Long exposure handheld photography is coupled with the problem of blurring, which is difficult to remove without additional information. The goal of this work was to utilize motion sensors contained in modern smartphones to detect exact motion track of the image sensor during the exposure and then to remove the blur from the resulting photograph according to this data. A system was proposed which performs deconvolution using a kernel from the recorded gyroscope data. An implementation on Android platform was proved on a test smartphone device.

In the presented work we study the methods of image deblurring using two images of the same scene with different exposure times, focusing on two main approach categories, so called deconvolution and non-deconvolution methods. We present theoretical backgrounds on both categories and evaluate their limitations and advantages. We dedicate one section to compare both method categories on test data (images) for which we our MATLAB implementation of the methods. We also compare the effectiveness of said methods against the results of a selected single-image de-noising algorithm. We do not focus at computational efficiency of algorithms and work with single-channel images only.

This thesis deals with the topic of 3D image processing for digital holographic microscopy - numerical refocusing. This method allows to perform mathematically accurate defocus correction on image of a sample captured away from the sample plane and it was applicable only for images that were made made using coherent illumination source. It has been generalized to a form in which it is also applicable to devices that use incoherent (non-monochromatic or extended) illumination sources. Another presented achievement concerns hologram processing. The advanced hologram processing method enables obtaining more data mainly concerning precision of quantities from one hologram — normally, one would have to capture multiple holograms to get those. Both methods have been verified experimentally.

In the presented work we study methods of image deblurring using two images of the same scene with different exposure times, focusing on two main approach categories, the so called deconvolution and non-deconvolution methods. We present theoretical backgrounds on both categories and evaluate their limitations and advantages. We dedicate one section to a comparison of both method categories on test data (images) for which we use a MATLAB implementation of the methods. We also compare the effectiveness of said methods against the results of a selected single- image de-noising algorithm. We do not focus at computational efficiency of algorithms and work with grayscale images only.

This paper deals with the variability of HRF, which may have crucial impact on outcomes of fMRI neuronal activation detection in some cases. There are three methods described - averaging, regression deconvolution and biconjugate gradient method - which provide HRF shape estimation. In frame of simulations regression method, which uses B-spline curves of 4-th order for window length of 30 s, was chosen as the most robust method. Deconvolution estimates was used as HRF models for classic analyse of fMRI data, concretely visual oddball paradigm, via general linear model. Enlargement of localizated areas was observed and after expert consultation with scientific employees from neurology clinic, outcomes was evaluated as relevant. Furthermore Matlab application, which provides confortable observation of HRF variability among brain areas, was made.

In this thesis, I deal with the measurement of the transverse momentum spectrum of the top quark produced in top-antitop pairs at the LHC at center of mass energy 7 TeV. The analysis is carried out within the ATLAS collaboration. In the single lepton decay channel, I have performed studies on the simulation which were necessary to obtain the final spectrum from real data. I describe basic event selection rules to reduce background events. I study the efficiency of top-antitop pairs reconstruction. I study the unfolding of the measured spectrum which corrects for effects caused by imperfect resolutions. At the end, I show the measured top quark transverse momentum spectrum obtained from my analysis.

This thesis deals with the topic of 3D image processing for digital holographic microscopy - numerical refocusing. This method allows to perform mathematically accurate defocus correction on image of a sample captured away from the sample plane and it was applicable only for images that were made made using coherent illumination source. It has been generalized to a form in which it is also applicable to devices that use incoherent (non-monochromatic or extended) illumination sources. Another presented achievement concerns hologram processing. The advanced hologram processing method enables obtaining more data mainly concerning precision of quantities from one hologram — normally, one would have to capture multiple holograms to get those. Both methods have been verified experimentally.

Tato dizertační práce představuje metodu zobrazování perfúze magnetickou rezonancí, jež je výkonným nástrojem v diagnostice, především v onkologii. Po ukončení sběru časové sekvence T1-váhovaných obrazů zaznamenávajících distribuci kontrastní látky v těle začíná fáze zpracování dat, která je předmětem této dizertace. Je zde představen teoretický základ fyziologických modelů a modelů akvizice pomocí magnetické rezonance a celý řetězec potřebný k vytvoření obrazů odhadu parametrů perfúze a mikrocirkulace v tkáni. Tato dizertační práce je souborem uveřejněných prací autora přispívajícím k rozvoji metodologie perfúzního zobrazování a zmíněného potřebného teoretického rozboru.

Title: Deconvolution fluorescence microscopy of yeast cells Author: Tomáš Štec Department: Institute of Physics of Charles University Supervisor: prof. RNDr. Jarmoír Plášek, CSc., Institute of Physics of Charles Uni- versity Abstract: Fluorescence microscopy presents an fast and cheap alternative to more advanced imaging methods like confocal and electron microscopy, even though it is subject to heavy image distortion. It is possible to recover most of the original distortion-free image using deconvolution in computer image processing. This al- lows reconstruction of 3D structure of studied objects. Deconvolution procedure of NIS Elements AR program undergoes an thorough inspection in this diploma the- sis. It is then applied on restoration of 3D structure of calcofluor stained cell wall of budding yeast Saccharomyces cerevisiae. Changes of the structure of the cell wall during cell ageing are being examined. Cell wall of aged cells shows increased surface roughness and even ruptures at the end of cell life. Keywords: fluorescence, microscopy, deconvolution, NIS Elements AR, calcofluor, yeast, cell wall, ageing

The theoretical part of this work describes perfusion analysis of dynamic contrast enhanced magnetic resonance imaging from data acquisition to estimation of perfusion parameters. The main application fields are oncology, cardiology and neurology. The thesis is focused on quantitative perfusion analysis, specifically it contributes to solving of the the main challenge of this method – correct estimation of the contrast-agent concentration sequence in the arterial input of the region of interest (arterial input function). The goals of the thesis are stated based on literature review and on the expertise of our group. Blind deconvolution is selected as the method of choice. In the practical part of this thesis, a new method for arterial input function identification based on blind deconvolution is proposed. The method is designed for both preclinical and clinical applications. It was validated on synthetic, preclinical and clinical data. Furthermore, possibilities of the longer temporal sampling provided by blind deconvolution were analyzed. This can be used for improved spatial resolution and possibly for higher SNR. For easier deployment of the proposed methods into clinical and preclinical use, a software tool for perfusion data processing was designed.