|
|
Unfolded Low-rank + Sparse Reconstruction for MRI
Mokrý, O. ; Vitouš, Jiří
We apply the methodology of deep unfolding on the problem of reconstruction of DCE-MRI data. The problem is formulated as a convex optimization problem, solvable via the primal-dual splitting algorithm. The unfolding allows for optimal hyperparameter selection for the model. We examine two approaches - with the parameters shared across the layers/iterations, and an adaptive version where the parameters can differ. The results demonstrate that the more complex model can better adapt to the data.
|
|
|
Automatic Processing of DCE-MRI Data
Karela, Jiří ; Mézl, Martin (referee) ; Jiřík, Radovan (advisor)
This master thesis deals with the issue of automatic processing of DCE-MRI data. It describes some important procedures and methods. The work is divided into theoretical part, practical part and conclusion. The theoretical part mainly describes some methods, on the basis of which the practical part was then solved. However, another theory related to the topic is also described here. The practical part then builds on the theory and solves the problem of automatic detection of arterial voxels and the concentration of contrast agent in the arteries. The algorithms are tested on rat brain data obtained from DCE-MRI. The conclusion serves as a summary and evaluation of our results. It also serves as a reflection on the implementation of our methods.
|
|
|
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.
|
|
|
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.
|
|
|
Comparison of Pharmacokinetic models for DCE-MRI
Bačovská, Kristýna ; Mézl, Martin (referee) ; Jiřík, Radovan (advisor)
This thesis deals with perfusion analysis using DCE-MRI (Dynamic contrast-enhanced magnetic resonance imaging). DCE-MRI is commonly used for microcirculation evaluation mainly in oncology and in recent years also in cardiology. The theoretical overview focuses on the issue of pharmacokinetic modeling and the estimation of perfusion parameters using selected models. The experimental part describes research software PerfLab and then it is aimed at the proposed program for synthetic data generation. Simulated data obtained under ideal conditions and in the presence of noise were used to compare models for the accuracy and reliability of DCE-MRI analysis.
|
|
|
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.
|
|
| |
|
|
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
|
|
|
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.
|
|
|
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.
|
guest ::
