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National Repository of Grey Literature 2 records found  Search took 0.00 seconds. 
Implementation of Algorithm for Recognition of Eye Retina
 Ondroušek, Jan ; Stružka, Jaroslav (referee) ; Hájek, Josef (advisor)
Vessel structure is a very important element in medical sience for diagnosis of eye and cardiovascular diseases. Therefore, its automatic segmentation is very important too. In introduction there is a short description of eye retina. After that, method of implementation is presented according to Ing. Jan Odstrčilík's thesis - Analyze of colour retinal images aimed to segmentation of vessel structures created under the auspices of Brno University of Technology - Faculty of Electrical Engineering and Communication, Department of Biomedical Engineering in 2008. This method is based on filtering input image with properly designed filtering masks, followed by thresholding with properly calculated value and finally cleaning result image from artefacts. Algorithm was written in C++ language. All important functions were implemented for purpose of given method with consideration on speed and accuray. Main sections of source code with description of user interface are introduced next in this thesis. At the end, the implementation was tested on real images from ÚBMI and DRIVE databases, results were recorded, expansions and adjustments possibilities of implementation were debated.
Detailed record
Implementation of Algorithm for Recognition of Eye Retina
 Ondroušek, Jan ; Stružka, Jaroslav (referee) ; Hájek, Josef (advisor)
Vessel structure is a very important element in medical sience for diagnosis of eye and cardiovascular diseases. Therefore, its automatic segmentation is very important too. In introduction there is a short description of eye retina. After that, method of implementation is presented according to Ing. Jan Odstrčilík's thesis - Analyze of colour retinal images aimed to segmentation of vessel structures created under the auspices of Brno University of Technology - Faculty of Electrical Engineering and Communication, Department of Biomedical Engineering in 2008. This method is based on filtering input image with properly designed filtering masks, followed by thresholding with properly calculated value and finally cleaning result image from artefacts. Algorithm was written in C++ language. All important functions were implemented for purpose of given method with consideration on speed and accuray. Main sections of source code with description of user interface are introduced next in this thesis. At the end, the implementation was tested on real images from ÚBMI and DRIVE databases, results were recorded, expansions and adjustments possibilities of implementation were debated.
Detailed record

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