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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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Segmentation Methods in Biomedical Image Processing
Mikulka, Jan ; Přibil, Jiří (referee) ; Dostál, Otto (referee) ; Gescheidtová, Eva (advisor)
The PhD thesis deals with modern methods of image processing, especially image segmentation, classification and evaluation of parameters. It is focused primarily on processing medical images of soft tissues obtained by magnetic resonance tomography (MR) and microscopic images of tissues. It is easy to describe edges of the sought objects using of segmented images. The edges found can be useful for further processing of monitored object such as calculating the perimeter, surface and volume evaluation or even three-dimensional shape reconstruction. The proposed solutions can be used for the classification of healthy/unhealthy tissues in MR or other imaging. Application examples of the proposed segmentation methods are shown in this thesis. Research in the area of image segmentation is focused on methods based on solving partial differential equations. This is a modern method for image processing, often called the active contour method. It is of great advantage in the segmentation of real images degraded by noise with fuzzy edges and transitions between objects. The results of the thesis are methods proposed for automatic image segmentation and classification.
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Free algebraic structures and their application for segmentation of a digital image
Čambalová, Kateřina ; Solovjovs, Sergejs (referee) ; Pavlík, Jan (advisor)
The thesis covers methods for image segmentation. Fuzzy segmentation is based on the thresholding method. This is generalized to accept multiple criteria. The whole process is mathematically based on the free algebra theory. Free distributive lattice is created from poset of elements based on image properties and the lattice members are represented by terms used by the threshoding. Possible segmentation results compose the equivalence classes distribution. The thesis also contains description of resulting algorithms and methods for their optimization. Also the method of area subtracting is introduced.
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Mobile robot detection using image processing
Novotný, Stanislav ; Březina, Lukáš (referee) ; Krejsa, Jiří (advisor)
This master´s thesis deals with processing of image sequence taken by statically placed camera over plane of robot movement. At first there are methods for image segmentation and localization methods described. In the next part, selected methods are implemented and compared to individual images. In the final part, selected methods are further implemented in algorithm for batch processing of image sequence.
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Road detection for mobile robot using image processing
Coufal, Jan ; Štarha, Pavel (referee) ; Krejsa, Jiří (advisor)
Diploma thesis deals with image processing for outdoor environment mobile robot. In first part, the problem is analyzed, general solution is proposed and suitable image processing methods are presented. In second part presented methods are tested and methods with best results are proposed. In third part is particular solution tested on real data.
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Analysis of autofluorescence retinal images
Mosyurchak, Andriy ; Odstrčilík, Jan (referee) ; Kolář, Radim (advisor)
Autofluorescence retinal images are obtained with a confocal laser scanning ophthalmoscope, and used for the diagnostic of glaucoma. Glaucoma causes a gradual death of nerve cells and can cause blindness. Retina autofluorescence is caused by pigment lipofuscin, which causes cell damage. The aim of this work was to study methods suitable for segmentation of autofluorescence zones and method for tracking objects in an image. In this project was implemented algorithm of autofluorescence zone detection using method of region growing, designed and realized method for tracking autofluorescence regions.
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Detection of security aids in image signal
Burdík, Vojtěch ; Šmirg, Ondřej (referee) ; Přinosil, Jiří (advisor)
This work is devoted to the relatively new field of computer – computer vision. It focuses on the recognition of people, positioning and colour detection of clothing placed on person. The aim is to build an algorithm that would be able to locate the person in the picture and would make colours tests of clothing and helmets. For image processing were used OpenCV library functions and from algorithms was compiled program solving this problem. The output of the program is the answer, what colour is person at stated locations wearing, and if clothing and helmet are the same colour, the person is evaluated as properly dressed. The resulting program is then disassembled and parts of the code are in detail described in this work. There is explained how to use correctly each OpenCV function used in program.
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Extraction of arteries and veins from fundus image of human retina.
Pinkava, Marek ; Říha, Kamil (referee) ; Minář, Jiří (advisor)
This thesis deals with processing of retinal fundus images. Vision is the most important human sense and its injury has very serious consequences for humans. Automatic processing of retinal images increases the efficiency of medical examination and accelerates diagnoses of deseases. Retina exhibits unique characteristics for each person and thus can also be used to identify people. In this task is briefly discussed the structure and properties of each parts of the eye, particularly the retina, and their possible diseases such as diabetic retinopathy, glaucoma and age related macular degeneration. Subsequently, the task describes the representation and characteristics of the digital image. Also is devoted to selected image segmentation methods namely thresholding, edge detection and segmentation techniques based on the matched filter. The outcome of this task is the application in which several segmentation methods are implemented for the blood vessels extraction. For each of these methods it is possible to set the parameters of the segmentation to ensure high quality blood vessels extraction in images of different quality.
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Optical character recognition from image data
Marinič, Michal ; Uher, Václav (referee) ; Burget, Radim (advisor)
The thesis is concerned with optical character recognition from image data with different methods used for character classification. In the first theoretical part it focuses on explanation of all important parts of system for optical character recognition. The latter practical part of the thesis describes an example of image segmentation, the implementation of artificial neural networks for image recognition and create simple training set of data for the evaluation of the network. It also describes the process of training Tesseract tool and its implementation in a simple application EasyTessOCR for character recognition.
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Segmetation of tomographic data in 3D Slicer
Korčuška, Robert ; Dvořák, Pavel (referee) ; Mikulka, Jan (advisor)
This thesis contains basic theoretical information about SVM-based image segmentation and data classification. Basic information about 3D Slicer software are presented. Aspects of medical images segmentation are described. Workplan and implemetation of SVM method for MRI segmentation in 3D Slicer sofware as extension module is created. SVM method is compared with simple segmentation algorithms included in 3D Slicer. Quality of segmentation, based on SVM, tested on real subjects is experimentaly demonstrated.
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