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Analysis of retinal vessel pulsation
Holásková, Anna ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
The content of this work is the analysis of retinal vessels pulsation of video sequences acquired by experimental fundus camera based on measuring the brightness profile of the vessel. The first level of analysis in this work is the segmentation of blood vessels and diameter measurement of blood vessels during the sequence. The work contains research methods dealing with the diameter measurement and evaluation of pulsation and analysis segmentation methods using for analysing the vasculature of the retina. From these methods, a vessel tracking method was selected. In segmented video sequences is on the ground of intensity profiles analysed vessel pulsation. Analysis is also made on original dataset and results are discussed considering the frequency characteristic.
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Plethysmography for retinal video processing
Plavcová, Daniela ; Valterová, Eva (referee) ; Kolář, Radim (advisor)
Sight is one of the five human senses and is very important for exploring near and far surroundings. However, this is prevented by various eye defects, which may be related to the vascular system of the retina and the pulsations that are observable on it. This work deals with the study of the relationship between the mentioned pulsations and glaucoma. To search for connections between these two aspects, video recordings from the retina are used, the pulsation of which is further worked in the form of a 1D signal, especially in the spectral region.
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Classification of retinal blood vessels
Mitrengová, Jana ; Kolář, Radim (referee) ; Odstrčilík, Jan (advisor)
The thesis deals with the classification of the retinal blood vessels in retinal image data. The first part of the thesis deals with the anatomy of the human eye and focuses on the description of the retina and its blood circulation. It further describes the principle of fundus camera and experimental video ophthalmoscope. The second part of the thesis is devoted to a literature search of academic publications that deal with the classification of the retinal vessels into arteries and veins. Subsequently, the principle of selected machine learning methods is presented. Based on the literature research, two methods for the classification of the blood vessels were proposed, the first one using the SVM classifier and the second one using the convolutional neural network U-Net. At the end, the analysis of vascular pulsations was performed. The practical part of the thesis was carried out in Matlab programming interface and images from the RITE, IOSTAR and AFIO database were used for classification and the retinal video sequences taken with an experimental video ophthalmoscope were processed in the analysis of pulsations.
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Plethysmography for retinal video processing
Plavcová, Daniela ; Valterová, Eva (referee) ; Kolář, Radim (advisor)
Sight is one of the five human senses and is very important for exploring near and far surroundings. However, this is prevented by various eye defects, which may be related to the vascular system of the retina and the pulsations that are observable on it. This work deals with the study of the relationship between the mentioned pulsations and glaucoma. To search for connections between these two aspects, video recordings from the retina are used, the pulsation of which is further worked in the form of a 1D signal, especially in the spectral region.
|
|
|
Classification of retinal blood vessels
Mitrengová, Jana ; Kolář, Radim (referee) ; Odstrčilík, Jan (advisor)
The thesis deals with the classification of the retinal blood vessels in retinal image data. The first part of the thesis deals with the anatomy of the human eye and focuses on the description of the retina and its blood circulation. It further describes the principle of fundus camera and experimental video ophthalmoscope. The second part of the thesis is devoted to a literature search of academic publications that deal with the classification of the retinal vessels into arteries and veins. Subsequently, the principle of selected machine learning methods is presented. Based on the literature research, two methods for the classification of the blood vessels were proposed, the first one using the SVM classifier and the second one using the convolutional neural network U-Net. At the end, the analysis of vascular pulsations was performed. The practical part of the thesis was carried out in Matlab programming interface and images from the RITE, IOSTAR and AFIO database were used for classification and the retinal video sequences taken with an experimental video ophthalmoscope were processed in the analysis of pulsations.
|
|
|
Analysis of retinal vessel pulsation
Holásková, Anna ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
The content of this work is the analysis of retinal vessels pulsation of video sequences acquired by experimental fundus camera based on measuring the brightness profile of the vessel. The first level of analysis in this work is the segmentation of blood vessels and diameter measurement of blood vessels during the sequence. The work contains research methods dealing with the diameter measurement and evaluation of pulsation and analysis segmentation methods using for analysing the vasculature of the retina. From these methods, a vessel tracking method was selected. In segmented video sequences is on the ground of intensity profiles analysed vessel pulsation. Analysis is also made on original dataset and results are discussed considering the frequency characteristic.
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