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Detection of cells in confocal microscopy images
Hubálek, Michal ; Štursa, Dominik (referee) ; Škrabánek, Pavel (advisor)
The goal of the thesis was to create an application that automatically detects healthy cardiomyocytes from images captured by a confocal microscope. The thesis was created based on the specific needs of researchers from the Slovak Academy of Sciences.The application will facilitate and increase the efficiency of their research,because until now they have to evaluate the images and search for suitable cells manually. The RetinaNet convolutional neural network is used for detection and has been implemented in a user-friendly desktop application. The application also automatically records and stores coordinates of detected cells which can be used for capturing cells in higher image quality. Another advantage of the developed application is its versatility, which allows to train detection on other data, making it applicable to other projects. The result of this work is a functional, standalone and intuitive application that is ready to be used by researchers.
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Classification of marked cells migration in tissue
Solař, Jan ; Skopalík, Josef (referee) ; Čmiel, Vratislav (advisor)
This diploma thesis deals with analysing of modern methods for cell detection, visualization and quantification in 3D space. The first section deals with optical methods for cells detection. There is detailed discussion about cell labeling and detection on confocal microscopy. There is also description about developed algorithm for whole cell volume quantification from microscopy images. This could made a comparsion of fluorescence signal according to time of cell labeling and according to cell shapes. There was also optimalization of handmade tissue phantoms visualization. It could be compared a possibilities of cell detections in these phantoms by confocal microscopy and OCT. It was also implemented algorithm for quantification of cells from OCT images. Besides confocal microscopy and OCT cells are also analyzed by other methods. The last part is the Conclusion of results and comparison of used methods.
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Detection of cells in confocal microscopy images
Hubálek, Michal ; Štursa, Dominik (referee) ; Škrabánek, Pavel (advisor)
The goal of the thesis was to create an application that automatically detects healthy cardiomyocytes from images captured by a confocal microscope. The thesis was created based on the specific needs of researchers from the Slovak Academy of Sciences.The application will facilitate and increase the efficiency of their research,because until now they have to evaluate the images and search for suitable cells manually. The RetinaNet convolutional neural network is used for detection and has been implemented in a user-friendly desktop application. The application also automatically records and stores coordinates of detected cells which can be used for capturing cells in higher image quality. Another advantage of the developed application is its versatility, which allows to train detection on other data, making it applicable to other projects. The result of this work is a functional, standalone and intuitive application that is ready to be used by researchers.
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Classification of marked cells migration in tissue
Solař, Jan ; Skopalík, Josef (referee) ; Čmiel, Vratislav (advisor)
This diploma thesis deals with analysing of modern methods for cell detection, visualization and quantification in 3D space. The first section deals with optical methods for cells detection. There is detailed discussion about cell labeling and detection on confocal microscopy. There is also description about developed algorithm for whole cell volume quantification from microscopy images. This could made a comparsion of fluorescence signal according to time of cell labeling and according to cell shapes. There was also optimalization of handmade tissue phantoms visualization. It could be compared a possibilities of cell detections in these phantoms by confocal microscopy and OCT. It was also implemented algorithm for quantification of cells from OCT images. Besides confocal microscopy and OCT cells are also analyzed by other methods. The last part is the Conclusion of results and comparison of used methods.
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