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Classification of the vascular tree in fundus images
Tebenkova, Iuliia ; Kolář, Radim (referee) ; Odstrčilík, Jan (advisor)
Retinal image analysis plays a very important role, as human gets around 90% of environment information with the help of eyes. Automation of process of retinal image analysis promotes to improve the efficiency of retinal medical examinations. The following thesis is dedicated to automatic classification methods of retinal vascular system images obtained from a digital fundus camera. Vessel classification method using classifier on the base of neural networks, which is trained and then tested on the retinal vessel segments, is investigated and implemented. In this thesis anatomical retinal survey, properties of image data from digital fundus camera and retinal image classification methods are briefly described. The last chapter is devoted to the evaluation of efficiency of retinal vessel classification with automatic methods.
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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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Criterial function for retinal image registration
Horáková, Pavla ; Kolář, Radim (referee) ; Harabiš, Vratislav (advisor)
This bachelor‘s thesis is focused on comparison criterial functions, which are usually used in registration of retinal images. Criterial functions reflect degree of images’ sameness thereby they influence proper registration considerably. The aim of this thesis is to discover criterial function, which is the best for image registration of retina. Registration of images is very difficult; it is important to get some informations such as an uniqueness or a shape of function.
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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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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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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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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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Temporal interpolation of ophthalmologic video sequencies using multimodal registration
Kadla, Jan ; Odstrčilík, Jan (referee) ; Jan, Jiří (advisor)
This master’s thesis gives a description of fundus camera as a medical imaging system. Sub features of this system are explained in short, thus examples of certain construction variants are given. Furthermore, the work deals with image fusion and associated possibilities of digital image processing. One set of consecutive scanned images of human eye’s retina has been provided for the practical part of this work. During program processing of these data, decomposition of obtained images to single-color sequences is performed. For these partial monochromatic sequences, monomodal registration is performed, based on calculation of the brightness similarity criterion between the pairs of images. From the three created monochromatic sequences of registered images, new sequence of color images is created, using multimodal registration of each image triples. As a basis for similarity evaluation during multimodal registration, an information similarity criterion was used.
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Analysis of fundus images aimed to localize pathological areas
Hartlová, Marie ; Kolář, Radim (referee) ; Odstrčilík, Jan (advisor)
Diabetic retinopathy is a serious eye complication of diabetes mellitus and one of the major causes of blindness in the world. This thesis deals with detection of neovascularizations, which is the first manifestation of diabetic retinopathy in the retina. In summary, in this thesis describe the properties image data from digital fundus camera, image segmentation methods, methods for automatic blood vessels segmentation and detection of neovaskularizations. This information are used to create own method to detect neovaskularization.
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Texture Analysis of Ophthalmologic Images
Kaňka, Jan ; Odstrčilík, Jan (referee) ; Jan, Jiří (advisor)
This thesis is concerned with creating of software for textural analysis of retinal images by statistic method called co-occurrence matrices as possible alternative method to detection of lesion of retina by the glaucoma diseases. The Glaucoma diseases without well-timed diagnostics and consequential treatment leads to blindness. The retinal images captured by fundus camera are common, easily processable and modern devices are able to make images of 10 Mpix resolution and bigger, what specifies outputs of analytic software. Method of co-occurrence analysis is simple and effective statistic. But computing demandingness, showing up with growing objective quality, comming up as disadvantage.
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