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Segmentation of carbon nanocones in TEM images using generalized Hough transform
Sladký, Vladimír ; Odstrčilík, Jan (referee) ; Walek, Petr (advisor)
Bachelor thesis deals with automatic detection of carbon nanostructures in TEM images using generalized Hough transform. There is described the theory of Hough transform in order to detect analytic as well as general structures in images. According to the characteristics of carbon nanostructures TEM images synthetic test images, that are preprocessed by morphological operations and thresholding with global threshold, are created. Hough transform algorithm that detects nanocones in synthetic images of carbon nanocone structures is created. Success and accuracy of detection is tested changing the parameters of artificial images or level of preprocessing.
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Brain connectivity estimation
Sladký, Vladimír ; Jurčo, Juraj (referee) ; Cimbálník, Jan (advisor)
Epileptic disease is connected with change in activity of neuronal clusters. Brain connectivity analysis deals with statistic interdependencies between different neuronal centres. Earlier studies show that changes in connectivity can be seen near primary epileptic site. What is changing connectivity and its characteristic in interictal recordings are yet to be fully known. In this thesis are analyzed data from intracranial EEG electrodes, positioned in and neighboring areas of epileptic site. Changes in connectivity of epileptic site and its surroundings are observed by nonlinear correlation method. Decrease in connectivity of epileptic site during slow wave sleep was detected on frequencies above 80 Hz. Reduced connectivity was measured on the border of epileptic zone and normal tissue. Observed features are accentuated during sleep. It was also found out that connectivity at the border of epileptic zone apears to have nonlinear property. The results show that physiological processes during sleep are influencing connectivity near epileptic site and decrease in connectivity may be related to nonlinear dependence of neuronal activity at the border of epileptic zone. This study confirms hypothesis of the earlier studies and reveals new facts about connectivity of epileptic site from the perspective of nonlinear processes. Consequent study based on this findings might lead to more precise delineation of epileptic site and to better understanding of processes, which are causing epileptic fits.
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Segmentation of carbon nanocones in TEM images using generalized Hough transform
Sladký, Vladimír ; Odstrčilík, Jan (referee) ; Walek, Petr (advisor)
Bachelor thesis deals with automatic detection of carbon nanostructures in TEM images using generalized Hough transform. There is described the theory of Hough transform in order to detect analytic as well as general structures in images. According to the characteristics of carbon nanostructures TEM images synthetic test images, that are preprocessed by morphological operations and thresholding with global threshold, are created. Hough transform algorithm that detects nanocones in synthetic images of carbon nanocone structures is created. Success and accuracy of detection is tested changing the parameters of artificial images or level of preprocessing.
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|
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Brain connectivity estimation
Sladký, Vladimír ; Jurčo, Juraj (referee) ; Cimbálník, Jan (advisor)
Epileptic disease is connected with change in activity of neuronal clusters. Brain connectivity analysis deals with statistic interdependencies between different neuronal centres. Earlier studies show that changes in connectivity can be seen near primary epileptic site. What is changing connectivity and its characteristic in interictal recordings are yet to be fully known. In this thesis are analyzed data from intracranial EEG electrodes, positioned in and neighboring areas of epileptic site. Changes in connectivity of epileptic site and its surroundings are observed by nonlinear correlation method. Decrease in connectivity of epileptic site during slow wave sleep was detected on frequencies above 80 Hz. Reduced connectivity was measured on the border of epileptic zone and normal tissue. Observed features are accentuated during sleep. It was also found out that connectivity at the border of epileptic zone apears to have nonlinear property. The results show that physiological processes during sleep are influencing connectivity near epileptic site and decrease in connectivity may be related to nonlinear dependence of neuronal activity at the border of epileptic zone. This study confirms hypothesis of the earlier studies and reveals new facts about connectivity of epileptic site from the perspective of nonlinear processes. Consequent study based on this findings might lead to more precise delineation of epileptic site and to better understanding of processes, which are causing epileptic fits.
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