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Analysis of retinal nerve fiber layer in fundus images utilizing local binary patterns
Doležal, Petr ; Harabiš, Vratislav (referee) ; Odstrčilík, Jan (advisor)
This work describes LBP (Local Binary Pattern) method in its various forms as a tool for distinguishing images with and without texture. The first part of the essay looks into the retinal nerve fiber layer, loss of the nerve fiber and especially into possibilities of retinal images with help of the fundus camera and into properties of this way received data. Second part of the essay describes and explains the LBP method which uses local binary operators for description of texture by help of histograms. From this way brought force of histograms is possible to gain a complex of features. Due to different classification approaches can then determine if new samples were selected from an image loss of retinal nerve fiber layer (RNFL). This solves the next part of the essay. And then is evaluated the correlation of features of LBP histograms of these images with the thickness of the RNFL in the same place. The methods described in this essay have been tested on a set of images in Matlab program and received results show, that the method can be useful for the diagnosis of glaucoma diseases.
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Statistical analysis of images from optical coherence tomography with retinal applications
Kelča, Jan ; Slávik, Vladimír (referee) ; Kolář, Radim (advisor)
This work briefly describes the anatomy of the eye and retinal structure, including its pathological changes. The work is focused on the characteristics and the principle of optical coherence tomography and its application in ophthalmology in conjunction with statistical analysis of retinal images. The practical part explains problems of statistical analysis retinal images using histograms representing the distribution of gray shades and approximation of functions, which are stretched exponential function and Nakagami function. Suitable optimalization are obtained parameters, from which are formed parametric maps illustrating the distribution of gray levels in different areas of interest.
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Automatic detection of microaneurysms in fundus images
Klímová, Markéta ; Walek, Petr (referee) ; Kolář, Radim (advisor)
Diabetic retinopathy is a serious complication of diabetes mellitus. It develops as a result of total damage of vessels caused by hyperglycemia and it is one of major causes of blindness. The microaneurysms are the first clinically observed pathologies of diabetic retinopathy. The aim of this bachelor thesis is to propose and to implement an automated microaneurysm detector. Teoretical part describes the eye anatomy, diabetic retinopathy and some existing methods of automated detection. Next the implemented solution is described and the results of the detectin are evaluated.
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Analysis of retinal vessel pulsation
Holásková, Anna ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
The content of this work is the analysis of retinal vessels pulsation of video sequences acquired by experimental fundus camera based on measuring the brightness profile of the vessel. The first level of analysis in this work is the segmentation of blood vessels and diameter measurement of blood vessels during the sequence. The work contains research methods dealing with the diameter measurement and evaluation of pulsation and analysis segmentation methods using for analysing the vasculature of the retina. From these methods, a vessel tracking method was selected. In segmented video sequences is on the ground of intensity profiles analysed vessel pulsation. Analysis is also made on original dataset and results are discussed considering the frequency characteristic.
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Quality assessment of retinal images
Tvarůžek, Marek ; Jiřík, Radovan (referee) ; Kolář, Radim (advisor)
This thesis deals with the properties of retinal images, which are taken with a digital fundus camera. The basic image processing operations are described and applied on biomedical images. Based on these operations, the algorithm for image quality assessment is designed and implemented in Matlab. The quality metrics quantify the focusing. The proposed methods are tested on two datasets and the results are presented and discussed.
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Implementation of Algorithm for Recognition of Eye Retina
Ondroušek, Jan ; Stružka, Jaroslav (referee) ; Hájek, Josef (advisor)
Vessel structure is a very important element in medical sience for diagnosis of eye and cardiovascular diseases. Therefore, its automatic segmentation is very important too. In introduction there is a short description of eye retina. After that, method of implementation is presented according to Ing. Jan Odstrčilík's thesis - Analyze of colour retinal images aimed to segmentation of vessel structures created under the auspices of Brno University of Technology - Faculty of Electrical Engineering and Communication, Department of Biomedical Engineering in 2008. This method is based on filtering input image with properly designed filtering masks, followed by thresholding with properly calculated value and finally cleaning result image from artefacts. Algorithm was written in C++ language. All important functions were implemented for purpose of given method with consideration on speed and accuray. Main sections of source code with description of user interface are introduced next in this thesis. At the end, the implementation was tested on real images from ÚBMI and DRIVE databases, results were recorded, expansions and adjustments possibilities of implementation were debated.
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Application for Recognition of Human Eye Retina
Drozd, Radek ; Hájek, Josef (referee) ; Drahanský, Martin (advisor)
The blood vessels layout in a human eye retina is unique for every person in the world, so it is one of important biometric characteristics. Processing of colour retina image may be a part of an intended biometric system. There is an algorithm for automatic blood vessels detection, optic disc and macula localisation, finding of bifurcation points and saving those as a biometric template presented in this bachelor's thesis. C++ programming language and OpenCV library were used for implementation. The application was tested on a set of colour retina images, taken by fundus camera. The final application is supposed to run on a digital signal processor, developed by Texas Instruments. The thesis gives the introduction into biometrics, signal processing and human eye anatomy.
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Recognition by Retina
Stružka, Jaroslav ; Orság, Filip (referee) ; Fiala, Jiří (advisor)
This thesis deals with recognition by retina (identification, verification). In introduction we describe information about human eye, its diseases with focus on retina impact. Further (in main part) we conduct SW analyses based on biometry retina requirements and design of SW application for retina recognition. It is based on processing pipeline design (sequential application of image filters). This pipeline mostly contains filters focused on edge detection, adaptive threshold and skeletonisation. Finally, basic SW functions includes users registration (enroll), identification, verification. In conclusion we discuss experimental results and success of designed SW in practical application.
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Generation of Cryptographic Key from Eye Biometric Features
Semerád, Lukáš ; Hájek, Josef (referee) ; Drahanský, Martin (advisor)
The main topic of the thesis is creation of formulas for the amount of information entropy in biometric characteristics of iris and retina. This field of science in biometrics named above is unstudied yet, so the thesis tries to initiate research in this direction. The thesis also discusses the historical context of security and identification fields according to biometric characteristics of a human being with an overlap for potential usage in biometrics of iris and retina. The Daugman’s algorithm for converting iris image into the binary code which can be used as a cryptographic key is discussed in detail. An application implementing this conversion is also a part of the thesis.
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Experiments with Images of Eye Retina
Floryček, Jan ; Orság, Filip (referee) ; Fiala, Jiří (advisor)
The layout of blood vessels in human eye retina is one of the important physiological biometric characteristics of every individual. The processing of color retinal images and extraction of the blood vessel structure is an important phase in diagnostics of many eye diseases as well as in gathering biometric data. An automatic method for image processing, extracting the blood vessel structure and saving a template for usage in a biometric system will be described in this bachelor thesis. The method was developed and tested on actual retinal images acquired by digital fundus camera and it was implemented in language C++ with the use of OpenCV library. This thesis also contains a brief introduction to biometrics, computer graphics and medicine.
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