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dc.contributor.advisorKlíma, Miloš
dc.contributor.advisorFliegel, Karel
dc.contributor.advisorLasser, Theo
dc.contributor.authorLukeš, Tomáš
dc.date.accessioned2017-01-26T08:56:18Z
dc.date.available2017-01-26T08:56:18Z
dc.date.issued2017
dc.identifier.urihttp://hdl.handle.net/10467/66802
dc.description.abstractNovel fundamental research results provided new techniques going beyond the diffraction limit. These recent advances known as super-resolution microscopy have been awarded by the Nobel Prize as they promise new discoveries in biology and live sciences. All these techniques rely on complex signal and image processing. The applicability in biology, and particularly for live cell imaging, remains challenging and needs further investigation. Focusing on image processing and analysis, the thesis is devoted to a significant enhancement of structured illumination microscopy (SIM) and super-resolution optical fluctuation imaging (SOFI)methods towards fast live cell and quantitative imaging. The thesis presents a novel image reconstruction method for both 2D and 3D SIM data, compatible with weak signals, and robust towards unwanted image artifacts. This image reconstruction is efficient under low light conditions, reduces phototoxicity and facilitates live cell observations. We demonstrate the performance of our new method by imaging long super-resolution video sequences of live U2-OS cells and improving cell particle tracking. We develop an adapted 3D deconvolution algorithm for SOFI, which suppresses noise and makes 3D SOFI live cell imaging feasible due to reduction of the number of required input images. We introduce a novel linearization procedure for SOFI maximizing the resolution gain and show that SOFI and PALMcan both be applied on the same dataset revealing more insights about the sample. This PALMand SOFI concept provides an enlarged quantitative imaging framework, allowing unprecedented functional exploration of the sample through the estimation of molecular parameters. For quantifying the outcome of our super-resolutionmethods, the thesis presents a novel methodology for objective image quality assessment measuring spatial resolution and signal to noise ratio in real samples. We demonstrate our enhanced SOFI framework by high throughput 3D imaging of live HeLa cells acquiring the whole super-resolution 3D image in 0.95 s, by investigating focal adhesions in live MEF cells, by fast optical readout of fluorescently labelled DNA strands and by unraveling the nanoscale organization of CD4 proteins on a plasma membrane of T-cells. Within the thesis, unique open-source software packages SIMToolbox and SOFI simulation tool were developed to facilitate implementation of super-resolution microscopy methods.en
dc.language.isoenen
dc.titleSUPER-RESOLUTION MICROSCOPY LIVE CELL IMAGING AND IMAGE ANALYSISen
dc.typedisertační prácecze
dc.description.departmentKatedra radioelektroniky
theses.degree.disciplineRadioelektronika
theses.degree.grantorČeské vysoké učení technické v Praze. Fakulta elektrotechnická. Katedra radioelektroniky
theses.degree.programmeElektrotechnika a informatika


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