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Software tool for simulation of PET imaging
Maláňová, Katarína ; Nohel, Michal (referee) ; Mézl, Martin (advisor)
This bachelor´s thesis is focusing on imaging systems in nuclear medicine, with a detailed emphasis on PET imaging. Additionally, several software tools for simulation of this imaging process are summarized. In the practical part, a basic simulation is created using Python programming. The output of the simulation is a sinogram, which is subsequently used in various reconstruction algorithms. The simulation includes attenuation and TOF correction. A separate program has been created to demonstrate the effects of different parameters.
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Simulation of contrast-agent distribution in a real microvascular system
Schwachulová, Natalia ; Mézl, Martin (referee) ; Jiřík, Radovan (advisor)
The goal of this thesis is to simulate the distribution of contrast agents in a real microvascular system in order to validate methods used in perfusion imagining in DCE-MRI. It contains explanation of principles of the DCE-MRI method and introduction of blood vessels in each of the murine tissue datasets. The thesis resolves around finding graph model, representing blood vessels in used datasets, calculating diameter and respective vascular resistance of each blood vessel, determining direction of blood flow in the blood territory, estimation of impulse residual function of each tissue and creation of generator of concentration curves. Obtained concentration curves are then used to estimate perfusion parameters , and and analyzed using SW PerfLab in order to determine, which pharmacokinetic model is the best to represent each tissue.
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ECG biometrics using deep learning
Repčík, Tomáš ; Mézl, Martin (referee) ; Vičar, Tomáš (advisor)
This diploma thesis makes a comprehensive overview of various approaches to the usage of ECG as biometry. ECG of people was measured with ECG capable wristband for training and testing purposes. The measurements were gathered during the four-month period. The neural networks of various types were trained on these data, and the feedforward convolutional neural networks have the best performance. These models reached a true acceptance rate 98,9% and a true rejection rate 99,5% on average. After training, the models have been visualised with a variety of techniques and essentials parts of ECG for verification have been described. The thesis also describes the first implementation of the Android application.
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Detection of ventricular extrasystoles
Svánovská, Zuzana ; Mézl, Martin (referee) ; Sekora, Jiří (advisor)
Ventricular extrasystoles are pathological changes in the ECG signal. Detection of ventricular extrasystoles on 12leads ECG was created in MATLAB. My work contains two algorithms. The first of these algorithms is based on comparision wides of QRS komplexes. The second algorithm matchs maximum and minimum evaluations of QRS komplexes. We look for agreements beetween these two algorithms and finally if we find these agreenments in seven leads at least we will suppose presence of ventricular extrasystoles.
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Sudoku - algorithmization of solution
Buchta, Martin ; Sekora, Jiří (referee) ; Mézl, Martin (advisor)
In this paper, we present an overview of techniques that can be used by people to solve a Sudoku Puzzle. The individual algorithms were theoretically described using real tasks and were implemented on this basis to appropriate graphical user interface in Matlab with the possibility of webcam task loading.
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Methods for respiration estimates from ECG signal
Mitrengová, Jana ; Mézl, Martin (referee) ; Králík, Martin (advisor)
The thesis deals with the realization of methods for estimation of the respiratory curve from the ECG signal. The first part of the thesis deals with the anatomy and physiology of the respiratory and cardiovascular system. In this part of the thesis are also described ways of the breathing monitoring. The second part of the thesis is dedicated to the description of individual methods for the ECG derived respiration. The third part deals with the realization of selected methods, application of method algorithms on real data and comparison of resulting respiratory curves with the respiratory signals available from the PhysioNet database. In conclusion, the individual methods are compared with each other.
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Image registration of ultrasound sequences using evolutionary algorithms
Hnízdilová, Bohdana ; Odstrčilík, Jan (referee) ; Mézl, Martin (advisor)
This master´s thesis deals with the registration of ultrasound sequences using evolutionary algorithms. The theoretical part of the thesis describes the process of image registration and its optimalization using genetic and metaheuristic algorithms. The thesis also presents problems that may occur during the registration of ultrasonographic images and various approaches to their registration. In the practical part of the work, several optimization methods for the registration of a number of sequences were implemented and compared.
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Face detection in image
Koudela, Ondřej ; Harabiš, Vratislav (referee) ; Mézl, Martin (advisor)
This work is basic overview over methods of face detection in picture and it's components. The main part of the work is an example of algorithm developed in MATLAB programming language for face detection based on skin color segmentation in different color spaces and their implementation in real time. The basic algorithm is discussed in several steps with shown results for each of color spaces and in the end of the work is evaluation of used methods. This work also includes a simulation of processing real-time detection in MATLAB Simulink.
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Epidemiological modeling of Covid-19
Schubert, Richard ; Kašpar, Jakub (referee) ; Mézl, Martin (advisor)
This thesis deals with the continuous epidemiological deterministic compartmental models and the COVID-19 pandemic modeling distinctive features. The effect of different probability distributions of individuals stay in compartments is studied numerically in relation to basic reproductive number and the final size of the epidemic, respectively. New model for a retrospective analysis of the first half of 2020 northern Italy epidemiological data is proposed. The model parameters estimation is performed using minimisation of weighted sum of squared residuals and the search through parameter space with BFGS algorithm implementation.
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Face detection in image
Pospíšil, Lukáš ; Harabiš, Vratislav (referee) ; Mézl, Martin (advisor)
The main puprose of this paper is to introduce some of algorithms used in face detection in images. This paper focuses on face detection by using a skin-color based segmentation that is computed in three color spectrums (RGB,YCbCr and HSV). This paper also includes software for face detection in pictures and videos.
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