michal (referee) ; Jiřík, Radovan (advisor)
This dissertation deals with quantitative perfusion analysis of MRI contrast-enhanced image time sequences. It focuses on two so far separately used methods -- Dynamic contrast-enhanced MRI (DCE-MRI) and Dynamic susceptibility contrast MRI (DSC-MRI). The common problem of such perfusion analyses is the unreliability of perfusion parameters estimation. This penalizes usage of these unique techniques on a regular basis. The presented methods are intended to improve these drawbacks, especially the problems with quantification in DSC in case of contrast agent extravasation and instability of the deconvolution process in DCE using advanced pharmacokinetic models. There are a few approaches in literature combining DCE and DSC to estimate new parameters of the examined tissue, namely the relaxivity of the vascular and of the interstitial space. Originally, in this scheme, the 2CXM DCE model was used. Here various models for DCE analysis are tested keeping in mind the DCE-DSC combination. The ATH model was found to perform better in this setting compared to 2CXM. Finally, the ATH model was used in alternating DCE-DSC optimization algorithm and then in a truly fully simultaneous DCE-DSC. The processing was tested using simulated and in-vivo data. According to the results, the proposed simultaneous algorithm performs better in comparison with sequential DCE-DSC, unleashing full potential of perfusion analysis using MRI.
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Multiparametric segmentation of MR images
Chovanec, Ján ; Šmirg, Ondřej (referee) ; Dvořák, Pavel (advisor)
The aim of the thesis was familiarity of segmentation methods for automatic segmentation of MR images, using multiparametrical display. The theoretical part focuses on the description of methods of segmentation techniques. In the practical part are implemented K-means and level-set method. The methods are tested on the images of the brain obtained by different sequences (T1, T1c, T2, FLAIR). Segmentation methods are implemented in the program MATLAB. Implemented segmentation accuracy is demonstrated on data which there are reports reference results. Evaluation methods is performed using different classifiers decision. The K-means method is tested different metrics and different combinations of the input image. Finally, both methods are compared with one another and visually evaluated against the reference image.
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Relaxation times in the polymer gel electrolytes by magnetic resonance methods
Jehličková, Lenka ; Kadlec, Radim (referee) ; Kubásek, Radek (advisor)
The purpose of this Bachelor’s thesis is measuring of gelly structure relaxation using magnetic resonance imaging. The first part closely describes the theory needed for upcoming measuring. There is explained basic physical principle of NMR and terms such as precession, Larmor frequency and RF pulses are established. The measuring instrument is also schematically introduced, as are its main parts and division in aspect of magnetic fields. The most important part is explanation and understanding of relaxation processes that happen during NMR. Individual sequences used for measuring of relaxation processes are demonstrated by the spin echo method, which is the basic building block of all successive methods. The second part is processing of results. Measuring of fall and spectre of given gelly samples is expressed as a function of time T2 on the sample solidification time.
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Advanced Methods of Perfusion Analysis in MRI
Macíček, Ondřej ; Frollo, Ivan (referee) ; Mikl, Michal (referee) ; Jiřík, Radovan (advisor)
This dissertation deals with quantitative perfusion analysis of MRI contrast-enhanced image time sequences. It focuses on two so far separately used methods -- Dynamic contrast-enhanced MRI (DCE-MRI) and Dynamic susceptibility contrast MRI (DSC-MRI). The common problem of such perfusion analyses is the unreliability of perfusion parameters estimation. This penalizes usage of these unique techniques on a regular basis. The presented methods are intended to improve these drawbacks, especially the problems with quantification in DSC in case of contrast agent extravasation and instability of the deconvolution process in DCE using advanced pharmacokinetic models. There are a few approaches in literature combining DCE and DSC to estimate new parameters of the examined tissue, namely the relaxivity of the vascular and of the interstitial space. Originally, in this scheme, the 2CXM DCE model was used. Here various models for DCE analysis are tested keeping in mind the DCE-DSC combination. The ATH model was found to perform better in this setting compared to 2CXM. Finally, the ATH model was used in alternating DCE-DSC optimization algorithm and then in a truly fully simultaneous DCE-DSC. The processing was tested using simulated and in-vivo data. According to the results, the proposed simultaneous algorithm performs better in comparison with sequential DCE-DSC, unleashing full potential of perfusion analysis using MRI.
|
|
|
Relaxation times in the polymer gel electrolytes by magnetic resonance methods
Jehličková, Lenka ; Kadlec, Radim (referee) ; Kubásek, Radek (advisor)
The purpose of this Bachelor’s thesis is measuring of gelly structure relaxation using magnetic resonance imaging. The first part closely describes the theory needed for upcoming measuring. There is explained basic physical principle of NMR and terms such as precession, Larmor frequency and RF pulses are established. The measuring instrument is also schematically introduced, as are its main parts and division in aspect of magnetic fields. The most important part is explanation and understanding of relaxation processes that happen during NMR. Individual sequences used for measuring of relaxation processes are demonstrated by the spin echo method, which is the basic building block of all successive methods. The second part is processing of results. Measuring of fall and spectre of given gelly samples is expressed as a function of time T2 on the sample solidification time.
|
|
|
Multiparametric segmentation of MR images
Chovanec, Ján ; Šmirg, Ondřej (referee) ; Dvořák, Pavel (advisor)
The aim of the thesis was familiarity of segmentation methods for automatic segmentation of MR images, using multiparametrical display. The theoretical part focuses on the description of methods of segmentation techniques. In the practical part are implemented K-means and level-set method. The methods are tested on the images of the brain obtained by different sequences (T1, T1c, T2, FLAIR). Segmentation methods are implemented in the program MATLAB. Implemented segmentation accuracy is demonstrated on data which there are reports reference results. Evaluation methods is performed using different classifiers decision. The K-means method is tested different metrics and different combinations of the input image. Finally, both methods are compared with one another and visually evaluated against the reference image.
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