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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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Evolution algorithms for ultrasound perfusion analysis
Kolářová, Jana ; Odstrčilík, Jan (referee) ; Mézl, Martin (advisor)
This master´s thesis is focused on the application of evolutionary algorithms for interleaving data obtained by ultrasound scanning of tissue. The interleaved curve serves to estimate perfusion parameters, thus allowing to detect possible pathophysiology in the scanned area. The theoretical introduction is devoted to perfusion and its parameters, contrast agents for ultrasonic application, ultrasonic modality scanning, optimization, evolutionary algorithms in general and two selected evolutionary algorithms - genetic algorithm and bee algorithm. These algorithms were tested on noisy data obtained from clinical images of mice with tumor. The final part summarizes the results of the practical part and provides suggestions and recommendations for further possible development.
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Optimization techniques in image applications
Ondráček, Pavel ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
This thesis deals with methods for optimization in image processing. There is described some of optimization techniques and some applications in image processing. There is also described detailed procedure and realization of bee algorithm, genetic algorithm, PSO algorithm and their realization in image registration, matched filtering, image segmentation and image reconstruction. Algorithms and their efficiencies are compared in the particular application for image processing.
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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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Optimization techniques in image applications
Ondráček, Pavel ; Mézl, Martin (referee) ; Odstrčilík, Jan (advisor)
This thesis deals with methods for optimization in image processing. There is described some of optimization techniques and some applications in image processing. There is also described detailed procedure and realization of bee algorithm, genetic algorithm, PSO algorithm and their realization in image registration, matched filtering, image segmentation and image reconstruction. Algorithms and their efficiencies are compared in the particular application for image processing.
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|
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Evolution algorithms for ultrasound perfusion analysis
Kolářová, Jana ; Odstrčilík, Jan (referee) ; Mézl, Martin (advisor)
This master´s thesis is focused on the application of evolutionary algorithms for interleaving data obtained by ultrasound scanning of tissue. The interleaved curve serves to estimate perfusion parameters, thus allowing to detect possible pathophysiology in the scanned area. The theoretical introduction is devoted to perfusion and its parameters, contrast agents for ultrasonic application, ultrasonic modality scanning, optimization, evolutionary algorithms in general and two selected evolutionary algorithms - genetic algorithm and bee algorithm. These algorithms were tested on noisy data obtained from clinical images of mice with tumor. The final part summarizes the results of the practical part and provides suggestions and recommendations for further possible development.
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