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Illness Detection in Eye Retina Image
Aubrecht, Tomáš ; Drahanský, Martin (referee) ; Semerád, Lukáš (advisor)
Age-related macular degeneration is one of the most common retinal diseases of the human eye that leads at different rates to blindness. This disease occurs in two forms. While the wet can slow down its progression, for dry form there is no available treatment method so far, so prevention is the most important. For this reason, the aim of this work is to design and implement software that allows automatic detection of the symptoms of this disease from retinal images. The symptom detection algorithm is based on adaptive thresholding which obtains suspicious areas that are subsequently categorized. 407 retinal images were used for the evaluation and the software was highly successful. When used in conjunction with an optical retinal scanner, it helps ophthalmologists, for example, to diagnose more quickly.
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Detection and Recognition of ARMD Disease Impacts to the Human Eye Retina
Stančíková, Ivana ; Semerád, Lukáš (referee) ; Drahanský, Martin (advisor)
This thesis aims to create a software able to detect symptoms of age-related macular degeneration in images of human eye retina. This condition is considered one of the leading causes of vision loss in older adults. Lesions of the macular area called drusen are the first and also the most distinctive sign of developing ARMD. The approach presented in this thesis utilizes methods of image processing and computer vision to recognize retinal structures, in particular the optical disk and blood vessels, and distinguish between these structures and actual symptoms of the disease. The evaluation of the program's success rate was performed on 692 images originating from four databases. The resulting solution has the potential to assist medical professionals with earlier diagnosis of the disease and thus contribute to prevention of severe vision loss.
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Detection and Recognition of ARMD Disease Impacts to the Human Eye Retina
Stančíková, Ivana ; Semerád, Lukáš (referee) ; Drahanský, Martin (advisor)
This thesis aims to create a software able to detect symptoms of age-related macular degeneration in images of human eye retina. This condition is considered one of the leading causes of vision loss in older adults. Lesions of the macular area called drusen are the first and also the most distinctive sign of developing ARMD. The approach presented in this thesis utilizes methods of image processing and computer vision to recognize retinal structures, in particular the optical disk and blood vessels, and distinguish between these structures and actual symptoms of the disease. The evaluation of the program's success rate was performed on 692 images originating from four databases. The resulting solution has the potential to assist medical professionals with earlier diagnosis of the disease and thus contribute to prevention of severe vision loss.
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Illness Detection in Eye Retina Image
Aubrecht, Tomáš ; Drahanský, Martin (referee) ; Semerád, Lukáš (advisor)
Age-related macular degeneration is one of the most common retinal diseases of the human eye that leads at different rates to blindness. This disease occurs in two forms. While the wet can slow down its progression, for dry form there is no available treatment method so far, so prevention is the most important. For this reason, the aim of this work is to design and implement software that allows automatic detection of the symptoms of this disease from retinal images. The symptom detection algorithm is based on adaptive thresholding which obtains suspicious areas that are subsequently categorized. 407 retinal images were used for the evaluation and the software was highly successful. When used in conjunction with an optical retinal scanner, it helps ophthalmologists, for example, to diagnose more quickly.
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