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Detection of optic disc from fundus camera sequences
Juráček, Radek ; Harabiš, Vratislav (referee) ; Hracho, Michal (advisor)
This bachelor thesis deals with optical disc detection in retinal images taken by an experimental video ophthalmoscope. At the beginning, it briefly describes the anatomy of the eyesight and retina, retinal disease and selected diagnostic methods of retinal imaging. There are described methods of detecting objects in the image, which are subsequently used in the practical part dealing with optical disc detection using Hough transformation and matched filtration. Proposed procedures were tested on a 100-image set. Hough Transformation Detection was successful in 64% of cases, matched filtration was successful in 44% of cases.
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Segmentation of optic disc in retinal image data
Juráček, Radek ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
This bachelor thesis is focused on the algorithm of automatic detection of the optical disk in retinal images. It briefly describes the anatomy of the human eye and the principles of scanning the ocular background. The following describes the optical disk segmentation methods. Selected methods are implemented in MATLAB and optimized using a genetic algorithm. A total of five methods were introduced and optimized on the HRF dataset and two experimental datasets.
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Detection of optic disc from fundus camera sequences
Juráček, Radek ; Harabiš, Vratislav (referee) ; Hracho, Michal (advisor)
This semestral thesis deals with shape detection in images and application of it for detection of optic disk in sequence of fundus camera images. It describes major features of the human eye and retinal diseases. Further the thesis discusses some methods of image preprocessing, segmentation and generalised Hough transform for fundus images which is the main work content for optic disc localization. Practical part describes the proposed methods for detection of optical disk based on a circular Hough transformation and adapted filtering. Method of adaptad filtering achieved median of overlap 59,1%, method using fast Hough transform algorithm achieved median of overlap 24,95%, method using clasic Hough transform algorithm achieved median of overlap 29,95%.
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Segmentation of optic disc in retinal image data
Juráček, Radek ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
This bachelor thesis is focused on the algorithm of automatic detection of the optical disk in retinal images. It briefly describes the anatomy of the human eye and the principles of scanning the ocular background. The following describes the optical disk segmentation methods. Selected methods are implemented in MATLAB and optimized using a genetic algorithm. A total of five methods were introduced and optimized on the HRF dataset and two experimental datasets.
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Detection of optic disc from fundus camera sequences
Juráček, Radek ; Harabiš, Vratislav (referee) ; Hracho, Michal (advisor)
This bachelor thesis deals with optical disc detection in retinal images taken by an experimental video ophthalmoscope. At the beginning, it briefly describes the anatomy of the eyesight and retina, retinal disease and selected diagnostic methods of retinal imaging. There are described methods of detecting objects in the image, which are subsequently used in the practical part dealing with optical disc detection using Hough transformation and matched filtration. Proposed procedures were tested on a 100-image set. Hough Transformation Detection was successful in 64% of cases, matched filtration was successful in 44% of cases.
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|
|
Detection of optic disc from fundus camera sequences
Juráček, Radek ; Harabiš, Vratislav (referee) ; Hracho, Michal (advisor)
This semestral thesis deals with shape detection in images and application of it for detection of optic disk in sequence of fundus camera images. It describes major features of the human eye and retinal diseases. Further the thesis discusses some methods of image preprocessing, segmentation and generalised Hough transform for fundus images which is the main work content for optic disc localization. Practical part describes the proposed methods for detection of optical disk based on a circular Hough transformation and adapted filtering. Method of adaptad filtering achieved median of overlap 59,1%, method using fast Hough transform algorithm achieved median of overlap 24,95%, method using clasic Hough transform algorithm achieved median of overlap 29,95%.
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