Computational Analysis of Fundus Photographs for Early Detection of Diabetic Retinopathy (CROSBI ID 425540)
Ocjenski rad | doktorska disertacija
Podaci o odgovornosti
Prentašić, Pavle
Lončarić, Sven ; Vatavuk, Zoran
engleski
Computational Analysis of Fundus Photographs for Early Detection of Diabetic Retinopathy
Diabetic retinopathy is one of the leading disabling chronic diseases, and one of the leading causes of preventable blindness in the world. In order to achieve early diagnosis of diabetic retinopathy a major effort will have to be invested into automatic screening systems using color fundus photographs. This thesis investigates advanced image processing and analysis methods, which are needed for automatic screening system development. The first contribution of this thesis work is a database of fifty fundus images from healthy and diabetic patients. The data- base has normal and pathological structures labeled by five ophthalmology experts and is used for algorithm development and testing. The second contribution is a method for blood vessel segmentation from fundus photographs using model- based multi-scale vessel tracking. In order to locate the optic disc, which is present in all fundus photographs, a method based on a voting- based classifier and stochastic learning is presented as one of the thesis contributions. We show that this approach easily outperforms methods which are part of the classifier ensemble. In or- der to detect exudates, which are one of the most important early signs of diabetic retinopathy, a method based on combining a deep convolutional neural network with specific ophthalmic knowledge in one expert system was developed and represents the last thesis contribution. In the end, the thesis gives a summary of the work with considerations about potential performance improvements.
image processing, image analysis, computer vision, diabetic retinopathy
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Podaci o izdanju
79
14.02.2019.
obranjeno
Podaci o ustanovi koja je dodijelila akademski stupanj
Fakultet elektrotehnike i računarstva
Zagreb