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National Repository of Grey Literature 3 records found  Search took 0.01 seconds. 
Extraction of texture features aimed to detect glaucoma defects
 Daněk, Daniel ; Kolář, Radim (referee) ; Odstrčilík, Jan (advisor)
The thesis deals with an automatic method of texture analysis using Markov random fields texture modeling. The main aim of this work is to find out relevant textural features, which can be used for appropriate classification of the degree of retinal nerve fiber layer loss. The model of Markovian statistic uses a circular symmetric neighborhood structure and a least square error estimation of the model's parameter. Obtained textural features were quantitatively evaluated using correlation analysis. The results show, that there is a significant correlation between proposed textural features and RNFL thickness measured by OCT. Thus, the features can potentially serve for glaucoma diagnosis.
Detailed record
Optic disc detection in video-sequences from experimental fundus camera
 Daněk, Daniel ; Štohanzlová, Petra (referee) ; Odstrčilík, Jan (advisor)
This bachelor thesis deals with the analysis of images from experimental fundus camera, especially with structure of optic disc. The theoretical part describes major features of the human eye and principles of examination, especially examinations of fundus camera. This thesis discusses some methods of analysis and segmentation fundus images. The main work content is based on Hough transform and edge detection for optic disc localization. In the practical part of bachelor thesis we created Hough transform algorithm. Fundus images were tested with this algorithm method.
Detailed record
Extraction of texture features aimed to detect glaucoma defects
 Daněk, Daniel ; Kolář, Radim (referee) ; Odstrčilík, Jan (advisor)
The thesis deals with an automatic method of texture analysis using Markov random fields texture modeling. The main aim of this work is to find out relevant textural features, which can be used for appropriate classification of the degree of retinal nerve fiber layer loss. The model of Markovian statistic uses a circular symmetric neighborhood structure and a least square error estimation of the model's parameter. Obtained textural features were quantitatively evaluated using correlation analysis. The results show, that there is a significant correlation between proposed textural features and RNFL thickness measured by OCT. Thus, the features can potentially serve for glaucoma diagnosis.
Detailed record

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