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Tumor assessment using DCE-MRI image analysis
Šilhán, Jiří ; Zitová, Barbara (advisor) ; Jiřík, Radovan (referee)
This thesis deals with processing of data obtained by DCE-MRI, which uses magnetic resonance to track the propagation of contrast agents in the blo- odstream. Patient is given a contrast agent and then a series of images of the target area is taken. The output is a set of image data and perfusion maps. Work employs segmentation method which uses graph cuts to interactively look for the tumor, and evaluates it according to its shape properties. Study of whole data sets is simplified by image fusion methods.
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Comparison of the preclinical DCE-MRI perfusion techniques
Minsterová, Alžběta ; Jiřík, Radovan (referee) ; Macíček, Ondřej (advisor)
This diploma thesis deals with DCE-MRI (Dynamic Contrast-Enhanced Magnetic Resonance Imaging) thus one of the contrast magnetic resonance imaging methods. It describes the principle of conventional continuous DCE-MRI, which uses single bolus of contrast agent and further it focuses on the dual bolus contrast agent techniques, especially the interleaved acquisition. The graphical interface for processing Bruker systems data was made. Synthetic data were used to evaluate the influence of this method on the perfusion parameters estimation. Simulations proved that the further the second bolus is from the first one, the better results are. Simulations of acquisition interruption did not lead to the clear result. However, two statements, which are expected to lead to as good estimation of perfusion parameters as possible, were formulated
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Advanced signal processing methods in dynamic contrast enhanced magnetic resonance imaging
Bartoš, Michal ; Flusser,, Jan (referee) ; Mlynárik,, Vladimír (referee) ; Jiřík, Radovan (advisor)
Tato dizertační práce představuje metodu zobrazování perfúze magnetickou rezonancí, jež je výkonným nástrojem v diagnostice, především v onkologii. Po ukončení sběru časové sekvence T1-váhovaných obrazů zaznamenávajících distribuci kontrastní látky v těle začíná fáze zpracování dat, která je předmětem této dizertace. Je zde představen teoretický základ fyziologických modelů a modelů akvizice pomocí magnetické rezonance a celý řetězec potřebný k vytvoření obrazů odhadu parametrů perfúze a mikrocirkulace v tkáni. Tato dizertační práce je souborem uveřejněných prací autora přispívajícím k rozvoji metodologie perfúzního zobrazování a zmíněného potřebného teoretického rozboru.
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Scaling of arterial input function in DCE-MRI
Holeček, Tomáš ; Kolář, Radim (referee) ; Kratochvíla, Jiří (advisor)
Perfusion magnetic resonance imaging is modern diagnostic method used mainly in oncology. In this method, contrast agent is injected to the subject and then is continuously monitored the progress of its concentration in the affected area in time. Correct determination of the arterial input function (AIF) is very important for perfusion analysis. One possibility is to model AIF by multichannel blind deconvolution but the estimated AIF is necessary to be scaled. This master´s thesis is focused on description of scaling methods and their influence on perfussion parameters in dependence on used model of AIF in different tissues.
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Modelling in perfusion MR imaging
Válková, Hana ; Jiřík, Radovan (referee) ; Kratochvíla, Jiří (advisor)
This thesis deals with the magnetic resonance perfusion data analysis especially DCEMRI. In its introduction the thesis describes the problem of DCE-MRI data aquisition, the necessity of appropriate contrast agent and basic principles of perfusion analysis. The dynamic behavior of contrast agent vascular distribution can be described by arterial input function (AIF). The shape of the curves close to the area of interest is affected by dispersion which is called vascular transport function (VTF) due to the distribution of the contrast agent to the region of interest. Finally the tissue residual function describes system behavior of tissue. The practical part of the diploma thesis is aimed at implementation of model curves AIF, VTF and TRF. Furthermore, a simulation program was created for easy manipulation with introduced models moreover the program is used to perform an estimation of perfusion parameters based on nonblind deconvolution. The method is validated on synthetic data and illustrated on clinical data of the renal cell carcinoma patient.
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DCE-MRI Acquisition Methods
Kudlička, Petr ; Kratochvíla, Jiří (referee) ; Jiřík, Radovan (advisor)
In my master’s thesis I describe basics of magnetic resonance measurement. I focus on methods of DCE-MRI with T1 weighting image. I mention some basic contrast agents which are used in MRI imaging. I describe some of pulse sequences which are used in experimental part of my thesis. There I measure contrast in the sample. The measurement is performed in accordance with an acquisition protocol I have proposed. The experiment part was realized on 1.5 T magnet at Masaryk Oncological Institute in Brno. I improved software which is use to research of MR IR TurboFLASH’s data and made software which is use to evaluation perfuse analysis ours measured sequences. At the end I made a discussion about gained facts.
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Scaling of arterial input function in DCE-MRI
Holeček, Tomáš ; Kolář, Radim (referee) ; Kratochvíla, Jiří (advisor)
Perfusion magnetic resonance imaging is modern diagnostic method used mainly in oncology. In this method, contrast agent is injected to the subject and then is continuously monitored the progress of its concentration in the affected area in time. Correct determination of the arterial input function (AIF) is very important for perfusion analysis. One possibility is to model AIF by multichannel blind deconvolution but the estimated AIF is necessary to be scaled. This master´s thesis is focused on description of scaling methods and their influence on perfussion parameters in dependence on used model of AIF in different tissues.
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Compressed sensing for MRI perfusion imaging
Daňková, M. ; Rajmic, P. ; Jiřík, Radovan
Perfusion MRI is a diagnostic method in medicine. The signal captured from the affected area can be described by the curve of lognormal distribution. The standard way of obtaining the measurements is very slow and does not comply with today's challenging requirements. Using compressed sensing, we propose to acquire much less coefficients, having minimal effect on the signal reconstruction (using the assumption that the data is a sum of low-rank matrix and sparse matrix in row spectrum).
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