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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 registration using Optical Flow method
Bistrý, Jan ; Provazník, Ivo (referee) ; Malínský, Miloš (advisor)
Registration of medical images is technique, which is developing with new hybrid diagnostic imaging systems. Nowadays is a trend in image registration focused on monomodality and multimodality images registration. The first part of this master’s thesis is intent on present basic information about image registration. Concretely is intending on image transformation, interpolation, criteria function and at optimalization. Further part present realized Optical Flow technique and used “Demon” algorithm for image registration. The next part is focused on presentation of program solution and GUI. In the last section of this master’s thesis is verifying of created program on usual images and real CT images.
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Multimodal retinal image registration
Štohanzlová, Petra ; CSc, Tomáš Suk, (referee) ; Harabiš, Vratislav (advisor)
This work deals with possibilities of registration of retinal images from different mo-dalities, concretely optical coherence tomography (OCT), scanning laser ophthalmoscopy (SLO) and fundus camera. In first stage is the interest focused on registration of SLO and fundus images, which will serve to determine area of interest for consecutive registration of OCT data. The final stage is finding correct location of OCT B-scans in fundus image. On the basis of the studied methods of registration was chosen method making use of computation of correlation coefficient for both cases. For finding optimal parameters of registration is used searching through whole space of parameters. In partial stages of the work was created algorithm for alignment of B-scans followed by detection of blood vessels and also simple algorithm for detection of blood vessels from fundus image. For more transparent registration the graphical user interface was created, which allows loading input images and displaying the result in several possible forms.
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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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Retinal image registration using phase correlation
Šikula, Viktor ; Harabiš, Vratislav (referee) ; Kolář, Radim (advisor)
This master thesis deals with retinal image registration using phase correlation technique. There are described properties of retinal images and modality of scanning. A geometrical transformation encompasing scale, rotation and translation between two retinal images is considered and the whole registration framework is described. There are used retinal images from fundus camera and scanning laser ophthalmoscope (SLO). In this thesis is described corresponding bifurcations detection using phase correlation and registration using second-order polynomial transformation. The results are subjectively and objectively verificated.
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Head Pose Estimation and Tracking
Pospíšil, Aleš ; Krajsa, Ondřej (referee) ; Přinosil, Jiří (advisor)
Diplomová práce je zaměřena na problematiku detekce a sledování polohy hlavy v obraze jako jednu s možností jak zlepšit možnosti interakce mezi počítačem a člověkem. Hlavním přínosem diplomové práce je využití inovativních hardwarových a softwarových technologií jakými jsou Microsoft Kinect, Point Cloud Library a CImg Library. Na úvod je představeno shrnutí předchozích prací na podobné téma. Následuje charakteristika a popis databáze, která byla vytvořena pro účely diplomové práce. Vyvinutý systém pro detekci a sledování polohy hlavy je založený na akvizici 3D obrazových dat a registračním algoritmu Iterative Closest Point. V závěru diplomové práce je nabídnuto hodnocení vzniklého systému a jsou navrženy možnosti jeho budoucího zlepšení.
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Neuroinformatics: calibration methods in multicentric MR studies
Kovalčík, Tomáš ; Říha, Ivo (referee) ; Provazník, Ivo (advisor)
Work deals with methods of calibration of multi-center study of magnetic resonance imaging. Magnetic resonance is the phenomenon of the substance in a magnetic field of induction B0 delivers energy in the form of RF pulse with the Larmor frequency and thus to excite particles to higher energy levels. Calibration can be performed using the distinctive and homogeneous RF phantoms. Furthermore, we can perform calibration using image registration. To calibrate the images by registering the work described in the classical linear (affine) and nonlinear. Listed below are the simulators, which are also useful for modeling various artifacts.
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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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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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Registration of the autofluorescence images
Říha, František ; Harabiš, Vratislav (referee) ; Kolář, Radim (advisor)
The autofluorescence images of the retina, which are obtained by laser scanning confocal ophthalmoscope Heidelberg Retina Angiograph (HRA), are used for early glaucoma diagnosis. Glaucoma is caused by gradual damage of the optic nerves, which leads to the failing of eyesight and can even cause its complete loss. HRA system is used to obtain a set of retinal images, where every image represents certain segment of retina. This thesis describes image registration methods for retinal image mosaicing. The tested registration methods are based on the global function of similarity or the landmarks detection. As landmarks, the blood vessel bifurcations are considered.
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