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Segmentation of cardiac muscle images acquired using confocal microscopy
 Kadlec, Filip ; Shehadeh, Mhd Ali (oponent) ; Škrabánek, Pavel (vedoucí práce)
Automating data acquisition and processing is common practice in both microscopy and computer vision fields. To classify and localize objects of interest (cardiomyocytes in this case) in microscopy images, segmentation can be performed. In this particular case, semantic segmentation by using deep neural networks was used as the core mean to perform mentioned task and software providing possibility of processing unlabeled data or training neural network architectures on labeled data was implemented. This work does a brief introduction to optical microscopy, inspects segmentation and deep learning in detail and finally describes the process from preparing data, implementing and training neural networks, to design of the final software. This software will ease the work of researchers by providing them with only relevant data, automate microscopy data acquisition, and with minor changes it can be applied to any similar segmentation task.
Úplný záznam
Segmentation of cardiac muscle images acquired using confocal microscopy
 Kadlec, Filip ; Shehadeh, Mhd Ali (oponent) ; Škrabánek, Pavel (vedoucí práce)
Automating data acquisition and processing is common practice in both microscopy and computer vision fields. To classify and localize objects of interest (cardiomyocytes in this case) in microscopy images, segmentation can be performed. In this particular case, semantic segmentation by using deep neural networks was used as the core mean to perform mentioned task and software providing possibility of processing unlabeled data or training neural network architectures on labeled data was implemented. This work does a brief introduction to optical microscopy, inspects segmentation and deep learning in detail and finally describes the process from preparing data, implementing and training neural networks, to design of the final software. This software will ease the work of researchers by providing them with only relevant data, automate microscopy data acquisition, and with minor changes it can be applied to any similar segmentation task.
Úplný záznam

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