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Fluorescence imaging techniques in multimodal holographic microscope
Vašíček, David ; Procházková, Jana (referee) ; Čolláková, Jana (advisor)
The diploma thesis deals with the registration of images taken with the multimodal holographic microscope (MHM). The summary covers the fluorescent and holographic microscopy, and the multimodal holographic microscope combining both these microscopy types. Every pair of the images needs to be aligned in order to gain new information by combining both image types. The thesis contains an algorithm that registers images by phase correlation as well as a process created in MATLAB in accordance with the algorithm. The most important procedure parameters’ influence on the registration success is described and the results are annotated.
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Image analysis for correction of electron microscopes
Smital, Petr ; Schwarz, Daniel (referee) ; Kolář, Radim (advisor)
This thesis describes the physical nature of corrections of an electron microscope and mathematical methods of image processing required for their complete automation. The corrections include different types of focusing, astigmatism correction, electron beam centring, and image stabilisation. The mathematical methods described in this thesis include various methods of measuring focus and astigmatism, with and without using the Fourier transform, edge detection, histogram operations, and image registration, i.e. detection of spatial transformations in images. This thesis includes detailed descriptions of the mathematical methods, their evaluation using an “offline” application, descriptions of the algorithms of their implementation into an actual electron microscope and results of their testing on the actual electron microscope, in the form of a video footage grabbed from its control computer’s screen.
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Phase-correlation based image registration
Druckmüllerová, Hana ; Martišek, Dalibor (referee) ; Procházková, Jana (advisor)
Tato práce se zabývá použitím fázové korelace k určení vzájemné rotace, změny měřítka a posunu mezi digitálními obrazy. Fázová korelace je založena na Fourierově transformaci, proto je popsána Fourierova transformace funkcí definovaných na R^2 i diskrétní Fourierova transformace funkcí definovaných na konečném počtu bodů {0, 1, ... , N-1}^2, kde N je přirozené číslo. Dále je pozornost věnována modifikacím fázové korelace, díky nimž metoda umožňuje nalezení parametrů podobnostní transformace i mezi obrazy, které mají vysoký dynamický rozsah a slabě patrné struktury, obsahují aditivní nebo impulzní šum a jsou pořízeny pomocí různých snímačů a optických soustav. Obsahem práce jsou i modifikace metody pro snímky sluneční koróny pořízené během úplných zatmění Slunce, což patří mezi nejobtížnější úlohy registrace obrazů.
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Machine learning for analysis of MR images of brain
Král, Jakub ; Říha, Ivo (referee) ; Provazník, Ivo (advisor)
The thesis is focused on methods of machine learning used for recognising the first stage of schizophrenia in images from nuclear-magnetic resonance. The introduction of this paper is focused primarily on physical principles. Further in this work, the attention is given to registration methods, reduction of data set and machine learning. In the classification part, simmilarity rates, support vectors´ method, K-nearest neighbour classification and K-means are described. The last stage of theoretical part is focused on evaluation of the clasification. In practical part the results of reduction data set by methods PCA, CRLS-PCA and subjects PCA are described. Furthermore, the practical part is focused on pattern recognition by methods K-NN, K-means and test K-NN method on real data. Abnormalities which are recognised by some classification methods can distinguish patients with schizophrenia from healthy controls.
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Automatic segmentation of regions of interest in a human vertebra
Novosadová, Michaela ; Jan, Jiří (referee) ; Peter, Roman (advisor)
This bachelor´s thesis describes anatomy of the spine and the most frequent pathologies of the spine with focus on those tumour diseases, that affect more and more people today. The other part of the work describes theory of image registration. The aim of this thesis is to create an algorithm able to do automatic segmentation of regions of interest in human vertebra (body and posterior elements). This segmentation can simplify the classification of tumour diseases of the spine in the future. A solution was designed on the base of theoretical knowledge. This solution is based on registration of segmented models on original vertebrae. The thesis also describes the process of the solution. For easier understanding, the process of solution and the evaluation of results are added with number of graphs, images and tables.
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Optimization method based on TRUST for image registration
Pernicová, Lenka ; Mézl, Martin (referee) ; Harabiš, Vratislav (advisor)
The aim of the thesis is optimization for a medical images registration. The basis is to acquaint with the images registration and to peruse component global optimization methods, especially an optimization method TRUST. After theoretic knowledge it is possible to proceed to a suggestion of an optimization method based on the TRUST method and to realize in the program setting MATLAB. Created algorithms has been tested on test data and compared with other optimization methods as Simulated annealing.
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Image database system for glaucoma diagnosis support
Peter, Roman ; Roleček, Jiří (referee) ; Kolář, Radim (advisor)
Tato práce popisuje přehled standardních a pokročilých metod používaných k diagnose glaukomu v ranném stádiu. Na základě teoretických poznatků je implementován internetově orientovaný informační systém pro oční lékaře, který má tři hlavní cíle. Prvním cílem je možnost sdílení osobních dat konkrétního pacienta bez nutnosti posílat tato data internetem. Druhým cílem je vytvořit účet pacienta založený na kompletním očním vyšetření. Posledním cílem je aplikovat algoritmus pro registraci intenzitního a barevného fundus obrazu a na jeho základě vytvořit internetově orientovanou tři-dimenzionální vizualizaci optického disku. Tato práce je součásti DAAD spolupráce mezi Ústavem Biomedicínského Inženýrství, Vysokého Učení Technického v Brně, Oční klinikou v Erlangenu a Ústavem Informačních Technologií, Friedrich-Alexander University, Erlangen-Nurnberg.
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