23 research outputs found

    Using blind image filtering for images from TEM microscopes

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    Předložená práce se zabývá problematikou slepé filtrace obrazů z transmisního elektronového mikroskopu. V úvodu práce je uveden popis transmisního elektronového mikroskopu. Navazující část popisuje mechanismy interakce elektronů se zkoumaným vzorkem a z toho vyplývající zobrazovací techniky elektronové mikroskopie. Poslední kapitola teoretické části práce zahrnuje popis vybraných metod slepé filtrace obrazu zejména s využitím dekompozice obrazu na charakteristické složky. Taktéž je zde uveden výčet metod pro zhodnocení úspěšnosti filtrace. V praktické části jsou popsány aplikované metody slepé filtrace obrazů a výsledky filtrování. Jednotlivé metody jsou mezi sebou porovnány. Získané výsledky a využitelnost aplikovaných metod jsou zhodnoceny v diskuzi.This work deals with the blind filtration of the images from the transmission electron microscope. At the beginning of this work there is a basic description of the transmission electron microscope. Following part describes the mechanisms of electron interactions with the observed specimen. Description of basic electron microscopy imaging techniques is included. The last chapter of the theoretical part includes the description of several chosen blind image filtration techniques, especially those using the decomposition of the image into characteristic components. It also contains a summary of methods for evaluation the filtration effectiveness. The practical part focuses on a description of applied blind filtering methods and brings the results of the filtration. Individual methods are compared. In conclusion, the obtained results and usability of the applied methods are discussed.

    Quantification en imagerie optique diffuse cérébrale : analyse du signal et étude du problème direct

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    Physiologie -- Physiologie cérébrale humaine -- Couplage neurovasculaire -- Les vaisseaux sanguins cérébraux : les principaux sinus -- Imagerie optique diffuse et analyse du signal -- Définition du problème -- Problème direct -- Problème inverse -- Méthode d'analyse en imagerie optique diffuse -- Neuronavigation IRM-IOD -- IRM fonctionnelle -- Physique de l'IRM -- Neuronavigation -- Équipement de neuronavigation et de visualisation -- Analyse de la sensibilité -- Inverted responses in diffuse optical imaging and their correlation with negative BOLD signal -- Materials and methods -- Results -- Quantification -- Problème direct en imagerie optique diffuse -- Segmentation des tissus à partir de données IRMa -- Simulation Monte Carlo -- Formulation du problème -- Discrétisation et mise en oeuvre numérique -- Hybrid boundary element method applied to volumetric diffuse optical tomography -- Definition of the problem -- Born approximation -- Numerical discretization -- Results

    Temporal integration of loudness as a function of level

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    Image Registration Workshop Proceedings

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    Automatic image registration has often been considered as a preliminary step for higher-level processing, such as object recognition or data fusion. But with the unprecedented amounts of data which are being and will continue to be generated by newly developed sensors, the very topic of automatic image registration has become and important research topic. This workshop presents a collection of very high quality work which has been grouped in four main areas: (1) theoretical aspects of image registration; (2) applications to satellite imagery; (3) applications to medical imagery; and (4) image registration for computer vision research

    Temporal integration of loudness as a function of level

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    Generalized averaged Gaussian quadrature and applications

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    A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal

    MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications

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    Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described

    Analysis of fMRI images with bi-dimensional empirical mode decomposition based-on Green's functions

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    We present a new method for decomposing two-dimensional data arrays with empirical mode decomposition (EMD). It performs envelope surface interpolation based on Green's functions in tension (GiT) to extract bi-dimensional intrinsic mode functions (BIMFs). The new method is called GiT-BEMD and outperforms existing bi-dimensional ensemble EMD (BEEMD) variants in terms of computational costs and quality of extracted intrinsic modes. More specifically, it is easy to implement, much faster than BEEMD, very robust and free from processing artifacts. GiT-BEMD is applied to fMRI data recorded during a contour integration task. Features extracted from resulting volume intrinsic mode functions (VIMFs) achieve higher classification accuracy compared to the canonical BEEMD. The new method thus provides a valuable alternative to existing mode decomposition methods for analyzing images. (C) 2016 Elsevier Ltd. All rights reserved

    Graduate Academic Catalog 2021-2022

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