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Processing of image sequences from fundus camera
Klimeš, Filip ; Odstrčilík, Jan (referee) ; Kolář, Radim (advisor)
Cílem mé diplomové práce bylo navrhnout metodu analýzy retinálních sekvencí, která bude hodnotit kvalitu jednotlivých snímků. V teoretické části se také zabývám vlastnostmi retinálních sekvencí a způsobem registrace snímků z fundus kamery. V praktické části je implementována metoda hodnocení kvality snímků, která je otestována na reálných retinálních sekvencích a vyhodnocena její úspěšnost. Práce hodnotí i vliv této metody na registraci retinálních snímků.
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Data Analysis of a Company Producing Medical Supplies
Kulhánková, Monika ; Bartík, Vladimír (referee) ; Burgetová, Ivana (advisor)
This bachelor's thesis deals with the analysis of the company's sales data, specifically the classification of the customer's type according to his sales data. It provides a theoretical introduction to data mining. It describes the classification process and methods for creating classifiers and presents the CRISP-DM model. This thesis describes the provided data sets, from which the relevant attributes are selected. The data are preprocessed and used in the creation and testing of classification models. The result of this thesis is a comparison of the achieved results.
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Sleep stage classification
Lacinová, Michaela ; Smital, Lukáš (referee) ; Králík, Martin (advisor)
This bachelor thesis deals with analysis of polysomnography and its methods of measurement in electroencephalography, electromyography and electrooculography in the first part. It comprises an analysis of sleep stages recommended by the AASM. Polysomnographic data are further analysed in the domains of time and frequency, which are evaluated separately. In the second part the data are classified into particular classes using methods of decision trees and k-nearest neighbours in the MATLAB programming environment. These data are evaluated and compared with available literature.
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Detection of atrial fibrilation in long-term ECG
Polcer, Simon ; Kozumplík, Jiří (referee) ; Maršánová, Lucie (advisor)
The bachelor’s thesis deals with the automatic detection of atrial fibrillations in the long-term ECG signals. First, it provides a description of the electrophysiology of the heart, the atrial fibrillation and the automatic methods of their detection. The first method, implemented in this work, is based upon the parameters that were calculated from the irregularities of the RR intervals. The second method uses the stationary wavelet transform and other parameters are computed after the signal transformation. The calculated parameters are subsequently statistically evaluated in the STATISTICA software. Parameters are assessed by the non-parametric Mann-Whitney test, which selects parameters that exhibit statistically significant differences between signals containing atrial fibrillation and sinus rhythm. At the end, the classification is performed by two approaches such as Support vector machine and k-Nearest Neighbours.
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Data Analysis of a Company Producing Medical Supplies
Kulhánková, Monika ; Bartík, Vladimír (referee) ; Burgetová, Ivana (advisor)
This bachelor's thesis deals with the analysis of the company's sales data, specifically the classification of the customer's type according to his sales data. It provides a theoretical introduction to data mining. It describes the classification process and methods for creating classifiers and presents the CRISP-DM model. This thesis describes the provided data sets, from which the relevant attributes are selected. The data are preprocessed and used in the creation and testing of classification models. The result of this thesis is a comparison of the achieved results.
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Detection of atrial fibrilation in long-term ECG
Polcer, Simon ; Kozumplík, Jiří (referee) ; Maršánová, Lucie (advisor)
The bachelor’s thesis deals with the automatic detection of atrial fibrillations in the long-term ECG signals. First, it provides a description of the electrophysiology of the heart, the atrial fibrillation and the automatic methods of their detection. The first method, implemented in this work, is based upon the parameters that were calculated from the irregularities of the RR intervals. The second method uses the stationary wavelet transform and other parameters are computed after the signal transformation. The calculated parameters are subsequently statistically evaluated in the STATISTICA software. Parameters are assessed by the non-parametric Mann-Whitney test, which selects parameters that exhibit statistically significant differences between signals containing atrial fibrillation and sinus rhythm. At the end, the classification is performed by two approaches such as Support vector machine and k-Nearest Neighbours.
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Sleep stage classification
Lacinová, Michaela ; Smital, Lukáš (referee) ; Králík, Martin (advisor)
This bachelor thesis deals with analysis of polysomnography and its methods of measurement in electroencephalography, electromyography and electrooculography in the first part. It comprises an analysis of sleep stages recommended by the AASM. Polysomnographic data are further analysed in the domains of time and frequency, which are evaluated separately. In the second part the data are classified into particular classes using methods of decision trees and k-nearest neighbours in the MATLAB programming environment. These data are evaluated and compared with available literature.
|
|
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Processing of image sequences from fundus camera
Klimeš, Filip ; Odstrčilík, Jan (referee) ; Kolář, Radim (advisor)
Cílem mé diplomové práce bylo navrhnout metodu analýzy retinálních sekvencí, která bude hodnotit kvalitu jednotlivých snímků. V teoretické části se také zabývám vlastnostmi retinálních sekvencí a způsobem registrace snímků z fundus kamery. V praktické části je implementována metoda hodnocení kvality snímků, která je otestována na reálných retinálních sekvencích a vyhodnocena její úspěšnost. Práce hodnotí i vliv této metody na registraci retinálních snímků.
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