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Analysis of Ophthalmological Images Aimed to Diagnosis of Glaucoma
Vodáková, Martina ; Kolář, Radim (referee) ; Odstrčilík, Jan (advisor)
Bachelor thesis is focused on fundamental texture analysis of high-resolution fundus images aimed to subjectively and quantitatively describe properties of texture formed by the retinal nerve fiber layer. An area of interest was predefined in the form of ten sectors on each fundus image. The correlation between results of subjective and quantitative evaluation of the texture was monitored in each sector. The results show that proposed fundamental texture features are closely related to the subjective textural properties obtained from visual appearance of the retinal nerve fiber layer. The last step compares results from fundamental texture analysis with quantitative measurement of the retinal nerve fiber layer thickness provided by Optical Coherence Tomography.
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Visualization of 3D data in biomedical applications
Karzel, Michal ; Harabiš, Vratislav (referee) ; Štohanzlová, Petra (advisor)
This thesis describes the basic principle of optical coherence tomography and prepro- cessing of the measured raw data. Preprocessing is focused mainly on noise filtration, removing artifacts, normalization, conversion and compression of raw data. In this way preprocessed data is saved in a *. PFRG file as ”preprocessed fringe data”. Those pre- processed data will be visualised by simply software, which support three methods of visualisation. Volume data represented by voxels. Reconstruction of volume by marching cube algorithm. Cuts through volume along X, Y and Z axis.
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Intra-retinal layer segmentation in optical coherence tomography images
Zlotý, Petr ; Kolář, Radim (referee) ; Gazárek, Jiří (advisor)
This work describes optical coherence tomography, it's principle and methods for automatic segmentation intra-retinal layers in OCT images . There is proposed algorithm for boundary detection of two intra retinal layers, RFNL and RPE layer based on thresholding and second algorithm for detection of seven layers, which is based on graph search algorithm. In summary is compared accuracy against manualy segmented layers and there is also proposed solution for problematic parts.
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Perfusion Modelling in Optical Coherence Tomography
Štohanzlová, Petra ; Penhaker,, Marek (referee) ; Kudrna,, Petr (referee) ; Kolář, Radim (advisor)
This thesis deals mainly with perfusion modeling in optical coherence tomography (OCT). The introductory part deals with basic theory of the OCT, including a description of its basic applications. Part of the work was the testing of selected contrasting materials suitable for the OCT and the design and implementation of phantoms, which were subsequently used in the main part of the thesis. In the practical part, attention is paid to the perfusion analysis in the OCT, first the application of the dilution theory in the OCT for flow estimation, then a study testing the basic theory of perfusion on OCT by means of tissue phantom. Another part of the thesis is devoted to the method of speckle variance analysis for flow visualization.
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Segmentation of choroid blood vessels in 3D images from optical coherence tomography
Maňkoš, Richard ; Kolář, Radim (referee) ; Štohanzlová, Petra (advisor)
This project deals with segmentation of choroid blood vessels in 3D images from optical coherence tomography. The first part is dedicated to theoretical description of the human eye. The second part describes basic information about the optical coherence tomography. In the third part two techniques, which are used on the blood vessels segmentation are described. The last part is practical and deals with an image processing in software OCTSEG and with own created algorithm for blood vessel segmentation.
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Artifact elimination in optical coherence tomography images
Handová, Denisa ; Kolář, Radim (referee) ; Štohanzlová, Petra (advisor)
This work deals with familiarization with optical coherence tomography. It is divided into the several parts. The introductory part of the work describes the principle of this method, the mathematical explanation and characterization of two options for data acquisition - Time-domain OCT and Fourier-domain OCT. Below, the possibilities of using this technique in medicine, in ophthalmology, cardiology and neurology are described. The third part deals with the description of the artifacts and ways of their elimination. The work also includes solution for the reduction of these artifacts in MATLAB and this solution is used in the user application to remove artifact elimination in optical coherence tomography images. At the end, there are the examples of the measured and processed data
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Visualization of 3D data in biomedical applications
Karzel, Michal ; Harabiš, Vratislav (referee) ; Štohanzlová, Petra (advisor)
This thesis describes the basic principle of optical coherence tomography and prepro- cessing of the measured raw data. Preprocessing is focused mainly on noise filtration, removing artifacts, normalization, conversion and compression of raw data. In this way preprocessed data is saved in a *. PFRG file as ”preprocessed fringe data”. Those pre- processed data will be visualised by simply software, which support three methods of visualisation. Volume data represented by voxels. Reconstruction of volume by marching cube algorithm. Cuts through volume along X, Y and Z axis.
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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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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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