Retinal diseases such as age-related macular degeneration (AMD) are the major cause of blindness in the developed world. Early diagnosis of these diseases is difficult as symptoms appear only at advanced stages. Nevertheless, several studies suggest that impairment of dark adaptation (the ability of the retina to adapt to low lighting) is a cue to AMD. Dark adaptation is the result of the regeneration of light sensitive pigments after having reacted to light (bleaching). This PhD aims at developing a tool for objective measurements of the quantity of photopigment and the kinetics of dark adaptation. This work comprises a thorough review of the absorbing and reflecting properties of the different ocular structures, giving rise to a new model of retinal (or fundus) reflectance. This model provides a detailed description of the different pathways of light through the photoreceptor layer and was able to explain measurements and findings of the literature, in particular the effect of the photoreceptor matrix interstices. An extensive study of the influence of the different model parameters on the total fundus reflectance led to the proposal of a new objective and comparable measure of quantity of photopigment (QoP). This measure is obtained by fitting a constrained version of the new model to a double density difference (DDD) measurement (i.e. the logarithmic difference between reflectances of a retinal area in bleached and dark adapted states). This approach was validated by correctly fitting several DDD measurements from the literature. Future experimental studies are needed to confirm the relevance of the new QoP measure and specify its application in clinical diagnosis. Several fundus reflectometry instruments have been able to measure the DDD in human eyes however because of practical and technological limitations none of these instruments were suitable for clinical use. Here, these limitations are discussed and two new imaging fundus reflectometers are presented. Developed respectively by 4D Optics Ltd. and the Vision Research group at the University of Manchester, these two systems, based on modified fundus cameras, are ongoing development work towards clinically suitable imaging fundus reflectometry. Example data obtained with these two instruments exhibits aberrant points and low signal to noise ratio (SNR). The main issues encountered were camera noise and stability, uneven retinal illumination, and subject’s eye movements and changes of alignment. It is believed that these issues can be overcome with current technologies. One important impediment to the use of the dark adaptation experiment in clinical practice is the time it takes for photopigments to completely regenerate (up to 40 min in normal eyes). A theoretical data analysis strategy using the new model of fundus reflectance and the Marhoo, Lamb and Pugh model of photopigment regeneration kinetics is proposed to rapidly diagnose an abnormal regeneration, hence reducing considerably the duration of the experiment. This idea has not been tested on experimental data but may become relevant once better quality measurements of DDD are obtained.

Segmentation of vasculature tree is an important step of the process of image processing. There are many methods of automatic blood vessel segmentation. These methods are based on matched filters, pattern recognition or image classification. Use of automatic retinal image processing greatly simplifies and accelerates retinal images diagnosis. The aim of the automatic image segmentation algorithms is thresholding. This work primarily deals with retinal image thresholding. We discuss a few works using local and global image thresholding and supervised image classification to segmentation of blood tree from retinal images. Subsequently is to set of results from two different methods used image classification and discuss effectiveness of the vessel segmentation. Use image classification instead of global thresholding changed statistics of first method on healthy part of HRF. Sensitivity and accuracy decreased to 62,32 %, respectively 94,99 %. Specificity increased to 95,75 %. Second method achieved sensitivity 69.24 %, specificity 98.86% and 95.29 % accuracy. Combining the results of both methods achieved sensitivity up to72.48%, specificity to 98.59% and the accuracy to 95.75%. This confirmed the assumption that the classifier will achieve better results. At the same time, was shown that extend the feature vector combining the results from both methods have increased sensitivity, specificity and accuracy.

Retinógrafo é um complexo sistema óptico que, simultaneamente, ilumina e captura imagens da retina. Basicamente, esse equipamento é composto por três módulos: iluminação, lente objetiva e detecção. Em razão de seu sofisticado desenho óptico, é possível conciliar baixa refletividade da retina e obtenção de imagens de alta qualidade. Entretanto, em virtude do alto número de componentes não-coaxiais do módulo de iluminação, seu alinhamento óptico se torna complexo. Neste trabalho, é apresentado um sistema óptico totalmente coaxial para um retinógrafo nãomidriático. A óptica de iluminação tradicional é substituída por um anel de Surface Mounted Device (SMD) Light Emitting Diodes (LEDs) que, analogamente ao equipamento tradicional, forma um anel de luz no plano da pupila do olho, iluminando homogeneamente a retina e evitando reflexos gerados na córnea. Com essa substituição, os três módulos do equipamento se tornam coaxiais, facilitando o alinhamento final. Devido à inovação da arquitetura do retinógrafo, um novo método de eliminação de reflexos também foi introduzido, possibilitando ao equipamento fornecer imagens nítidas e de alta qualidade, suficientes para exames de triagem. Além da iluminação, os módulos da objetiva e de detecção foram substituídos por componentes comerciais, visando a simplificação do projeto de retinógrafo. Dessa forma, pretende-se reduzir o custo de comercialização do produto, de modo que clínicas no Brasil e em países em desenvolvimento possam ser equipadas e capazes de realizar diagnósticos de doenças do olho que causam perda parcial ou total da visão. / Fundus camera is a complex optical system that simultaneously illuminates and images the retina. It is basically divided into three modules: objective lens, illumination and detection. Because of its sophisticate optical design, it is possible to achieve high-quality images under low reflected light by the fundus. However, due to its high number of off-axis components, mainly in the illumination system, the optical alignment of the equipment can be complex. To simplify the architecture of the equipment, we report a completely coaxial optical system, with no off-axis components. The traditional illumination system is replaced by a ring of light emitting diodes of surface mounted device type. As in the previous design, the eye pupil is illuminated with a ring of light, producing a uniform pattern on the retina and avoiding reflection on the cornea. Due to this new design and the lack of optical components in the illumination system, a new method of avoiding reflection on the surfaces of the objective lens is presented. Besides, the objective lens and the detection system were composed of commercial components, also simplifying the equipment project and lowering its cost. The final goal of this work is to provide non-mydriatic high quality fundus images for screening with a low-cost equipment, enabling developing countries to increase the number of people examined.

Retinógrafo é um complexo sistema óptico que, simultaneamente, ilumina e captura imagens da retina. Basicamente, esse equipamento é composto por três módulos: iluminação, lente objetiva e detecção. Em razão de seu sofisticado desenho óptico, é possível conciliar baixa refletividade da retina e obtenção de imagens de alta qualidade. Entretanto, em virtude do alto número de componentes não-coaxiais do módulo de iluminação, seu alinhamento óptico se torna complexo. Neste trabalho, é apresentado um sistema óptico totalmente coaxial para um retinógrafo nãomidriático. A óptica de iluminação tradicional é substituída por um anel de Surface Mounted Device (SMD) Light Emitting Diodes (LEDs) que, analogamente ao equipamento tradicional, forma um anel de luz no plano da pupila do olho, iluminando homogeneamente a retina e evitando reflexos gerados na córnea. Com essa substituição, os três módulos do equipamento se tornam coaxiais, facilitando o alinhamento final. Devido à inovação da arquitetura do retinógrafo, um novo método de eliminação de reflexos também foi introduzido, possibilitando ao equipamento fornecer imagens nítidas e de alta qualidade, suficientes para exames de triagem. Além da iluminação, os módulos da objetiva e de detecção foram substituídos por componentes comerciais, visando a simplificação do projeto de retinógrafo. Dessa forma, pretende-se reduzir o custo de comercialização do produto, de modo que clínicas no Brasil e em países em desenvolvimento possam ser equipadas e capazes de realizar diagnósticos de doenças do olho que causam perda parcial ou total da visão. / Fundus camera is a complex optical system that simultaneously illuminates and images the retina. It is basically divided into three modules: objective lens, illumination and detection. Because of its sophisticate optical design, it is possible to achieve high-quality images under low reflected light by the fundus. However, due to its high number of off-axis components, mainly in the illumination system, the optical alignment of the equipment can be complex. To simplify the architecture of the equipment, we report a completely coaxial optical system, with no off-axis components. The traditional illumination system is replaced by a ring of light emitting diodes of surface mounted device type. As in the previous design, the eye pupil is illuminated with a ring of light, producing a uniform pattern on the retina and avoiding reflection on the cornea. Due to this new design and the lack of optical components in the illumination system, a new method of avoiding reflection on the surfaces of the objective lens is presented. Besides, the objective lens and the detection system were composed of commercial components, also simplifying the equipment project and lowering its cost. The final goal of this work is to provide non-mydriatic high quality fundus images for screening with a low-cost equipment, enabling developing countries to increase the number of people examined.

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.

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.

This master´s thesis deals with blood vessel segmentation in retinal image data. The theoretical part is focused on the basic description of anatomy and physiology of the eye and methods of observing the back of the eye. This thesis also describes the principles of classical and convolutional neural networks and segmentation techniques that are used to segment blood vessel in retinal images. In the practical part, a segmentation method using convolutional neural network U-net is implemented. This neural network is trained on the three datasets. Two datasets include images from experimental video ophthalmoscope. Because it impossible to compare the results of these two datasets with any other methods of retinal blood vessel segmentation, U-net is trained on other dataset that is HRF database. This dataset includes fundus images. The results of testing on this dataset serves for comparing results with other methods of retinal blood vessel segmentation.

This thesis deals with the principle of capturing images of the retina of fundus camera, their features and then preprocessing. The aim of preprocessing is the correction of nonillumination in images of the retina. The model of non-illumination is obtained by using parametric surfaces. Coons surface was selected from a set of surfaces based on the knowledge of retinal images. This has been approximated by a non-uniform illumination. Then the thesis concentrates on describing the methods involving shading corrections. Compensation of non-uniform illumination is based on the use of parametric surface and selected methods for shading correction. The methods presented in the last chapter were tested on simulated and real data. The results were evaluated subjectively.

This thesis deals with method of blood vessels segmentation from retinal images acquired by fundus camera. There is explored possibility of using wavelet transform as fast outline segmentation. The thesis includes study problems of preprocessing input image and decomposition of image using 2D DWT. Furthermore there is explored possibility of parametrical images thresholding that ensue from application of 2D DWT. There are designed algorithms for cleaning off artifacts from rough vessel map of blood vessel structures. The realization of algorithm was solved in programming environment MATLAB. There was created a user control interface in graphic application GUIDE, for easy control of whole segmentation process. In conclusion of thesis is proceeded the discussion of segmentation results for images from DBME database and quantitative evaluation of results for DRIVE database images.

This master thesis deals with detection of blood-vessel bifurcations in retinal images and its properties. There are explained procedure of taking photographs of retina by fundus camera, optical coherence tomography (OCT) and scanning laser opthalmoscope (SLO) and properties of fundus images are described. In this thesis are mentioned some effective thresholding methods and there are explained the most important morphological operations with binary images, as well as with grayscale images. Detected bifurcations are used for image registration with second-order polynomial transformation using corresponding bifurcations.