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Criterial function for retinal image registration
Horáková, Pavla ; Kolář, Radim (referee) ; Harabiš, Vratislav (advisor)
This bachelor‘s thesis is focused on comparison criterial functions, which are usually used in registration of retinal images. Criterial functions reflect degree of images’ sameness thereby they influence proper registration considerably. The aim of this thesis is to discover criterial function, which is the best for image registration of retina. Registration of images is very difficult; it is important to get some informations such as an uniqueness or a shape of function.
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Detection of pathologies in retinal images
Mesíková, Klaudia ; Kolář, Radim (referee) ; Vičar, Tomáš (advisor)
The goal of this thesis is to design and implement software for the detection of diabetes mellitus symptoms from the image of the human eye retina. Diabetic retinopathy is the most common disease affecting the retina. Pathologies connected with this disease can lead to partial or complete blindness. For the detection of pathological symptoms is important to correctly detect some parts of the eye retina such as optic disc and blood vessels. These can cause a problem with the identification of disease. After removing the optic disc and blood vessels, the pathology object is being detected.
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Disease Detection in Eye Retina Image
Koštialik, Daniel ; Semerád, Lukáš (referee) ; Maruniak, Lukáš (advisor)
Diabetic retinopathy and age related macular degeneration are among the most common eye retina diseases, which cause partial or complete blindness. The main goal of this thesis is to design and implement software for automatic detection of symptoms from eye fundus images. The detection algorithm is based on the image segmentation by region growing method and afterwards analysis. Determination of retina objects such as optic disc, macula and blood vessels is important prior symptoms detection as they can adversely affect the results of the analysis. Total 259 images were analysed and algorithm reaches more than 90 % average success rate. The algorithm, in combination with appropriate hardware and optic mechanism, forms one of practical application in global population screening. Thanks the automatic detection it is possible to determine the presence of symptoms and start an early treatment.
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Classification and Recognition of Pathologic Foundings in Eye Retina Images
Macek, Ján ; Orság, Filip (referee) ; Drahanský, Martin (advisor)
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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Detection of Diseases of Diabetes on the Human Eye Retina
Sýkorová, Tereza ; Semerád, Lukáš (referee) ; Drahanský, Martin (advisor)
This bachelor's thesis deals with the detection of the symptoms of diabetic retinopathy at retinal images taken by a digital fundus camera. Optic disc, fovea, and blood vessels are found before searching for exudates and hemorrhages. This step improves final detection. The detector uses morphological reconstruction of a candidate region for determination of specific lesions. An algorithm based on thresholding precises its edges. Found regions are classified according to shape and color. Evaluation of detection was done using 120 images selected from three databases. Adding automatic detection of signs of diabetic retinopathy into equipment for retinal screening can help medical doctors in diagnosis and prevent possible vision loss which the disease can cause.
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Detection and Recognition of Diabetes Disease Impacts to the Human Eye Retina
Jausch, Andrej ; Semerád, Lukáš (referee) ; Drahanský, Martin (advisor)
This bachelor's thesis deals with the design of algorithms for the recognition of a diabetes disease impacts to the human eye retina. Diabetic retinopathy is one of the most common diseases aecting the retina and its consequences lead to partial or complete weakness. The basis of the algorithm for detection is to create candidate areas from dierent viewpoints of image processing - computer vision and their subsequent analysis. Core components of the retina have impacts to detection results - optical disc and blood vessels, which need to be properly detected and subsequently excluded from processing. Testing the implemented application took place in 68 images selected from two databases. One of the possible uses of the proposed methods in the future is in combination with the retinal scanning device for the automatic detection of diabetes symptoms during the retinal screening process.
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Comparison of Retinal Images with Pathological Findings
Palacková, Bianca ; Semerád, Lukáš (referee) ; Drahanský, Martin (advisor)
The goal of this thesis is to design and implement software for comparison of retinal images with pathological findings. The most common diseases affecting the retina are diabetic retinopathy and age related macular degeneration. Detection of main components such as optic disc and fovea, need to be detected for proper comparison and detection of diseases. 570 images was used for evaluation of detection of these main components. In both cases, algorithm achieved success over 90\%. 120 images were analysed by 3 ophthalmologists for evaluation of ability to locate pathological findings. Automatic comparison of retinal images can be useful for determination of disease progression.
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Automatic detection of microaneurysms in fundus images
Klímová, Markéta ; Walek, Petr (referee) ; Kolář, Radim (advisor)
Diabetic retinopathy is a serious complication of diabetes mellitus. It develops as a result of total damage of vessels caused by hyperglycemia and it is one of major causes of blindness. The microaneurysms are the first clinically observed pathologies of diabetic retinopathy. The aim of this bachelor thesis is to propose and to implement an automated microaneurysm detector. Teoretical part describes the eye anatomy, diabetic retinopathy and some existing methods of automated detection. Next the implemented solution is described and the results of the detectin are evaluated.
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Microaneurysms and hemorrhages detection in retinal images
Tobiášová, Nela ; Štohanzlová, Petra (referee) ; Kolář, Radim (advisor)
Diabetic retinopathy is a serious eye complication of diabetes mellitus and one of the major causes of blindness in the world. The microaneurysms and the haemorrhages are the pathologies of diabetic retinopathy. Their detection can halt or reverse the progression of this disease and prevent blindness. The algorithms could be helpful to ophthalmologists. This bacherol’s thesis is concerned with the detection of microaneurysms and haemorrhages in fundus images. The diabetic retinopathy, the types of lesions and the treatment methods are described in the first part of the paper. Existing methods are described as follows. The practical part of this work is aimed at the proposal and the detection of the red lesions. It consists of several steps, such as selecting the correct channel of RGB images, using local methods of contrast enhancement, edge detection, thresholding, creating a training set of the feature vector and the classification with the use of the neutral network.
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Tool for Detection and Correction of Images with Diseased Eye Retinas
Jochlík, Jakub ; Semerád, Lukáš (referee) ; Drahanský, Martin (advisor)
Loss or partial loss of eye sight can have major effect on quality of person's life. One of the most common diseases, which causes loss or partial loss of eye sight are diabetic retinopathy and age releated macular degeneration. Both of these diseases can be prevented or mediated by early detection and proper treatment. The fundus camera, which is used to capture eye retina, has had major effect on increasing quality and speed of early detection. Images captured by fundus camera can be automatically analyzed in order to detect any possible signs of retina damage. This thesis proposes one possible way of automating this process. First part of this thesis describes eye, its diseases and capturing technology. Second part then proposes way of automating detection process and its implementation. Lastly, the results are evaluated.
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