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Detection of the nerve fibres in ophthalmologic images
Urbánek, Dušan ; Harabiš, Vratislav (referee) ; Kolář, Radim (advisor)
This thesis deals with detection of the retinal nerve fiber layer in gray level retinal images taken by fundus camera. The first part describes a physiology of human eye and glaucoma disease. Then, the use of wavelet transform and algorithm of texture analysis applied for texture analysis. Next chapters describe theory of texture analysis named „Gray level run length matrices“ and its application for detection of the nerve fiber layer. Applications of this method are described for three types of retinal tissues and for whole image. The last chapter describes gray levels around optic disc and results obtained from parameters from GLRL matrices.
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Analysis of Retinal Image Data to Support Glaucoma Diagnosis
Odstrčilík, Jan ; Kybic, Jan (referee) ; Matula,, Petr (referee) ; Kolář, Radim (advisor)
Fundus kamera je široce dostupné zobrazovací zařízení, které umožňuje relativně rychlé a nenákladné vyšetření zadního segmentu oka – sítnice. Z těchto důvodů se mnoho výzkumných pracovišť zaměřuje právě na vývoj automatických metod diagnostiky nemocí sítnice s využitím fundus fotografií. Tato dizertační práce analyzuje současný stav vědeckého poznání v oblasti diagnostiky glaukomu s využitím fundus kamery a navrhuje novou metodiku hodnocení vrstvy nervových vláken (VNV) na sítnici pomocí texturní analýzy. Spolu s touto metodikou je navržena metoda segmentace cévního řečiště sítnice, jakožto další hodnotný příspěvek k současnému stavu řešené problematiky. Segmentace cévního řečiště rovněž slouží jako nezbytný krok předcházející analýzu VNV. Vedle toho práce publikuje novou volně dostupnou databázi snímků sítnice se zlatými standardy pro účely hodnocení automatických metod segmentace cévního řečiště.
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Specle analysis for optical coherence tomography image segmentation
Gallo, Vladimír ; Kolář, Radim (referee) ; Štohanzlová, Petra (advisor)
This paper presents basic principles of optical coherence tomography, review of applications and basic categorization of these systems. Paper also deals with the typical properties of images from optical coherence tomography, especially speckle pattern. This paper also provides an overview of the origin of speckle noise and utilization of its dependence on microstructure of probed tissue for image classification based on textural analysis. Experimental part of this paper consists of phantom preparation, data acquisition by OCT system, implementation of speckle analysis in MATLAB and of testing of its functionality on standard textural dataset and also on acquired image phantom data. Speckle analysis is used for phantom image data segmentation.
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Texture analysis of retinal images
Mikauš, Jakub ; Odstrčilík, Jan (referee) ; Gazárek, Jiří (advisor)
The thesis deals with the detection of the nerve fiber layer disruptions in retina scans. The introduction presents an overview of the human eye fysiology and analyses the input image data. The thesis continues with an investigation of two texture analysis methods. While the method of adapted filters does not produce very good results, the method of brightness assessment is shown to work satisfactorily. The final part of the thesis describes the implemented tool for the detection of the nerve fiber layer disruptions.
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Analysis of 3D CT image data aimed at detection and classification of specific tissue structures
Šalplachta, Jakub ; Malínský, Miloš (referee) ; Jan, Jiří (advisor)
This thesis deals with the segmentation and classification of paraspinal muscle and subcutaneous adipose tissue in 3D CT image data in order to use them subsequently as internal calibration phantoms to measure bone mineral density of a vertebrae. Chosen methods were tested and afterwards evaluated in terms of correctness of the classification and total functionality for subsequent BMD value calculation. Algorithms were tested in programming environment Matlab® on created patient database which contains lumbar spines of twelve patients. Following sections of this thesis contain theoretical research of the issue of measuring bone mineral density, segmentation and classification methods and description of practical part of this work.
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Creation of Database and Classification of Diatoms
Svoboda, Jan ; Nötzel, Ralf (referee) ; Drahanský, Martin (advisor)
Výsledná aplikace pracuje s vytvořenou databází, obsahující obrázky jednotlivých rozsivek a informace o nich uložené v XML dokumentu. Nad touto databází jsou zajištěny základní operace přidávání, úpravy, mazání a vyhledávání. Vyhledávání může probíhat třemi způsoby, a to pomocí textových vstupů, obrázkových vstupů nebo jejich kombinací. Algoritmus vyhledávání pomocí obrázkových vstupů se snaží najít v databázi co nejpodobnější kandidáty s ohledem na tvar a tloušťku schránky rozsivky a na vnitřní strukturu rozsivky jako takové. Toto vyhledávání je nejčastěji znepřesněno kvalitou pořízených snímků, či obrázků porovnávaných rozsivek. Program obsahuje přehledné a intuitivní grafické rozhraní, jež nám pohodlně umožňuje prohlížet stávající databázi a provádět operace nad ní s možností nastavení filtrovacích hodnot při vyhledávání.
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Intelligent features classification aimed to support diagnosis of glaucoma
Vykoupil, Pavel ; Čmiel, Vratislav (referee) ; Odstrčilík, Jan (advisor)
This bachelor thesis deals with inteligent features classification aimed to support diagnosis of glaucoma. First part focuses on eye anatomy and disease called glaucoma. In next part is briefly described texture analysis and how do we get attributes for classification. In last part it is dealt with attribute classification with the aid of neural networks and algorithm HoKashyap and AdaBoost. This thesis is therefore focused on comparing effectivity of these classifiers on the field of optical diagnostics which was managed successfully.
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Texture analysis of retinal images oriented towards detection of neronal fibre layer
Gazárek, Jiří ; Jiřík, Radovan (referee) ; Jan, Jiří (advisor)
The thesis is focused on detection of local disappearance of the neural layer on retina in fundus-camera images. The first chapter describes the human eye physiology, the glaucoma disease and the analyzed data. The second chapter compares four different approaches that should enable automatic detection of a possible damage to the retinal neural layer. These four approaches have been tested and evaluated; three of them showed an acceptable correlation with the medical expert conclusions – the directional spectral approach, the edge based approach and the difference local brightness. The last approch via local co-occurrence matrices has not turned out to be informative with the respect to the issue concerned. Then a program for the automatic detection of the nerve fibre layer loss areas has been designed, realized and evaluated. This task is solved in the last chapter. A relatively good agreement between the medical expert conclusions and the conclusions detected automatically by this program has been reached.
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Image analysis of object surface texture
Klimeš, Jiří ; Horák, Karel (referee) ; Petyovský, Petr (advisor)
This master thesis deals with design and implementation of algorithms for image analysis of object surface texture for the purpose of automating the surface grinding process. In the first part of this thesis, a search was performed in the field of image analysis of object surface texture. The proposed descriptors were tested on the created annotated database of texture images. Subsequently, a scene for image acquisition of the machined object was designed and assembled, and the grinding process was automated based on the results of the previous analysis. The implementation and achieved results were evaluated and other possible improvements were proposed.
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Extraction of texture features aimed to detect glaucoma defects
Daněk, Daniel ; Kolář, Radim (referee) ; Odstrčilík, Jan (advisor)
The thesis deals with an automatic method of texture analysis using Markov random fields texture modeling. The main aim of this work is to find out relevant textural features, which can be used for appropriate classification of the degree of retinal nerve fiber layer loss. The model of Markovian statistic uses a circular symmetric neighborhood structure and a least square error estimation of the model's parameter. Obtained textural features were quantitatively evaluated using correlation analysis. The results show, that there is a significant correlation between proposed textural features and RNFL thickness measured by OCT. Thus, the features can potentially serve for glaucoma diagnosis.
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