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Gonzalez, Ana Guadalupe Salazar. "Structure analysis and lesion detection from retinal fundus images." Thesis, Brunel University, 2011. http://bura.brunel.ac.uk/handle/2438/6456.
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Ocular pathology is one of the main health problems worldwide. The number of people with retinopathy symptoms has increased considerably in recent years. Early adequate treatment has demonstrated to be effective to avoid the loss of the vision. The analysis of fundus images is a non intrusive option for periodical retinal screening. Different models designed for the analysis of retinal images are based on supervised methods, which require of hand labelled images and processing time as part of the training stage. On the other hand most of the methods have been designed under the basis of specific characteristics of the retinal images (e.g. field of view, resolution). This compromises its performance to a reduce group of retinal image with similar features. For these reasons an unsupervised model for the analysis of retinal image is required, a model that can work without human supervision or interaction. And that is able to perform on retinal images with different characteristics. In this research, we have worked on the development of this type of model. The system locates the eye structures (e.g. optic disc and blood vessels) as first step. Later, these structures are masked out from the retinal image in order to create a clear field to perform the lesion detection. We have selected the Graph Cut technique as a base to design the retinal structures segmentation methods. This selection allows incorporating prior knowledge to constraint the searching for the optimal segmentation. Different link weight assignments were formulated in order to attend the specific needs of the retinal structures (e.g. shape). This research project has put to work together the fields of image processing and ophthalmology to create a novel system that contribute significantly to the state of the art in medical image analysis. This new knowledge provides a new alternative to address the analysis of medical images and opens a new panorama for researchers exploring this research area.
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Colomer, Granero Adrián. "Fundus image analysis for automatic screening of ophthalmic pathologies." Doctoral thesis, Universitat Politècnica de València, 2018. http://hdl.handle.net/10251/99745.
Full textAbstract:
En los ultimos años el número de casos de ceguera se ha reducido significativamente. A pesar de este hecho, la Organización Mundial de la Salud estima que un 80% de los casos de pérdida de visión (285 millones en 2010) pueden ser evitados si se diagnostican en sus estadios más tempranos y son tratados de forma efectiva. Para cumplir esta propuesta se pretende que los servicios de atención primaria incluyan un seguimiento oftalmológico de sus pacientes así como fomentar campañas de cribado en centros proclives a reunir personas de alto riesgo. Sin embargo, estas soluciones exigen una alta carga de trabajo de personal experto entrenado en el análisis de los patrones anómalos propios de cada enfermedad. Por lo tanto, el desarrollo de algoritmos para la creación de sistemas de cribado automáticos juga un papel vital en este campo. La presente tesis persigue la identificacion automática del daño retiniano provocado por dos de las patologías más comunes en la sociedad actual: la retinopatía diabética (RD) y la degenaración macular asociada a la edad (DMAE). Concretamente, el objetivo final de este trabajo es el desarrollo de métodos novedosos basados en la extracción de características de la imagen de fondo de ojo y clasificación para discernir entre tejido sano y patológico. Además, en este documento se proponen algoritmos de pre-procesado con el objetivo de normalizar la alta variabilidad existente en las bases de datos publicas de imagen de fondo de ojo y eliminar la contribución de ciertas estructuras retinianas que afectan negativamente en la detección del daño retiniano. A diferencia de la mayoría de los trabajos existentes en el estado del arte sobre detección de patologías en imagen de fondo de ojo, los métodos propuestos a lo largo de este manuscrito evitan la necesidad de segmentación de las lesiones o la generación de un mapa de candidatos antes de la fase de clasificación. En este trabajo, Local binary patterns, perfiles granulométricos y la dimensión fractal se aplican de manera local para extraer información de textura, morfología y tortuosidad de la imagen de fondo de ojo. Posteriormente, esta información se combina de diversos modos formando vectores de características con los que se entrenan avanzados métodos de clasificación formulados para discriminar de manera óptima entre exudados, microaneurismas, hemorragias y tejido sano. Mediante diversos experimentos, se valida la habilidad del sistema propuesto para identificar los signos más comunes de la RD y DMAE. Para ello se emplean bases de datos públicas con un alto grado de variabilidad sin exlcuir ninguna imagen. Además, la presente tesis también cubre aspectos básicos del paradigma de deep learning. Concretamente, se presenta un novedoso método basado en redes neuronales convolucionales (CNNs). La técnica de transferencia de conocimiento se aplica mediante el fine-tuning de las arquitecturas de CNNs más importantes en el estado del arte. La detección y localización de exudados mediante redes neuronales se lleva a cabo en los dos últimos experimentos de esta tesis doctoral. Cabe destacar que los resultados obtenidos mediante la extracción de características "manual" y posterior clasificación se comparan de forma objetiva con las predicciones obtenidas por el mejor modelo basado en CNNs. Los prometedores resultados obtenidos en esta tesis y el bajo coste y portabilidad de las cámaras de adquisión de imagen de retina podrían facilitar la incorporación de los algoritmos desarrollados en este trabajo en un sistema de cribado automático que ayude a los especialistas en la detección de patrones anomálos característicos de las dos enfermedades bajo estudio: RD y DMAE.In last years, the number of blindness cases has been significantly reduced. Despite this promising news, the World Health Organisation estimates that 80% of visual impairment (285 million cases in 2010) could be avoided if diagnosed and treated early. To accomplish this purpose, eye care services need to be established in primary health and screening campaigns should be a common task in centres with people at risk. However, these solutions entail a high workload for trained experts in the analysis of the anomalous patterns of each eye disease. Therefore, the development of algorithms for automatic screening system plays a vital role in this field. This thesis focuses on the automatic identification of the retinal damage provoked by two of the most common pathologies in the current society: diabetic retinopathy (DR) and age-related macular degeneration (AMD). Specifically, the final goal of this work is to develop novel methods, based on fundus image description and classification, to characterise the healthy and abnormal tissue in the retina background. In addition, pre-processing algorithms are proposed with the aim of normalising the high variability of fundus images and removing the contribution of some retinal structures that could hinder in the retinal damage detection. In contrast to the most of the state-of-the-art works in damage detection using fundus images, the methods proposed throughout this manuscript avoid the necessity of lesion segmentation or the candidate map generation before the classification stage. Local binary patterns, granulometric profiles and fractal dimension are locally computed to extract texture, morphological and roughness information from retinal images. Different combinations of this information feed advanced classification algorithms formulated to optimally discriminate exudates, microaneurysms, haemorrhages and healthy tissues. Through several experiments, the ability of the proposed system to identify DR and AMD signs is validated using different public databases with a large degree of variability and without image exclusion. Moreover, this thesis covers the basics of the deep learning paradigm. In particular, a novel approach based on convolutional neural networks is explored. The transfer learning technique is applied to fine-tune the most important state-of-the-art CNN architectures. Exudate detection and localisation tasks using neural networks are carried out in the last two experiments of this thesis. An objective comparison between the hand-crafted feature extraction and classification process and the prediction models based on CNNs is established. The promising results of this PhD thesis and the affordable cost and portability of retinal cameras could facilitate the further incorporation of the developed algorithms in a computer-aided diagnosis (CAD) system to help specialists in the accurate detection of anomalous patterns characteristic of the two diseases under study: DR and AMD.
En els últims anys el nombre de casos de ceguera s'ha reduït significativament. A pesar d'este fet, l'Organització Mundial de la Salut estima que un 80% dels casos de pèrdua de visió (285 milions en 2010) poden ser evitats si es diagnostiquen en els seus estadis més primerencs i són tractats de forma efectiva. Per a complir esta proposta es pretén que els servicis d'atenció primària incloguen un seguiment oftalmològic dels seus pacients així com fomentar campanyes de garbellament en centres regentats per persones d'alt risc. No obstant això, estes solucions exigixen una alta càrrega de treball de personal expert entrenat en l'anàlisi dels patrons anòmals propis de cada malaltia. Per tant, el desenrotllament d'algoritmes per a la creació de sistemes de garbellament automàtics juga un paper vital en este camp. La present tesi perseguix la identificació automàtica del dany retiniano provocat per dos de les patologies més comunes en la societat actual: la retinopatia diabètica (RD) i la degenaración macular associada a l'edat (DMAE) . Concretament, l'objectiu final d'este treball és el desenrotllament de mètodes novedodos basats en l'extracció de característiques de la imatge de fons d'ull i classificació per a discernir entre teixit sa i patològic. A més, en este document es proposen algoritmes de pre- processat amb l'objectiu de normalitzar l'alta variabilitat existent en les bases de dades publiques d'imatge de fons d'ull i eliminar la contribució de certes estructures retinianas que afecten negativament en la detecció del dany retiniano. A diferència de la majoria dels treballs existents en l'estat de l'art sobre detecció de patologies en imatge de fons d'ull, els mètodes proposats al llarg d'este manuscrit eviten la necessitat de segmentació de les lesions o la generació d'un mapa de candidats abans de la fase de classificació. En este treball, Local binary patterns, perfils granulometrics i la dimensió fractal s'apliquen de manera local per a extraure informació de textura, morfologia i tortuositat de la imatge de fons d'ull. Posteriorment, esta informació es combina de diversos modes formant vectors de característiques amb els que s'entrenen avançats mètodes de classificació formulats per a discriminar de manera òptima entre exsudats, microaneurismes, hemorràgies i teixit sa. Per mitjà de diversos experiments, es valida l'habilitat del sistema proposat per a identificar els signes més comuns de la RD i DMAE. Per a això s'empren bases de dades públiques amb un alt grau de variabilitat sense exlcuir cap imatge. A més, la present tesi també cobrix aspectes bàsics del paradigma de deep learning. Concretament, es presenta un nou mètode basat en xarxes neuronals convolucionales (CNNs) . La tècnica de transferencia de coneixement s'aplica per mitjà del fine-tuning de les arquitectures de CNNs més importants en l'estat de l'art. La detecció i localització d'exudats per mitjà de xarxes neuronals es du a terme en els dos últims experiments d'esta tesi doctoral. Cal destacar que els resultats obtinguts per mitjà de l'extracció de característiques "manual" i posterior classificació es comparen de forma objectiva amb les prediccions obtingudes pel millor model basat en CNNs. Els prometedors resultats obtinguts en esta tesi i el baix cost i portabilitat de les cambres d'adquisión d'imatge de retina podrien facilitar la incorporació dels algoritmes desenrotllats en este treball en un sistema de garbellament automàtic que ajude als especialistes en la detecció de patrons anomálos característics de les dos malalties baix estudi: RD i DMAE.
Colomer Granero, A. (2018). Fundus image analysis for automatic screening of ophthalmic pathologies [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/99745
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Běťák, Ondřej. "Multimodální registrace retinálních snímků z fundus kamery a OCT." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-219716.
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V první části se práce se zabývá rešerší metod a principů potřebných při registraci obrazu. Dále pak popisuje zobrazovací systémy očního pozadí jako jsou OCT, fundus kamera a SLO. Druhá část práce je zaměřena na praktickou realizaci programů pro registraci snímků z OCT, SLO a fundus kamery v programovém prostředí Matlab.
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Morales, Martínez Sandra. "Fundus characterization for automatic disease screening through retinal image processing." Doctoral thesis, Editorial Universitat Politècnica de València, 2015. http://hdl.handle.net/10251/53933.
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[EN] The World Health Organization estimates that in 2010 there were 285 million people visually impaired in the world. It is calculated that the 80\% of these cases are preventable or treatable. In addition, aging population and chronic disease increase are two factors that predict a higher number of blindness cases in the future. Hypertension, diabetic retinopathy (DR), age-related macular degeneration (AMD) and glaucoma are the most common pathologies in the current society that provoke retinal damage and can be directly related to blindness and vision loss. The early diagnosis of these diseases allows, through appropriate treatment, to reduce costs generated when they are in advanced states and may become chronic. This fact justifies screening campaigns. However, a screening campaign requires a heavy workload for trained experts in the analysis of anomalous patterns of each disease, which in addition to the increase of population at risk, makes these campaigns economically unfeasible. Therefore, the need of automatic screening system developments is highlighted.
The final goal of this thesis is the implementation of novel methods that allow the analysis and processing of fundus images to implement an automatic screening of four of the most important diseases that affect world population. In particular, the main objective of the thesis is to build up algorithms for the characterization of the retinal structures and the retina background in order to assist in the discrimination between a ``normal" and pathological retina.
Mathematical morphology along with other operators are used for the detection of the retinal vessels and the optic disk. The proposed methods work properly on databases with a large degree of variability. Not only have the main structures been segmented, but significant features have also been extracted from them to be used in a computer aided diagnosis software for hypertensive risk determination. The texture of the retina background is also analyzed in this work by means of local binary patterns with the aim of identifying DR and AMD and avoiding the need of segmentation of the characteristic retinal lesions of each disease. The results are promising above all for AMD diagnosis.[ES] La Organización Mundial de la Salud estima que en 2010 había 285 millones de personas con alguna discapacidad visual en el mundo. Se calcula que el 80\% de estos casos son evitables o tratables. Además, el envejecimiento de la población y el aumento de las enfermedades crónicas son dos factores que hacen prever un número todavía mayor de casos de ceguera en el futuro. La hipertensión, la retinopatía diabética (RD), la degeneración macular asociada a la edad (DMAE) y el glaucoma son las enfermedades más comunes que provocan daños en la retina y, por tanto, están directamente relacionadas con la ceguera y con la pérdida de visión. El diagnóstico de estas enfermedades en estadios tempranos permite, mediante el tratamiento adecuado, reducir los costes que generan en estados ya avanzados y que en la mayoría de los casos acaban convirtiéndose en crónicas, lo que justifica la realización de campañas de cribado. Sin embargo, una campaña de cribado exige una gran carga de trabajo de personal experto entrenado en el análisis de los patrones anómalos propios de cada enfermedad, lo que sumado al aumento de la población de riesgo, hace que estas campañas sean inviables económicamente. Por lo tanto, se evidencia la necesidad del desarrollo de sistemas de cribado automáticos. El objetivo final del presente trabajo es la implementación de métodos novedosos de análisis de imágenes de fondo de ojo para usarlos en un sistema de cribado de cuatro de las enfermedades más importantes que afectan a la población actual. En concreto, el objetivo principal de la tesis es el desarrollo de algoritmos para la caracterización de las estructuras y del fondo retiniano, los cuales servirán de ayuda para discriminar una retina ``normal" de otra patológica. Para la detección de los vasos retinianos y del disco óptico, se ha usado morfología matemática además de otros operadores. Se ha demostrado que los métodos propuestos para este fin funcionan adecuadamente en bases de datos con un alto grado de variabilidad. No sólo se han segmentado las principales estructuras retinianas, sino que, además, se han extraído sus características más significativas para determinar el riesgo hipertensivo. En este trabajo, también se han analizado las texturas presentes en el fondo de la retina por medio de la teoría de los patrones binarios locales con el objetivo de identificar la RD y la DMAE a la vez que se evita la necesidad de la segmentación de las lesiones específicas de cada enfermedad. Los resultados son prometedores, sobre todo, para la detección de la DMAE.
[CAT] L'Organització Mundial de la Salut estima que en 2010 havia 285 milions de persones amb alguna discapacitat visual en el món. Es calcula que el 80\% d'aquests casos són evitables o tractables. A més, l'envelliment de la població i l'augment de les malalties cròniques són dos factors que fan preveure un número encara major de casos de ceguera en el futur. La hipertensió, la retinopatia diabètica (RD), la degeneració macular associada a l'edat (DMAE) i el glaucoma són les malalties més comuns que provoquen danys en la retina i, per tant, estan directament relacionades amb la ceguera i amb la pèrdua de visió. El diagnòstic d'aquestes malalties en estadis primerencs permet, per mitjà del tractament adequat, reduir els costos que generen en estats ja avançats i que en la majoria dels casos acaben convertint-se en cròniques, la qual cosa justifica la realització de campanyes de garbellament. No obstant això, una campanya de garbellament exigix una gran càrrega de treball de personal expert entrenat en l'anàlisi dels patrons anòmals propis de cada malaltia, que si es suma a l'augment de la població de risc, fa que aquestes campanyes siguen inviables econòmicament. Per tant, s'evidencia la necessitat del desenrotllament de sistemes de garbellament automàtics. L'objectiu final del present treball és la implementació de mètodes nous d'anàlisi d'imatges de fons d'ull per a usar-los en un sistema de garbellament de quatre de les malalties més importants que afecten la població actual. En concret, l'objectiu principal de la tesi és el desenvolupament d'algoritmes per a la caracterització de les estructures i del fons retinià, els quals serviran d'ajuda per a discriminar una retina ``normal" d'una altra patològica. Per a la detecció dels vasos retinians i del disc òptic, s'ha usat morfologia matemàtica a més d'altres operadors. S'ha demostrat que els mètodes proposats per a aquest fi funcionen adequadament en bases de dades amb un alt grau de variabilitat. No sols s'han segmentat les principals estructures retinianes, sinó que, a més, s'han extret les seues característiques més significatives per a determinar el risc hipertensiu. En aquest treball, també s'han analitzat les textures presents en el fons de la retina per mitjà de la teoria dels patrons binaris locals amb l'objectiu d'identificar la RD i la DMAE al mateix temps que s'evita la necessitat de la segmentació de les lesions específiques de cada malaltia. Els resultats són prometedors, sobretot, per a la detecció de la DMAE.
Morales Martínez, S. (2015). Fundus characterization for automatic disease screening through retinal image processing [Tesis doctoral]. Editorial Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/53933
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Svoboda, Ondřej. "Pokročilé metody segmentace cévního řečiště na fotografiích sítnice." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220290.
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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.
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Xu, Xiayu. "Automated delineation and quantitative analysis of blood vessels in retinal fundus image." Diss., University of Iowa, 2012. https://ir.uiowa.edu/etd/3017.
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Automated fundus image analysis plays an important role in the computer aided diagnosis of ophthalmologic disorders. A lot of eye disorders, as well as cardiovascular disorders, are known to be related with retinal vasculature changes. Many studies has been done to explore these relationships. However, most of the studies are based on limited data obtained using manual or semi-automated methods due to the lack of automated techniques in the measurement and analysis of retinal vasculature. In this thesis, a fully automated retinal vessel width measurement technique is proposed. This novel method models the accurate vessel boundary delineation problem in two-dimension into an optimal surface segmentation problem in threedimension. Then the optimal surface segmentation problem is transformed into finding a minimum-cost closed set problem in a vertex-weighted geometric graph. The problem is modeled differently for straight vessel and for branch point because of the different conditions in straight vessel and in branch point. Furthermore, many of the retinal image analysis needs the location of the optic disc and fovea as a prerequisite information, for example, in the analysis of the relationship between vessel width and the distance to the optic disc. Hence, a simultaneous optic disc and fovea detection method is presented, which includes a two-step classification of three classes. The major contributions of this thesis include: 1) developing a fully automated vessel width measurement technique for retinal blood vessels, 2) developing a simultaneous optic disc and fovea detection method, 3) validating the methods using multiple datasets, and 4) applying the proposed methods in multiple retinal vasculature analysis studies.
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Pinkava, Marek. "Extrakce krevního řečiště z Fundus snímku lidského oka." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220635.
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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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Díaz, Pinto Andrés Yesid. "Machine Learning for Glaucoma Assessment using Fundus Images." Doctoral thesis, Universitat Politècnica de València, 2019. http://hdl.handle.net/10251/124351.
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[ES] Las imágenes de fondo de ojo son muy utilizadas por los oftalmólogos para la evaluación de la retina y la detección de glaucoma. Esta patología es la segunda causa de ceguera en el mundo, según estudios de la Organización Mundial de la Salud (OMS).
En esta tesis doctoral, se estudian algoritmos de aprendizaje automático (machine learning) para la evaluación automática del glaucoma usando imágenes de fondo de ojo. En primer lugar, se proponen dos métodos para la segmentación automática. El primer método utiliza la transformación Watershed Estocástica para segmentar la copa óptica y posteriormente medir características clínicas como la relación Copa/Disco y la regla ISNT. El segundo método es una arquitectura U-Net que se usa específicamente para la segmentación del disco óptico y la copa óptica.
A continuación, se presentan sistemas automáticos de evaluación del glaucoma basados en redes neuronales convolucionales (CNN por sus siglas en inglés). En este enfoque se utilizan diferentes modelos entrenados en ImageNet como clasificadores automáticos de glaucoma, usando fine-tuning. Esta nueva técnica permite detectar el glaucoma sin segmentación previa o extracción de características. Además, este enfoque presenta una mejora considerable del rendimiento comparado con otros trabajos del estado del arte.
En tercer lugar, dada la dificultad de obtener grandes cantidades de imágenes etiquetadas (glaucoma/no glaucoma), esta tesis también aborda el problema de la síntesis de imágenes de la retina. En concreto se analizaron dos arquitecturas diferentes para la síntesis de imágenes, las arquitecturas Variational Autoencoder (VAE) y la Generative Adversarial Networks (GAN). Con estas arquitecturas se generaron imágenes sintéticas que se analizaron cualitativa y cuantitativamente, obteniendo un rendimiento similar a otros trabajos en la literatura.
Finalmente, en esta tesis se plantea la utilización de un tipo de GAN (DCGAN) como alternativa a los sistemas automáticos de evaluación del glaucoma presentados anteriormente. Para alcanzar este objetivo se implementó un algoritmo de aprendizaje semi-supervisado.[CAT] Les imatges de fons d'ull són molt utilitzades pels oftalmòlegs per a l'avaluació de la retina i la detecció de glaucoma. Aquesta patologia és la segona causa de ceguesa al món, segons estudis de l'Organització Mundial de la Salut (OMS). En aquesta tesi doctoral, s'estudien algoritmes d'aprenentatge automàtic (machine learning) per a l'avaluació automàtica del glaucoma usant imatges de fons d'ull. En primer lloc, es proposen dos mètodes per a la segmentació automàtica. El primer mètode utilitza la transformació Watershed Estocàstica per segmentar la copa òptica i després mesurar característiques clíniques com la relació Copa / Disc i la regla ISNT. El segon mètode és una arquitectura U-Net que s'usa específicament per a la segmentació del disc òptic i la copa òptica. A continuació, es presenten sistemes automàtics d'avaluació del glaucoma basats en xarxes neuronals convolucionals (CNN per les sigles en anglès). En aquest enfocament s'utilitzen diferents models entrenats en ImageNet com classificadors automàtics de glaucoma, usant fine-tuning. Aquesta nova tècnica permet detectar el glaucoma sense segmentació prèvia o extracció de característiques. A més, aquest enfocament presenta una millora considerable del rendiment comparat amb altres treballs de l'estat de l'art. En tercer lloc, donada la dificultat d'obtenir grans quantitats d'imatges etiquetades (glaucoma / no glaucoma), aquesta tesi també aborda el problema de la síntesi d'imatges de la retina. En concret es van analitzar dues arquitectures diferents per a la síntesi d'imatges, les arquitectures Variational Autoencoder (VAE) i la Generative adversarial Networks (GAN). Amb aquestes arquitectures es van generar imatges sintètiques que es van analitzar qualitativament i quantitativament, obtenint un rendiment similar a altres treballs a la literatura. Finalment, en aquesta tesi es planteja la utilització d'un tipus de GAN (DCGAN) com a alternativa als sistemes automàtics d'avaluació del glaucoma presentats anteriorment. Per assolir aquest objectiu es va implementar un algoritme d'aprenentatge semi-supervisat.
[EN] Fundus images are widely used by ophthalmologists to assess the retina and detect glaucoma, which is, according to studies from the World Health Organization (WHO), the second cause of blindness worldwide. In this thesis, machine learning algorithms for automatic glaucoma assessment using fundus images are studied. First, two methods for automatic segmentation are proposed. The first method uses the Stochastic Watershed transformation to segment the optic cup and measures clinical features such as the Cup/Disc ratio and ISNT rule. The second method is a U-Net architecture focused on the optic disc and optic cup segmentation task. Secondly, automated glaucoma assessment systems using convolutional neural networks (CNNs) are presented. In this approach, different ImageNet-trained models are fine-tuned and used as automatic glaucoma classifiers. These new techniques allow detecting glaucoma without previous segmentation or feature extraction. Moreover, it improves the performance of other state-of-art works. Thirdly, given the difficulty of getting large amounts of glaucoma-labelled images, this thesis addresses the problem of retinal image synthesis. Two different architectures for image synthesis, the Variational Autoencoder (VAE) and Generative Adversarial Networks (GAN) architectures, were analysed. Using these models, synthetic images that were qualitative and quantitative analysed, reporting state-of-the-art performance, were generated. Finally, an adversarial model is used to create an alternative automatic glaucoma assessment system. In this part, a semi-supervised learning algorithm was implemented to reach this goal.
The research derived from this doctoral thesis has been supported by the Generalitat Valenciana under the scholarship Santiago Grisolía [GRISOLIA/2015/027].
Díaz Pinto, AY. (2019). Machine Learning for Glaucoma Assessment using Fundus Images [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/124351
TESIS
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Hu, Qiao. "Automatic construction of arterial and venous vascular trees in fundus images." Diss., University of Iowa, 2016. https://ir.uiowa.edu/etd/3107.
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The retinal vasculature analysis plays an important role in the diagnosis of ophthalmological diseases, as well as general human disorders that manifest on the retina. The fundus photograph is a 2-D color image modality of the retina and is widely used in modern ophthalmology clinics due to its relatively low cost and its non-invasive access to the retina. However, due to the complexity of the retinal vasculature presented on the image and the large variation of the image quality, no automated method is able to re-construct the retinal vasculature (i.e. construct arteriovenous trees) satisfactorily, thus preventing its analysis on large-scale clinical datasets.
In this thesis, we present a systematic and complete study to automatically construct the retinal vasculature on fundus photographs and apply it to a clinical dataset. First of all, a preliminary study is conducted to detect and classify important landmarks in the retinal vasculature using a machine learning method. The evaluation of this method reveals the difficulty of identifying each landmark as an independent target. Then a novel and more global method is proposed to construct retinal arteriovenous trees (A/V trees). The strategy of the proposed method is to build an over-connected vessel network, and separate it into vascular trees, then classify them into A/V trees. Particularly, by taking advantages of specific properties of the retinal vasculature, global and local information are combined together to recognize landmarks of the vasculature. Instead of recognizing each landmark independently as other methods do, this method considers the relationship between landmarks in a more global manner, thus recognizing them simultaneously and globally. With a special graph design, each landmark is associated with multiple possible configurations and costs, and a near optimal solution is selected by minimizing the costs of landmarks and the global property of the whole vascular network. With each landmark recognized, the A/V trees are easily inferred with a pixel classification method. By doing so, local noise in the images and local errors during pre-processing are corrected to some degree, and small vessels that are difficult to classify locally can also be recognized. The proposed method is compared with another method and the evaluation demonstrates its superiority.
To demonstrate its potential applicability, we apply the proposed method on a cohort study data of HIV-infected patients with treatment. New metrics to analyze retinal vessel width is developed based on the A/V trees built using the proposed method, and it is compared with a conventional metric. Statistical analysis reveals the advantages of the new metric and thus indicates the benefit of the proposed method and its potential application on large datasets.
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Klimeš, Filip. "Zpracování obrazových sekvencí sítnice z fundus kamery." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-220975.
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Cílem mé diplomové práce bylo navrhnout metodu analýzy retinálních sekvencí, která bude hodnotit kvalitu jednotlivých snímků. V teoretické části se také zabývám vlastnostmi retinálních sekvencí a způsobem registrace snímků z fundus kamery. V praktické části je implementována metoda hodnocení kvality snímků, která je otestována na reálných retinálních sekvencích a vyhodnocena její úspěšnost. Práce hodnotí i vliv této metody na registraci retinálních snímků.
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Van, der Westhuizen Christo Carel. "Efficient registration of limited field of view ocular fundus imagery." Thesis, Stellenbosch : Stellenbosch University, 2013. http://hdl.handle.net/10019.1/85633.
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Thesis (MScEng)-- Stellenbosch University, 2013.ENGLISH ABSTRACT: Diabetic- and hypertensive retinopathy are two common causes of blindness that can be prevented by managing the underlying conditions. Patients suffering from these conditions are encouraged to undergo regular examinations to monitor the retina for signs of deterioration. For these routine examinations an ophthalmoscope is used. An ophthalmoscope is a relatively inexpensive device that allows an examiner to directly observe the ocular fundus (the interior back wall of the eye that contains the retina). These devices are analog and do not allow the capture of digital imagery. Fundus cameras, on the other hand, are larger devices that o er high quality digital images. They do, however, come at an increased cost and are not practical for use in the eld. In this thesis the design and implementation of a system that digitises imagery from an ophthalmoscope is discussed. The main focus is the development of software algorithms to increase the quality of the images to yield results of a quality closer to that of a fundus camera. The aim is not to match the capabilities of a fundus camera, but rather to o er a cost-e ective alternative that delivers su cient quality for use in conducting routine monitoring of the aforementioned conditions. For the digitisation the camera of a mobile phone is proposed. The camera is attached to an ophthalmoscope to record a video of an examination. Software algorithms are then developed to parse the video frames and combine those that are of better quality. For the parsing a method of rapidly selecting valid frames based on colour thresholding and spatial ltering techniques are developed. Registration is the process of determining how the selected frames t together. Spatial cross-correlation is used to register the frames. Only translational transformations are assumed between frames and the designed algorithms focuses on estimating this relative translation in a large set of frames. Methods of optimising these operations are also developed. For the combination of the frames, averaging is used to form a composite image. The results obtained are in the form of enhanced grayscale images of the fundus. These images do not match those captured with fundus cameras in terms of quality, but do show a signi cant increase when compared to the individual frames that they consists of. Collectively a set of video frames can cover a larger region of the fundus than what they do individually. By combining these frames an e ective increase in the eld of view is obtained. Due to low light exposure, the individual frames also contain signi cant noise. In the results the noise is reduced through the averaging of several frames that overlap at the same location.
AFRIKAANSE OPSOMMING: Diabetiese- en hipertensiewe retinopatie is twee algemene oorsake van blindheid wat deur middel van die behandeling van die onderliggende oorsake voorkom kan word. Pasiënte met hierdie toestande word aangemoedig om gereeld ondersoeke te ondergaan om die toestand van die retina te monitor. 'n Oftalmoskoop word gebruik vir hierdie roetine ondersoeke. 'n Oftalmoskoop is 'n relatiewe goedkoop, analoë toestel wat 'n praktisyn toelaat om die agterste interne wand van die oog the ondersoek waar die retina geleë is. Fundus kameras, aan die ander kant, is groter toestelle wat digitale beelde van 'n hoë gehalte kan neem. Dit kos egter aansienlik meer en is dus nie geskik vir gebruik in die veld nie. In hierdie tesis word die ontwerp en implementering van 'n stelsel wat beelde digitaliseer vanaf 'n oftalmoskoop ondersoek. Die fokus is op die ontwikkeling van sagteware algoritmes om die gehalte van die beelde te verhoog. Die doel is nie om die vermoëns van 'n fundus kamera te ewenaar nie, maar eerder om 'n koste-e ektiewe alternatief te lewer wat voldoende is vir gebruik in die veld tydens die roetine monitering van die bogenoemde toestande. 'n Selfoonkamera word vir die digitaliserings proses voorgestel. Die kamera word aan 'n oftalmoskoop geheg om 'n video van 'n ondersoek af te neem. Sagteware algoritmes word dan ontwikkel om die videos te ontleed en om videogrepe van goeie kwaliteit te selekteer en te kombineer. Vir die aanvanklike ontleding van die videos word kleurband drempel tegnieke voorgestel. Registrasie is die proses waarin die gekose rame bymekaar gepas word. Direkte kruiskorrelasie tegnieke word gebruik om die videogrepe te registreer. Daar word aanvaar dat die videogrepe slegs translasie tussen hulle het en die voorgestelde registrasie metodes fokus op die beraming van die relatiewe translasie van 'n groot versameling videogrepe. Vir die kombinering van die grepe, word 'n gemiddeld gebruik om 'n saamgestelde beeld te vorm. Die resultate wat verkry word, word in die vorm van verbeterde gryskleur beelde van die fundus ten toon gestel. Hierdie beelde is nie gelykstaande aan die kwaliteit van beelde wat deur 'n fundus kamera geneem is nie. Hulle toon wel 'n beduidende verbetering teenoor individuele videogrepe. Deur dat 'n groot versameling videogrepe wat gesamentlik 'n groter area van die fundus dek gekombineer word, word 'n e ektiewe verhoging van data in die area van die saamgestelde beeld verkry. As gevolg van lae lig blootstelling van die individuele grepe bevat hul beduidende ruis. In die saamgestelde beelde is die ruis aansienlik minder as gevolg van 'n groter hoeveelheid data wat gekombineer is om sodoende die ruis uit te sluit.
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Giancardo, Luca. "Automated fundus images analysis techniques to screen retinal diseases in diabetic patients." Phd thesis, Université de Bourgogne, 2011. http://tel.archives-ouvertes.fr/tel-00692354.
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In this Ph.D. thesis, we study new methods to analyse digital fundus images of diabetic patients. In particular, we concentrate on the development of the algorithmic components of an automatic screening system for diabetic retinopathy. The techniques developed can be categorized in: quality assessment and improvement, lesion segmentation and diagnosis. For the first category, we present a fast algorithm to numerically estimate the quality of a single image by employing vasculature and colour-based features; additionally, we show how it is possible to increase the image quality and remove reflection artefacts by merging information gathered in multiple fundus images (which are captured by changing the stare point of the patient). For the second category, two families of lesion are targeted: exudate and microaneurysms; two new algorithms which work on single fundus images are proposed and compared with existing techniques in order to prove their efficacy; in the microaneurysms case, a new Radon transform-based operator was developed. In the last diagnosis category, we have developed an algorithm that diagnoses diabetic retinopathy and diabetic macular edema based on the lesions segmented; starting from a single unseen image, our algorithm can generate a diabetic retinopathy and ma cular edema diagnosis in _22 seconds on a 1.6 GHz machine with 4 GB of RAM; additionally, we show the first results of a macular edema detection algorithm based on multiple fundus images, which can potentially identify the swelling of the macula even when no lesions are visible.
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Šikula, Viktor. "Lícování snímků sítnice pomocí metody fázové korelace." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2011. http://www.nusl.cz/ntk/nusl-219201.
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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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Odstrčilík, Jan. "Analýza obrazových dat sítnice pro podporu diagnostiky glaukomu." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-233628.
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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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Bortolin, Júnior Sérgio Antônio Martini. "Detecção automática de microaneurismas e hemorragias em imagens de fundo do olho." Universidade Federal do Pampa, 2013. http://dspace.unipampa.edu.br:8080/xmlui/handle/riu/243.
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Este trabalho tem como objetivo a proposição de um novo método para a detecção automática de microaneurismas e hemorragias em imagens de fundo do olho. Essas lesões são consideradas o primeiro sinal de retinopatia diabética. A retinopatia diabética é uma doença originada pelo diabetes e é apontada com a principal causa de cegueira na população com idade ativa de trabalho. O método proposto é fundamentado em conceitos de morfologia matemática e consiste em eliminar os componentes da anatomia da retina até atingir o conjunto de lesões. Este método é formado por cinco etapas: a) pré-processamento; b) destaque das estruturas escuras; c) detecção dos vasos sanguíneos; d) eliminação dos vasos sanguíneos; e) eliminação da fóvea. A precisão do método foi testada num banco de dados público de imagens de fundo do olho, onde o mesmo obteve resultados satisfatórios e comparáveis aos demais métodos da literatura, reportando médias de sensitividade e especificidade de 87.69% e 92.44%, respectivamente.
This contribution presents an approach for automatic detection of microaneurysms and hemorrhages in fundus images. These lesions are considered the earliest signs of diabetic retinopathy. The diabetic retinopathy is a disease caused by diabetes and is considered as the major cause of blindness in working age population. The proposed method is based on mathematical morphology and consists in removing components of retinal anatomy to reach the lesions. This method consists of five steps: a) pre-processing; b) enhancement of low intensity structures; c) detection of blood vessels; d) elimination of blood vessels; e) elimination of the fovea. The accuracy of the method was tested on a public database of fundus images, where it achieved satisfactory results, comparable to other methods from the literature, reporting 87.69% and 92.44% of mean sensitivity and specificity, respectively.
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Oliveira, André Orlandi de. "Retinógrafo coaxial não-midriático." Universidade de São Paulo, 2017. http://www.teses.usp.br/teses/disponiveis/76/76132/tde-01122017-144856/.
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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.
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Welfer, Daniel. "Métodos computacionais para identificar automaticamente estruturas da retina e quantificar a severidade do edema macular diabético em imagens de fundo de olho." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2011. http://hdl.handle.net/10183/34777.
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Através das imagens de fundo do olho, os especialistas em oftalmologia podem detectar possíveis complicações relacionadas ao Diabetes como a diminuição ou até a perda da capacidade de visão. O Edema Macular Diabético (EMD) é uma das complicações que lideram os casos de danos à visão em pessoas em idade de trabalho. Sendo assim, esta tese apresenta métodos para automaticamente identificar os diferentes níveis de gravidade do Edema Macular Diabético visando auxiliar o especialista no diagnóstico dessa patologia. Como resultado final, propõe-se automaticamente e rapidamente identificar, a partir da imagem, se o paciente possui o EMD leve, moderado ou grave. Utilizando imagens de fundo do olho de um banco de dados livremente disponível na internet (ou seja, o DIARETDB1), o método proposto para a identificação automática do EMD obteve uma precisão de 94,29%. Alguns métodos intermediários necessários para a solução desse problema foram propostos e os resultados publicados na literatura científica.Through color eye fundus images, the eye care specialists can detect possible complications related to diabetes as the vision impairment or vision loss. The Diabetic Macular Edema (DME) is the most common cause of vision damage in working-age people. Therefore, this thesis presents an approach to automatically identify the different levels of severity of diabetic macular edema aiming to assist the expert in the diagnosis of this pathology. As a final result, a methodology to automatically and quickly identify, from the eye fundus image, if a patient has the EMD mild, moderate or severe EMD is proposed. In a preliminary evaluation of our DME grading scheme using publicly available eye fundus images (i.e., DIARETDB1 image database), an accuracy of 94.29% was obtained. Some intermediate methods needed to solve this problem have been proposed and the results published in scientific literature.
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Prosser, Jan. "Lícování sekvencí sítnice pomocí fázové korelace." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2018. http://www.nusl.cz/ntk/nusl-378151.
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This master’s thesis is aimed at registration of frames of retinal fundus video using phase corre- lation. An introduction describes general research in topic of retinal fundus, eye movements, diff erent approaches for image registration, phase correlation and examples of phase corre- lation applications. The second, practical part of master’s thesis, is dedicated to description of the proposed algorithm for registration of frames of retinal fundus video. The description of the proposed algorithm is divided into three parts. First two parts describe how frames of retinal fundus video are rated in terms of suitability for registration. Third part describes image registration algorithm itself. In conclusion, the accuracy of algorithm and computational time are evaluated.
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Harabiš, Vratislav. "Registrace obrazů - aplikace v oftalmologii a ultrasonografii." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-233627.
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Image registration is widely used in clinical practice. However image registration and its~evaluation is still challenging especially with regards to new possibilities of various modalities. One of these areas is contrast-enhanced ultrasound imaging. The time-dependent image contrast, low signal-to-noise ratio and specific speckle pattern make preprocessing and image registration difficult. In this thesis a method for registration of images in ultrasound contrast-enhanced sequences is proposed. The method is based on automatic fragmentation into image subsequences in which the images with similar characteristics are registered. The new evaluation method based on comparison of perfusion model is proposed. Registration and evaluation method was tested on a flow phantom and real patient data and compared with a standard methods proposed i literature. The second part of this thesis contains examples of application of image registration in~ophthalmology and proposition for its improvement. In this area the image registration methods are widely used, especially landmark based image registration method. In this thesis methods for landmark detection and its correspondence estimation are proposed.
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Baše, Michal. "Detekce bifurkací cévního řečiště na sítnici." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2011. http://www.nusl.cz/ntk/nusl-219260.
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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.
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Kadla, Jan. "Časová interpolace oftalmologických videosekvencí pomocí multimodálního lícování." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220855.
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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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Jönsson, Marthina. "Automated methods in the diagnosing of retinal images." Thesis, KTH, Systemsäkerhet och organisation, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-122721.
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This report contains a summation of a variety of articles that have been read and analysed. Each article describes different methods that can be used to detect lesions, optic disks, drusen and exudates in retinal images. I.e. diagnose e.g. Diabetic Retinopathy and Age-Related Macular Degeneration. A general approach is presented, which all methods more or less is based on. Methods to locate the optic disk The PCA kNN Regression Hough Transform Fuzzy Convergence Vessel Direction Matched Filter Etc. The best method based on result, reliability, number of images and publisher is kNN regression. The result of this method is remarkably good and that brings some doubt about its reliability. Though the method was published at IEEE and that gives the method a more trustful look. A next best method which also is very useful is Vessel Direction Matched Filter. Methods to detect drusen – diagnose Age-Related Macular Degeneration PNN classifier Histogram approach Etc. The best method based on result, reliability, number of images and publisher is the PNN classifier. The method had a sensitivity of 94 % and a specificity of 95 %. 300 images were used in the experiment which was published by the IEEE in 2011. Methods to detect exudates – diagnose Diabetic Retinopathy Morphological techniques Luv colour space, Wiener filter an Canny edge detector. The best method based on result, reliability, number of images and publisher is an experiment called “Feature Extraction”. The method includes the Luv colour space, Wiener filter (remove noise) and the Canny edge detector.Den här rapporten innehåller en sammanfattning av ett flertal artiklar som har blivit studerade. Varje artikel har beskrivit en metod som kan användas för att upptäcka sjuka förändringar i ögonbottenbilder, det vill säga, åldersförändringar i gula fläcken och diabetisk retinopati. Metoder för att lokalisera blinda fläcken PCA kNN regression Hough omvandling Suddig konvergens Filtrering beroende på kärlens riktning Mm. Den bästa metoden baserat på resultat, pålitlighet, antal bilder och utgivare är kNN regression. De förvånansvärt goda resultaten kan inbringa lite tvivel på huruvida resultaten stämmer. Artikeln publicerades dock av IEEE och det gör artikeln mer trovärdig. Den näst bästa metoden är filtrering beroende på kärlens riktning. Metoder för att diagnosticera åldersförändringar i gula fläcken PNN klassificeraren Histogram Mm. Den bästa metoden baserat på resultat, pålitlighet, antal bilder och utgivare är PNN klassificeraren. Metoden hade en sensitivitet på 94 % och en specificitet på 95 %. 300 bilder användes i experimentet som publicerades av IEEE år 2011. Metoder att diagnosticera diabetisk retinopati Morfologiska tekniker Luv colour space, Wiener filter and Canny edge detector. Den bästa metoden baserat på resultat, pålitlighet, antal bilder och utgivare är ett experimentet som heter ”Feature Extraction”. Experimentet inkluderar Luv colour space, Wiener filter (brus borttagning) och Canny edge detector
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Vieira, Flávio Pascoal. "Proposta de inovação no sistema de aquisição de imagens aplicado em retinógrafos digitais." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/18/18152/tde-14052013-082239/.
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A retinografia e angiografia digital são técnicas de observação e captura de imagens do fundo do olho que permitem o diagnóstico de diversas patologias. O aperfeiçoamento dos retinógrafos digitais, viabilizado pelos avanços tecnológicos observados nas últimas décadas, tornou possíveis modificações sistêmicas inovadoras como a apresentada e discutida neste trabalho. O principal objetivo é avaliar comparativamente a resolução espacial de imagens captadas com uma configuração que utiliza apenas um sensor monocromático e um conjunto de LEDs cromáticos, com imagens geradas por um sensor com filtro cromático integrado. A proposta é suportada por resultados teóricos que indicam um desempenho superior do uso de sensores monocromáticos em retinografia. Para validação da nova metodologia o sistema descrito foi montado e várias fotos da retina foram capturadas. Todo o processo de imageamento do fundo do olho é descrito, incluindo rotinas de software que precisaram ser criadas em decorrência das inovações. A partir das imagens capturadas foram aplicadas técnicas de avaliação global de maneira que as previsões teóricas puderam ser verificadas. Por fim são apresentadas conclusões sobre o desempenho global do sistema e adicionados tópicos como sugestões para continuidade futura do trabalho.The digital retinography and angiography are techniques to observe and capture images of the eye fundus that allows the diagnosis of several diseases. The improvements of digital fundus camera made possible by technological advances seen in recent decades have made possible innovative systemic changes, as the presented and discussed in this work. The main objective is to comparatively evaluate the spatial resolution of images captured with a configuration that uses only a monochrome sensor and a set of chromatic LEDs, with images generated by a sensor with integrated color filter. The proposal is supported by theoretical results that indicate a superior performance when using a monochrome sensor to get fundus images. To validate the new methodology, the system described was assembled and several retina pictures were taken. The whole process of imaging the eye fundus is described, including software procedures that had to be created as a consequence of the innovations. From the images captured, overall evaluation techniques have been applied, so that theoretical forecasts could be verified. Finally, conclusions are presented on the overall performance of the system and suggestions for topics for future work were added.
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Escorcia, Gutierrez José. "Image Segmentation Methods for Automatic Detection of the Anatomical Structure of the Eye in People with Diabetic Retinopathy." Doctoral thesis, Universitat Rovira i Virgili, 2021. http://hdl.handle.net/10803/671543.
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Aquesta tesi s'emmarca dins del pla integral de prevenció precoç de la Retinopatia Diabètica (RD) posat en marxa pel govern espanyol seguint les recomanacions de l'Organització Mundial de la Salut de promoure iniciatives que consciencien sobre la importància de fer revisions oculars regulars entre les persones amb diabetis.
Per tal de poder determinar el nivell de retinopatia diabètica cal localitzar i identificar diferents tipus de lesions a la retina. Per poder fer-ho, cal que primer s'eliminin de la imatge les estructures anatòmiques normals de l'ull (vasos sanguinis, disc òptic i fòvea) a fi de fer més visibles les anomalies. Aquesta tesi s'ha centrat en aquest pas de neteja de la imatge.
En primer lloc, aquesta tesi proposa un nou marc per a la segmentació ràpida i automàtica del disc òptic basat en la Teoria del Portafoli de Markowitz. En base a aquesta teoria es proposa un model innovador de fusió de colors capaç d'admetre qualsevol metodologia de segmentació en el camp de la imatge mèdica. Aquest enfoc s'estructura com una etapa de pre-processament potent i en temps real que es podria integrar-se a la pràctica clínica diària, permetent accelerar el diagnòstic de la DR a causa de la seva simplicitat, rendiment i velocitat.
La segona contribució d'aquesta tesi és un mètode per fer simultàniament una segmentació dels vasos sanguinis i la detecció de la zona avascular foveal, reduint considerablement el temps de processament d'imatges. A més a més, el primer component de l'espai de color xyY (que representa els valors de crominància) és el que predomina en l'estudi dels diferents components de color desenvolupat en aquesta tesi, centrat en la segmentació dels vasos sanguinis i la detecció de fòvea. Finalment, es proposa una recopilació automàtica de mostres per fer una interpolació estadística del color i que són utilitzades en l'algorisme de segmentació de Convexity Shape Prior.
La tesi també proposa un altre mètode de segmentació dels vasos sanguinis que es basa en una selecció de característiques efectiva basada arbres de decisions. S'ha aconseguit trobar les 5 característiques més rellevants per segmentar aquestes estructures oculars. La validació mitjançant tres tècniques de classificació diferents (arbres de decisions, xarxes neuronals i màquines de suport vectorial).Esta tesis se enmarca dentro del plan integral de prevención contra la Retinopatía Diabética (RD), ejecutado por el Gobierno de España alineado a las políticas de la Organización Mundial de la Salud para promover iniciativas que conciencien a la población con diabetes sobre la importancia de exámenes oculares de manera periódica. Para poder determinar el nivel de retinopatía diabética hace falta localizar e identificar diferentes tipos de lesiones en la retina. Para conseguirlo primero se han de eliminar de la imagen las estructures anatómicas normales del ojo (vasos sanguíneos, disco óptico y fóvea) para hacer visibles las anomalías. Esta tesis se ha centrado en este paso de limpieza de la imagen. En primer lugar, esta tesis propone un novedoso enfoque para la segmentación rápida y automática del disco óptico basado en la Teoría de Portafolio de Markowitz. En base a esta teoría se propone un innovador modelo de fusión de color capaz de soportar cualquier metodología de segmentación en el campo de las imágenes médicas. Este enfoque se estructura como una etapa de preprocesamiento potente y en tiempo real que podría integrarse en la práctica clínica diaria para acelerar el diagnóstico de RD debido a su simplicidad, rendimiento y velocidad. La segunda contribución de esta tesis es un método para segmentar simultáneamente los vasos sanguíneos y detectar la zona avascular foveal, reduciendo considerablemente el tiempo de procesamiento para tal tarea. Adicionalmente, la primera componente del espacio de color xyY (que representa los valores de crominancia) es la que predomina del estudio de las diferentes componentes de color realizado en esta tesis para la segmentación de vasos sanguíneos y la detección de la fóvea. Finalmente, se propone una recolección automática de muestras para interpolarlas basadas en la información estadística de color y que a su vez son la base del algoritmo Convexity Shape Prior. La tesis también propone otro método de segmentación de vasos sanguíneos basado en una selección efectiva de características soportada en árboles de decisión. Se ha conseguido encontrar las 5 características más relevantes para la segmentación de estas estructuras oculares. La validación utilizando tres técnicas de clasificación (árbol de decisión, red neuronal artificial y máquina de soporte vectorial).
This thesis is framed within the comprehensive plan for early prevention of Diabetic Retinopathy (DR) launched by the Spain government following the World Health Organization to promote initiatives that raise awareness of the importance of regular eye exams among people with diabetes. To determine the level of diabetic retinopathy, we need to find and identify different types of lesions in the eye fundus. First, the normal anatomic structures of the eye (blood vessels, optic disc and fovea) must be removed from the image, in order to make visible the abnormalities. This thesis has focused on this step of image cleaning. This thesis proposes a novel framework for fast and fully automatic optic disc segmentation based on Markowitz's Modern Portfolio Theory to generate an innovative color fusion model capable of admitting any segmentation methodology in the medical imaging field. This approach acts as a powerful and real-time pre-processing stage that could be integrated into daily clinical practice to accelerate the diagnosis of DR due to its simplicity, performance, and speed. This thesis's second contribution is a method to simultaneously make a blood vessel segmentation and foveal avascular zone detection, considerably reducing the required image processing time. In addition, the first component of the xyY color space representing the chrominance values is the most supported according to the approach developed in this thesis for blood vessel segmentation and fovea detection. Finally, several samples are collected for a color interpolation procedure based on statistic color information and are used by the well-known Convexity Shape Prior segmentation algorithm. The thesis also proposes another blood vessel segmentation method that relies on an effective feature selection based on decision tree learning. This method is validated using three different classification techniques (i.e., Decision Tree, Artificial Neural Network, and Support Vector Machine).
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Stuchi, José Augusto. "Registro de imagens por correlação de fase para geração de imagens coloridas em retinógrafos digitais utilizando câmera CCD monocromática." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/18/18152/tde-18072013-110903/.
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A análise da retina permite o diagnostico de muitas patologias relacionadas ao olho humano. A qualidade da imagem e um fator importante já que o médico normalmente examina os pequenos vasos da retina e a sua coloração. O equipamento normalmente utilizado para a visualização da retina e o retinógrafo digital, que utiliza sensor colorido com filtro de Bayer e luz (flash) branca. No entanto, esse filtro causa perda na resolução espacial, uma vez que e necessário um processo de interpolação matemática para a formação da imagem. Com o objetivo de melhorar a qualidade da imagem da retina, um retinógrafo com câmera CCD monocromática de alta resolução foi desenvolvido. Nele, as imagens coloridas são geradas pela combinação dos canais monocromáticos R (vermelho), G (verde) e B (azul), adquiridos com o chaveamento da iluminação do olho com LED vermelho, verde e azul, respectivamente. Entretanto, o pequeno período entre os flashes pode causar desalinhamento entre os canais devido a pequenos movimentos do olho. Assim, este trabalho apresenta uma técnica de registro de imagens, baseado em correlação de fase no domínio da frequência, para realizar precisamente o alinhamento dos canais RGB no processo de geração de imagens coloridas da retina. A validação do método foi realizada com um olho mecânico (phantom) para a geração de 50 imagens desalinhadas que foram corrigidas pelo método proposto e comparadas com as imagens alinhadas obtidas como referência (ground-truth). Os resultados mostraram que retinógrafo com câmera monocromática e o método de registro proposto nesse trabalho podem produzir imagens coloridas da retina com alta resolução espacial, sem a perda de qualidade intrínseca às câmeras CCD coloridas que utilizam o filtro de Bayer.The analysis of retina allows the diagnostics of several pathologies related to the human eye. Image quality is an important factor since the physician often examines the small vessels of the retina and its color. The device usually used to observe the retina is the fundus camera, which uses color sensor with Bayer filter and white light. However, this filter causes loss of spatial resolution, since it is necessary a mathematical interpolation process to create the final image. Aiming at improving the retina image quality, a fundus camera with monochromatic CCD camera was developed. In this device, color images are generated by combining the monochromatic channels R (red), G (green) and B (blue), which were acquired by switching the eye illumination with red, green and blue light, respectively. However, the short period between the flashes may cause misalignment among the channels because of the small movements of the eye. Thus, this work presents an image registration technique based on phase correlation in the frequency domain, for accurately aligning the RGB channels on the process of generating retina color images. Validation of the method was performed by using a mechanical eye (phantom) for generating 50 misaligned images, which were aligned by the proposed method and compared to the aligned images obtained as references (ground-truth). Results showed that the fundus camera with monochromatic camera and the method proposed in this work can produce high spatial resolution images without the loss of quality intrinsic to color CCD cameras that uses Bayer filter.
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Štohanzlová, Petra. "Multimodální registrace obrazů sítnice." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2011. http://www.nusl.cz/ntk/nusl-219244.
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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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Říha, Pavel. "Pokročilé zpracování oftalmologických video sekvencí retinálních obrazů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2015. http://www.nusl.cz/ntk/nusl-221355.
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The diploma thesis deals with registration and analysis of images from the experimental low-cost fundus camera that reaches a low SNR (around 10 dB) and low temporal and spatial resolution. The aim of the diploma tesis is to explore the possibilities of digital processing leading to the creation of a videosequence that has real benefits for medical diagnostics. The well-known program elastix is used for registration. Preprocessing filters and interpolation are implemented in Matlab. The program provides a wide range of setting options, out of which many combinations were tested and evaluated. To assess the accuracy achieved, spatial variations in the detected motion of blood-vessels are evaluated. Best results with a precision below 0.3 px were achieved by using a band-pass filter, a~suitably sized mask, rigid registration and a metric of the mutual information. Test sequences were registered precisely enough both for visual assessment and basic computational analysis. Registered sequences and the developed application that both can be used in the further development of the experimental camera are the main contributions of the diploma thesis.
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Macek, Ján. "Klasifikace a rozpoznávání patologických nálezů v obrazech sítnice oka." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2016. http://www.nusl.cz/ntk/nusl-255376.
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Diabetic retinopathy and age-related macular degeneration are two of the most common retinal diseases in these days, which can lead to partial or full loss of sight. Due to it, it is necessary to create new approaches enabling to detect these diseases and inform the patient about his condition in advance. The main objective of this work is to design and to implement an algorithm for retinal diseases classification based on images of the patient's retina of previously mentioned diseases. In the first part of this work, there is described in detail each stage of each disease and its the most frequent symptoms. In this thesis, there is also a chapter about fundus camera, which is a tool for image creation of human eye retina. In the second part of this thesis, there is proposed an approach for classification of diabetic retinopathy and age-related macular degeneration. There is also a chapter about algorithmic methods which can be used for image processing and object detection in image. The last part of this thesis contains the test results and their evaluation. Assessment of success of proposed and implemented methods is also part of this chapter.
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Sekhar, Sribalamurugan. "Automated localisation of landmarks in retinal fundus images." Thesis, University of Liverpool, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.533938.
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Rahim, S. S. "Automatic screening and classification of diabetic retinopathy eye fundus images." Thesis, Coventry University, 2016. http://curve.coventry.ac.uk/open/items/affaf3f0-540a-444e-b6bb-243046d58b25/1.
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Diabetic Retinopathy (DR) is a disorder of the retinal vasculature. It develops to some degree in nearly all patients with long-standing diabetes mellitus and can result in blindness. Screening of DR is essential for both early detection and early treatment. This thesis aims to investigate automatic methods for diabetic retinopathy detection and subsequently develop an effective system for the detection and screening of diabetic retinopathy. The presented diabetic retinopathy research involves three development stages. Firstly, the thesis presents the development of a preliminary classification and screening system for diabetic retinopathy using eye fundus images. The research will then focus on the detection of the earliest signs of diabetic retinopathy, which are the microaneurysms. The detection of microaneurysms at an early stage is vital and is the first step in preventing diabetic retinopathy. Finally, the thesis will present decision support systems for the detection of diabetic retinopathy and maculopathy in eye fundus images. The detection of maculopathy, which are yellow lesions near the macula, is essential as it will eventually cause the loss of vision if the affected macula is not treated in time. An accurate retinal screening, therefore, is required to assist the retinal screeners to classify the retinal images effectively. Highly efficient and accurate image processing techniques must thus be used in order to produce an effective screening of diabetic retinopathy. In addition to the proposed diabetic retinopathy detection systems, this thesis will present a new dataset, and will highlight the dataset collection, the expert diagnosis process and the advantages of the new dataset, compared to other public eye fundus images datasets available. The new dataset will be useful to researchers and practitioners working in the retinal imaging area and would widely encourage comparative studies in the field of diabetic retinopathy research. It is envisaged that the proposed decision support system for clinical screening would greatly contribute to and assist the management and the detection of diabetic retinopathy. It is also hoped that the developed automatic detection techniques will assist clinicians to diagnose diabetic retinopathy at an early stage.
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Smyth, Danielle Julianna. "Characterisation of cellulases from anaerobic fungus Piromyces sp. strain KS11 /." [St. Lucia, Qld.], 2004. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe19081.pdf.
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Laissue, P. P. "Morphogenesis of a filamentous fungus : dynamics of the actin cytoskeleton and control of hyphal integrity in Ashbya gossypii." Thesis, University of Kent, 2004. https://kar.kent.ac.uk/12170/.
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Wang, Su. "On human level understanding of digital fundus images for retinal disease detection." Thesis, University of Surrey, 2017. http://epubs.surrey.ac.uk/814169/.
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Diabetic retinopathy (DR) is the damage to the retina and is a complication that can affect diabetes population. It is one of the most common causes of blindness worldwide. In any diabetic retinopathy screening programme or population based clinical study, a large number of digital fundus images are captured. These images are diagnosed by trained human experts, which can be a costly and time-consuming task due to the number of images they have to examine. Therefore, this is a field that would greatly benefit from the development of automated fundus analysis systems. It may potentially facilitate healthcare in remote regions and developing countries where reading expertise is scarce. The aim of this thesis to automatically analyse fundus images. The inherent variations in such images pose challenges for in-depth understanding on the presence of various DR signs. In this thesis, I first developed approaches for extracting retinal blood vessels and microaneurysms. Singular Spectrum Analysis (SSA) plays a key role to obtain the main structural features from the cross-sectional profiles of candidate objects. A vessel distribution map containing major prominent vessel fragments is constructed by combining SSA and local information. Based on the vessel distribution map, the full vessel network is then tracked and obtained. In microaneurysm detection, the cross-section profiles of candidate objects are filtered through SSA in order to extract a set of features for classification. Both detections have been tested on the publicly available datasets and further large sets of fundus images containing both pathological and healthy retinal photographs, demonstrating their effectiveness through various comparisons. The thesis further investigated human level understanding of digital fundus images for retinal disease detection. This part of work indicated that convolutional neural networks have great potential in developing automated fundus image analysis. Two independent large datasets are used to train two different DR grading systems based on American Academy of Ophthalmology (AAO) grading standards as well as UK National Screening Committee (NSC) grading standards to demonstrate the effectiveness and generic nature of such approach. This method was tested on very large scale sets of images. My method achieves a substantial high sensitivity and specificity of 96.20% and 94.60% respectively compared with previous work, if assuming human’s manual grading is correct. If no assumption on the correctness of human’s grading, high level of statistic agreement is also achieved between the automated system and human.
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Nourse, Jamie. "The structure, organisation and function of dispensable chromosomes in the phytopathogenic fungus Colltotrichum Gloeosporioides /." St. Lucia, Qld, 2001. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe16086.pdf.
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Qureshi, Touseef Ahmad. "Extraction of arterial and venous trees from disconnected vessel segments in fundus images." Thesis, University of Lincoln, 2016. http://eprints.lincoln.ac.uk/23687/.
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The accurate automated extraction of arterial and venous (AV) trees in fundus images subserves investigation into the correlation of global features of the retinal vasculature with retinal abnormalities. The accurate extraction of AV trees also provides the opportunity to analyse the physiology and hemodynamic of blood flow in retinal vessel trees. A number of common diseases, including Diabetic Retinopathy, Cardiovascular and Cerebrovascular diseases, directly affect the morphology of the retinal vasculature. Early detection of these pathologies may prevent vision loss and reduce the risk of other life-threatening diseases. Automated extraction of AV trees requires complete segmentation and accurate classification of retinal vessels. Unfortunately, the available segmentation techniques are susceptible to a number of complications including vessel contrast, fuzzy edges, variable image quality, media opacities, and vessel overlaps. Due to these sources of errors, the available segmentation techniques produce partially segmented vascular networks. Thus, extracting AV trees by accurately connecting and classifying the disconnected segments is extremely complex. This thesis provides a novel graph-based technique for accurate extraction of AV trees from a network of disconnected and unclassified vessel segments in fundus viii images. The proposed technique performs three major tasks: junction identification, local configuration, and global configuration. A probabilistic approach is adopted that rigorously identifies junctions by examining the mutual associations of segment ends. These associations are determined by dynamically specifying regions at both ends of all segments. A supervised Naïve Bayes inference model is developed that estimates the probability of each possible configuration at a junction. The system enumerates all possible configurations and estimates posterior probability of each configuration. The likelihood function estimates the conditional probability of the configuration using the statistical parameters of distribution of colour and geometrical features of joints. The parameters of feature distributions and priors of configuration are obtained through supervised learning phases. A second Naïve Bayes classifier estimates class probabilities of each vessel segment utilizing colour and spatial properties of segments. The global configuration works by translating the segment network into an STgraph (a specialized form of dependency graph) representing the segments and their possible connective associations. The unary and pairwise potentials for ST-graph are estimated using the class and configuration probabilities obtained earlier. This translates the classification and configuration problems into a general binary labelling graph problem. The ST-graph is interpreted as a flow network for energy minimization a minimum ST-graph cut is obtained using the Ford-Fulkerson algorithm, from which the estimated AV trees are extracted. The performance is evaluated by implementing the system on test images of DRIVE dataset and comparing the obtained results with the ground truth data. The ground truth data is obtained by establishing a new dataset for DRIVE images with manually classified vessels. The system outperformed benchmark methods and produced excellent results.
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Ang, Gerard S. L. "Measuring the performance of the Australian multi-sector superannuation funds using data envelopment analysis /." [St. Lucia, Qld], 2004. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe18227.pdf.
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Gosbee, Melinda Jane. "Water deficit stress and the colonisation of mango plant tissue by the stem end rot fungus, Botryospaeria dothidea /." St. Lucia, Qld, 2003. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe17490.pdf.
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Tsukamoto, Shuhei. "The sectoral analysis of credit direction and rationing in Japan from 1954 to 1991 : from the viewpoints of flow-of-funds accounts, financial reforms, and business investments /." St. Lucia, Qld, 2004. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe18082.pdf.
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Tebenkova, Iuliia. "Klasifikace cévního řečiště na snímcích sítnice." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2013. http://www.nusl.cz/ntk/nusl-220067.
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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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Carapito, Sofia Isabel Alexandre. "O estatuto da imagem na publicidade e o seu valor estratégico : reposicionamento da marca Fundão." Master's thesis, Universidade da Beira Interior, 2010. http://hdl.handle.net/10400.6/1269.
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Vivemos, actualmente, numa sociedade que se caracteriza por uma emergente tecnologia das comunicações e dos media de massas, onde se destaca, na publicidade, a importância crescente e visível da imagem, sendo incontornável a sua presença em todos os contextos do quotidiano social.
Estas imagens publicitárias têm o propósito de causar uma sensação e um impacto, de modo a ficar na mente do consumidor, atribuindo, assim, uma identidade a um produto. O uso da imagem tem-se revelado, então, um instrumento valioso de trabalho e um aparelho argumentativo cheio de artifícios, para os quais tem contribuído uma Retórica da Imagem.
Neste Relatório de Estágio, e tendo em conta o pressuposto da afirmação da “sociedade da imagem”, importa compreender a forma como a imagem comunica e transmite as suas mensagens, bem como a importância do uso da imagem na publicidade e a sua contribuição para a construção de uma argumentação persuasiva no anúncio, bem como na construção de identidade de uma marca. Propõe-se, então, desenvolver uma definição da própria imagem, tendo em vista apreender a significação e a produção de sentidos através da mesma, examinar um conjunto de imagens publicitárias, trabalhadas como instrumento de comunicação mais relevante para a publicidade, de acordo com as categorias propostas pelos principias autores que irão ser apresentados, e também procurar avaliar a influência da imagem para a constituição de uma marca forte e apelativa no mercado actual, que se tem pautado por uma crescente exigência visual.
Propõe-se ainda descrever o Estágio Curricular do Mestrado em Comunicação Estratégica: Publicidade e Relações Públicas, da Faculdade de Artes e Letras da Universidade da Beira Interior, realizado na empresa We are one, assim como a estratégia criada para comunicar, através de imagens, a marca “Fundão”.
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Navarro, Coll Julia. "Análisis iconográfico desde una perspectiva de género de las fundas de disco de la Bibliothèque nationale de France desde 1900 hasta 1940." Doctoral thesis, Universitat Politècnica de València, 2016. http://hdl.handle.net/10251/60157.
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[EN] This Doctoral Thesis analyzed from a gender and iconographic perspective still images accompanying the music recorded between 1900 and 1940, particularly in the album sleeves localized by intensive fieldwork in the Bibliothèque nationale de France.
The sample size, 512 individuals, is supported with specific material of particular relevance, wax cylinders package, pianola rolls and albums disc, located on the funds from the Museu de la Música de Barcelona, the Biblioteca de Catalunya, Biblioteca Nacional de España, the Hochschule für Musik und Tanz Köln and Musikaren Euskal Artxiboa, Archivo Vasco de la Música.
The study builds on previous research on the relationship between still image and recorded music, developed by the author in the DEA. The PhD thesis extends these theoretical positions and is based on the localization, selection and cataloging of a representative sample of cases prior to 1940 remaining devalued and discontinued. At the core of the study iconographic variables are determined and visual analysis model based on gender studies, new musicology and image studies are proposed.
Finally, the PhD thesis values the graphic discursive relevance in the period between 1900 and 1940, usually not considered and, however, essential for a global understanding of the phenomenon of sound recording and its implementation as new cultural practice.
This is a documentary investigation based on unpublished primary sources of exploratory nature and inductive character, performed by quantitative analysis tools, qualitative and visual.[ES] La presente Tesis Doctoral analiza desde una perspectiva iconográfica y de género las imágenes fijas que acompañan a la música grabada entre 1900 y 1940, en concreto en las fundas de disco localizadas mediante trabajo de campo intensivo en la Bibliothèque nationale de France. La amplitud de la muestra, 512 ejemplares, se apoya con materiales puntuales de especial relevancia, envases de cilindros de cera, rollos de pianola y álbumes de disco, localizados en los fondos del Museu de la Música de Barcelona, la Biblioteca de Catalunya, la Biblioteca Nacional de España, el Hochschule für Musik und Tanz Köln y el Musikaren Euskal Artxiboa, Archivo Vasco de la Música. El estudio toma como base la investigación precedente sobre la relación entre imagen fija y música grabada, desarrollada por la autora en el DEA. La Tesis Doctoral amplía estas posiciones teóricas y se concreta en la localización, selección y catalogación de una muestra representativa de las fundas de disco previas a 1940 que permanecían devaluadas y descatalogadas. En el núcleo del estudio se determinan las variables iconográficas y se propone un modelo de análisis visual basado en los estudios de género, la nueva musicología y los estudios de la imagen. Finalmente, la Tesis Doctoral pone en valor la relevancia gráfico discursiva del período comprendido entre 1900 y 1940, habitualmente no considerado y, sin embargo, fundamental para la comprensión global del fenómeno de la grabación sonora y su implantación como nueva práctica cultural. Se trata de una investigación documental basada en fuentes primarias inéditas, de naturaleza exploratoria y carácter inductivo, llevada a cabo mediante herramientas de análisis cuantitativo, cualitativo y visual.
[CAT] La present Tesi Doctoral analitza des d'una perspectiva iconogràfica i de gènere les imatges fixes que acompanyen a la música gravada entre 1900 i 1940, en concret en les fongues de disc localitzades mitjançant treball de camp intensiu en la Bibliothèque nationale de France. L'amplitud de la mostra, 512 exemplars, es recolza amb materials puntuals d'especial rellevància, envasos de cilindres de cera, rotllos de pianola i àlbums de disc, localitzats en els fons del Museu de la Música de Barcelona, la Biblioteca de Catalunya, la Biblioteca Nacional de España, el Hochschule für Musik und Tanz Köln i el Musikaren Euskal Artxiboa, Archivo Vasco de la Música. L'estudi pren com a base la recerca precedent sobre la relació entre imatge fixa i música gravada, desenvolupada per l'autora en el DEA. La Tesi Doctoral amplia aquestes posicions teòriques i es concreta en la localització, selecció i catalogació d'una mostra representativa de les fongues de disc prèvies a 1940 que romanien devaluades i descatalogades. En el nucli de l'estudi es determinen les variables iconogràfiques i es proposa un model d'anàlisi visual basada en els estudis de gènere, la nova musicologia i els estudis de la imatge. Finalment, la Tesi Doctoral posa en valor la rellevància gràfic discursiva del període comprès entre 1900 i 1940, habitualment no considerat i, no obstant açò, fonamental per a la comprensió global del fenomen de l'enregistrament sonor i la seua implantació com a nova pràctica cultural. Es tracta d'una recerca documental basada en fonts primàries inèdites, de naturalesa exploratòria i caràcter inductiu, duta a terme mitjançant eines d'anàlisi quantitativa, qualitatiu i visual.
Navarro Coll, J. (2016). Análisis iconográfico desde una perspectiva de género de las fundas de disco de la Bibliothèque nationale de France desde 1900 hasta 1940 [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/60157
TESIS
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Lieberman, Kenneth R. "Reforming a nation : implications of IMF conditionality on Russia /." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2003. http://library.nps.navy.mil/uhtbin/hyperion-image/03Jun%5FLieberman.pdf.
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Thesis (M.A. in National Security Affirs)--Naval Postgraduate School, June 2003.Thesis advisor(s): Robert McNab, Karen Guttieri, Robert Looney. Includes bibliographical references (p. 63-67). Also available online.
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Walczysko, Martin. "Segmentace cév v obrazech sítnice." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2010. http://www.nusl.cz/ntk/nusl-218767.
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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.
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Vančurová, Johana. "Segmentace cévního řečiště v retinálních obrazových datech." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2019. http://www.nusl.cz/ntk/nusl-400975.
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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.
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Grace, Paul. "Investigation of the efficacy of an online diagnostic tool for improving the diagnosis of ocular fundus lesions imaged by Optical Coherence Tomography (OCT)." Thesis, London South Bank University, 2017. http://researchopen.lsbu.ac.uk/1839/.
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Background: Novel ocular imaging technology has proliferated within UK community optometry. Optical Coherence Tomography (OCT) is a pillar of ocular imaging, playing a central role in retinal disease management. As a non-invasive method for diagnosis and follow-up of patients with common retinal conditions such as age-related macular degeneration (AMD) and diabetic macular oedema, OCT is well suited to the primary care setting of community optometry. The novel nature of OCT images presents considerable challenges for community optometrists. AMD prevalence will rise as a consequence of population growth and unprecedented life expectancy and, despite the emergence of novel treatment options, limited clinical capacity threatens access to potentially sight-saving treatment. Limited guidance exists for optometrists using OCT for diagnostic and referral decisions. Objective: To measure the efficacy of a novel internet resource which, if proven to be efficacious, could not only aid in the use of OCT for diagnosis of retinal disease and subsequent patient management but could also play a role in ongoing training of optometrists. Method: An online diagnostic tool (OCTAID) was designed for diagnosis of central retinal lesions using OCT. The effectiveness of OCTAID was evaluated by a randomised controlled trial comparing two groups of practitioners who underwent an online assessment (using clinical vignettes) of their diagnostic and management skills based on OCT images before and after an educational intervention. Participants' answers were validated against experts' classifications (the reference standard). OCTAID was randomly allocated as the educational intervention for one group with the control group receiving an intervention of standard OCT material. Participants: Participants were community optometrists recruited through online optometry forums Setting: Internet based application Results: 53 optometrists (study group) and 65 optometrists (control group) completed the study (n = 118), forming the analysis population. Both groups performed similarly at baseline with no significant difference in mean exam 1 scores (p = 0.212). The primary outcome measure was mean improvement in exam score between the two exam modules. Participants who received OCTAID improved their exam score significantly more than those who received conventional educational materials (p = 0.005). Conclusion: Use of OCTAID is associated with an improvement in the combined skill of OCT scan recognition and subsequent patient management. There is potential for this mode of educational delivery in optometric training. Future work recommendations: With further development, OCTAID could become a collaborative learner-centred model of OCT education allowing optometrists to take responsibility for their own learning within a unique professional community.
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Grizzle, Linda S. "Three Pension Cost Methods under Varying Assumptions." Diss., CLICK HERE for online access, 2005. http://contentdm.lib.byu.edu/ETD/image/etd850.pdf.
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SILVA, Roberto Higino Pereira da. "Algoritmo para extração de imagens de fundo não homogêneos usando o espaço de cores YCbCr." Universidade Federal de Campina Grande, 2006. http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/1511.
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A extração de objetos em uma imagem tem várias aplicações na área da automação, tais como: reconhecimento de padrões em sistemas de vigilância, visão de robôs e outros. Este trabalho apresenta um algoritmo estatístico de extração de imagens no espaço de cores RGB implementado em uma plataforma DSP e a análise dos resultados obtidos. É proposto um outro método estatístico para extração de imagens em fundo desconhecido, podendo ser homogêneo ou não- homogêneo. O algoritmo proposto tem como base o espaço de cores YCbCr , é destinado a aplicações que exigem performance e tolerância a um determinado intervalo de erro. Utiliza a métrica dos máximos para determinar a distância entre os vetores desse espaço, sendo capaz de suportar pequenas variações de luminosidade. Apresenta- se a simulação que validou a funcionalidade desse algoritmo.
The images objects embedded extraction has several applicationns in theautomation area, such as: patterns recognition in surveillance systems, robots vision and others. An image statistical extraction algorithm in the RGB colors space was implemented in a DSP`plataform and the obtained results analysis are presented in this dissertation. We propose a new statistical method for objects extraction in an unknown background (non-homogenous or homogenous), using the YCbCr space. It uses maximum metric to determine its distances betwenn the space vectors, being capable to suport small global variations and places of brightness. They are presented the simulation results that validate the algorithm functionality for applications that demand performance and be tolerant to a determined error interval.
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Tretter, Zdeněk. "Generování syntetických obrazů sítnic oka." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2017. http://www.nusl.cz/ntk/nusl-363734.
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The goal of this thesis is to design and implement a program capable of automatically generating synthetic images of eye retinas. The generated images should be similar to those of real retinas, which are hard to obtain, so they could be used for development of various algorithms, which work with eye retina images in their place. This thesis describes anatomic properties of the eye retina, ways to take images of it and also usage of eye retina recognition in biometric and medicinal applications. Design of the program and the way in which individual parts of the retina are assembled together into the final image is also explained in this thesis. These individual parts are created using procedural textures in separate layers of the image. Next chapter of this work describes implementation details of the program. The conclusion then experimentally verifies suitability of the generated images for algorithmic processing.
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Pres, Martin. "Lokalizace bifurkací ve snímcích sítnice." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2016. http://www.nusl.cz/ntk/nusl-255405.
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From biometrical point of view, main features of retina are fovea, optic nerve and blood vessel tree. Blood vessel tree is unique for each person and this biological feature is used in biometric systems for person-recognition by retinal images. This document describes methods for optic disc and fovea localization, method for vessel tree segmentation, which is based on well-known \emph{Matched filters} method and also describes method for localization of blood vessel bifurcations. Main goal of this thesis is creation of program which can automatically preprocess input image, segment blood vessels and localize vessel bifircations. The program is implemented in Java with OpenCV library.
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Coelho, Luciana Guidon. "Novos métodos de estimação de ruído de fundo de céu aplicados à missão CoRoT." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/3/3142/tde-13092012-105925/.
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O satélite franco-europeu com participação brasileira, CoRoT (Convention, Rotation and planetary Transits), faz parte de uma missão espacial dedicada à sismologia estelar e à busca por exoplanetas. Para a descoberta de exoplanetas, o objetivo é detectar a ocultação temporária da estrela ao redor da qual orbita o planeta em questão, ou seja, detectar um trânsito planetário que pode ser traduzido por uma diminuição tênue do fluxo de fótons estelar coletado pelos CCDs do fotômetro. Existem alguns ruídos e diversas fontes de luz que atingem os CCDs e que não são provenientes das estrelas em estudo. Tais ruídos e fontes de luz geram uma iluminação chamada de fundo de céu nos CCDs que é não homogênea e que precisa ser corrigida antes do início da exploração científica dos dados obtidos nas observações do satélite. A correção de fundo de céu é um procedimento padrão na redução de dados fotométricos, e consiste na subtração do nível médio de fundo de céu das medições fotométricas de uma estrela. Para a determinação do fundo de céu o CoRoT utiliza um conjunto de janelas de fundo de céu. Este trabalho propõem métodos alternativos para a alocação destas janelas de fundo de céu e estimação do ruído de fundo de céu para o canal de exoplanetas do satélite CoRoT. São apresentados dois novos métodos de alocação de janelas e são testados diversos métodos de estimação de ruído de fundo de céu. Os testes realizados neste trabalho sugerem fortemente a utilização do método chamado k-min para a alocação de janelas e do método mediana e 5 vizinhos para a estimação de ruído de fundo de céu. O método k-min procura alocar as janelas de maneira homogênea e em locais de mínimo de uma imagem do céu observado pelo satélite e o método mediana e 5 vizinhos estima o ruído de fundo de céu a partir da mediana de todas as janelas de fundo de céu com nível DC corrigido pela mediana das cinco janelas vizinhas mais próximas.The French-European satellite with Brazilian participation, CoRoT (Convention, Rotation and planetary Transits), is part of a space mission dedicated to stellar seismology and exoplanets search. Both scientific programs are based on a high-precision photometry and require long-term uninterrupted observations. The satellite uses stellar photometry from images captured on CCD (charged coupled devices), known as photometry by mask. For the discovery of exoplanets, the goal is to detect the temporary hiding of the star which around orbits the planet in question, that is, to detect a planetary transit, which can be translated by a slight decrease in the stellar photon flux collected by the CCDs of the photometer. There are some noise and various sources of light that reaches the CCD and are not from the stars under study. Such noise and light sources produce a light called \"sky background\" in CCDs that is not homogeneous and that must be corrected before the scientific exploration of the data obtained from satellite observations. The sky background correction is a standard procedure in the reduction of photometric data. It consists in subtracting the average level of sky background of photometric measurements of a star. To determine the sky background noise, CoRoT uses a set of sky background windows and this work proposes alternative methods for allocating these windows and for estimating the sky background noise to the CoRoT exoplanet channel. Here are present two new methods of windows allocation and are tested several methods of estimating the sky background noise. Tests conducted in this study strongly suggest the use of the method called k-min for windows allocation and the method \"median and 5 neighbors\" to the estimation of sky background noise. The k-min method tries to allocate windows homogeneously and in minimum locals of image of the sky observed by the satellite, and the method \"median and 5 neighbors estimates the sky background noise by the median of all background windows with DC level corrected by the median of the five nearest neighbors.