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Quantitative Digital Holographic Microscopy using machine learning
Duša, Martin ; Kolář, Radim (referee) ; Vičar, Tomáš (advisor)
This thesis presents machine learning methods for determining the parameters of micro and nano particles from digital holographic microscopy images. In the theoretical part the principles of hologram imaging, holographic microscopy and the similarity between Mie theory and hologram are presented. The second part of the theoretical review is devoted to machine learning methods used in determining the quantitative information of particles. The practical part is focused on the design of a procedure for determining the position, refractive index and radius using the U-Net architecture implemented in PyTorch and DeepTrack 2.1. The results of the proposed methodologies are discussed at the end of the paper.
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Rigorous Simulation of Light Interaction with Cells
Dršata, Martin ; Kalousek, Radek (referee) ; Petráček, Jiří (advisor)
This bachelor thesis focuses on rigorous simulations of light scattering by living cells. The first part is dedicated to brief introduction to the given issues and the basic description of the often used computational methods and models of cell structures. Experimental part deals with light scattering simulations using the finite difference time domain method (FDTD). Models of spherical cell and red blood cell are used in these simulations. The aim of the calculations for the first model is to assess the accuracy of the FDTD method with respect to the analytical method using Mie theory of light scattering.
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Measurement of extinction spectra of optically trapped plasmon nano-particles
Flajšmanová, Jana ; Jonáš,, Alexander (referee) ; Brzobohatý, Oto (advisor)
This thesis deals with the dark-field imaging and the optical spectroscopy of optically trapped plasmonic nanoparticles. The optical trapping and the characterization of a single particle or multiple nanoparticles as well are demonstrated. The number of the optically trapped particles can be estimated from the dark-field scattering intensity. Experiments show the presence of the interparticle coupling among trapped metallic nanoparticles which has not been observed in case of dielectric particles. The scattering spectra of the plasmonic nanoparticles were compared with theoretical models based on the Mie theory and the Discrete dipole approximation.
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Quantitative Digital Holographic Microscopy using machine learning
Duša, Martin ; Kolář, Radim (referee) ; Vičar, Tomáš (advisor)
This thesis presents machine learning methods for determining the parameters of micro and nano particles from digital holographic microscopy images. In the theoretical part the principles of hologram imaging, holographic microscopy and the similarity between Mie theory and hologram are presented. The second part of the theoretical review is devoted to machine learning methods used in determining the quantitative information of particles. The practical part is focused on the design of a procedure for determining the position, refractive index and radius using the U-Net architecture implemented in PyTorch and DeepTrack 2.1. The results of the proposed methodologies are discussed at the end of the paper.
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Measurement of extinction spectra of optically trapped plasmon nano-particles
Flajšmanová, Jana ; Jonáš,, Alexander (referee) ; Brzobohatý, Oto (advisor)
This thesis deals with the dark-field imaging and the optical spectroscopy of optically trapped plasmonic nanoparticles. The optical trapping and the characterization of a single particle or multiple nanoparticles as well are demonstrated. The number of the optically trapped particles can be estimated from the dark-field scattering intensity. Experiments show the presence of the interparticle coupling among trapped metallic nanoparticles which has not been observed in case of dielectric particles. The scattering spectra of the plasmonic nanoparticles were compared with theoretical models based on the Mie theory and the Discrete dipole approximation.
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Rigorous Simulation of Light Interaction with Cells
Dršata, Martin ; Kalousek, Radek (referee) ; Petráček, Jiří (advisor)
This bachelor thesis focuses on rigorous simulations of light scattering by living cells. The first part is dedicated to brief introduction to the given issues and the basic description of the often used computational methods and models of cell structures. Experimental part deals with light scattering simulations using the finite difference time domain method (FDTD). Models of spherical cell and red blood cell are used in these simulations. The aim of the calculations for the first model is to assess the accuracy of the FDTD method with respect to the analytical method using Mie theory of light scattering.
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