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Detection of blood elements
Kadlček, Václav ; Kolář, Radim (referee) ; Lamoš, Martin (advisor)
Thesis deals with the detection and subsequent blood elements classification. Blood elements are described mainly in terms of optical features, that is used for digital image processing. Furthermore, available pre-processing theory, image analysis and methods of classifikation are discussed. Acquired knowledges are applied in MATLAB. Image Processing Toolbox is a pillar for that work within this programming environment. The program includes user interface, thus facilitating communication with the program. The program was tested on blood smear images and the results were evaluated.
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Simultaneous EEG/fMRI analysis using EEG data processing
Ištok, Martin ; Vítek, Martin (referee) ; Lamoš, Martin (advisor)
The main objective of this diploma thesis is to describe simultaneous electroencephalography-correlated functional magnetic resonance imaging analysis using EEG data processing. It includes basic characteristics of EEG and fMRI recording and analysis and their combination as simultaneous EEG/fMRI analysis and deals with obstructions during its processing. The thesis includes a design of an experiment used for recording and analysis of simultaneous EEG/fMRI data using EEG source reconstruction for regressor construction. Thesis incorporates a software solution used for extraction of signal describing a source activity interpolated by EEG source reconstruction. The signal is then processed and used to construct a basic regressor. The thesis also deals with the software solution being used for a study focused on intracranial epileptic discharges localization using a simultaneous EEG/fMRI analysis in which it reveals source activity during ongoing epileptic spike and summarizes the results.
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Event Fixation Related Potential During Visual Emotion Stimulation
Mičánková, Veronika ; Lamoš, Martin (referee) ; Potočňák, Tomáš (advisor)
Cílem této diplomové práce je najít a popsat souvislost mezi fixací očí v emočně zabarveném stimulu, kterým je obrázek či video, a EEG signálu. K tomuto studiu je třeba vyvinout softwarové nástroje v prostředí Matlab k úpravě a zpracování dat získaných z eye trackeru a propojení s EEG signály pomocí nově vytvořených markerů. Na základě získaných znalostí o fixacích, jsou v prostředí BrainVision Analyzeru EEG data zpracovány a následně jsou segmentovány a průměrovány jako evokované potenciály pro jednotlivé stimuly (ERP a EfRP). Tato práce je vypracována ve spolupráci s Gipsa-lab v rámci výzkumného projektu.
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Effect of brain regions coordinates selection on dynamic causal modelling results
Veselá, Martina ; Harabiš, Vratislav (referee) ; Lamoš, Martin (advisor)
Master’s thesis is aimed at familiarization with the principles of measurement and data processing functional magnetic resonance, focusing on the analysis of effective connectivity using dynamic causal modelling (DCM). The practical part includes three main thematic areas relating to the description of the processing and evaluation of measured or simulated data. First, there is on sample dataset described the neuroscientific SPM toolbox to analyze measured data. Then follows introduction of the proposed approach with which is investigated the behavior of the model estimation neural interactions with respect to the change of input parameters. This phenomenon is also simulated and on base of achieved results is recommended optimal approach to analyzing effective connectivity using dynamic causal modeling for the group of subjects. The last circuit in the practical part is assessment of shift the coordinates of brain areas on dynamic causal modelling results for the group of subjects from the data obtained from real measurements. Obtained results from simulated data and the results obtained from measured data are evaluated and discussed in the final part.
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Influence of region coordinates selection on dynamic causal modelling results
Klímová, Jana ; Mikl, Michal (referee) ; Lamoš, Martin (advisor)
This thesis deals with functional magnetic resonance imaging (fMRI), in particular with dynamic causal modelling (DCM) as one of the methods for effective brain connectivity analysis. It has been studied the effect of signal coordinates selection, which was used as an input of DCM analysis, on its results based on simulated data testing. For this purpose, a data simulator has been created and described in this thesis. Furthermore, the methodology of testing the influence of the coordinates selection on DCM results has been reported. The coordinates shift rate has been simulated by adding appropriate levels of various types of noise signals to the BOLD signal. Consequently, the data has been analyzed by DCM. The program has been supplemented by a graphical user interface. To determine behaviour of the model, Monte Carlo simulations have been applied. Results in the form of dependence of incorrectly estimated connections between brain areas on the level of the noise signals have been processed and discussed.
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Analysis of connections between simultaneous EEG and fMRI data
Labounek, René ; Kremláček,, Jan (referee) ; Lamoš, Martin (advisor)
Electroencephalography and functional magnetic resonance are two different methods for measuring of neural activity. EEG signals have excellent time resolution, fMRI scans capture records of brain activity in excellent spatial resolution. It is assumed that the joint analysis can take advantage of both methods simultaneously. Statistical Parametric Mapping (SPM8) is freely available software which serves to automatic analysis of fMRI data estimated with general linear model. It is not possible to estimate automatic EEG–fMRI analysis with it. Therefore software EEG Regressor Builder was created during master thesis. It preprocesses EEG signals into EEG regressors which are loaded with program SPM8 where joint EEG–fMRI analysis is estimated in general linear model. EEG regressors consist of vectors of temporal changes in absolute or relative power values of EEG signal in the specified frequency bands from selected electrodes due to periods of fMRI acquisition of individual images. The software is tested on the simultaneous EEG-fMRI data of a visual oddball experiment. EEG regressors are calculated for temporal changes in absolute and relative EEG power values in three frequency bands of interest ( 8-12Hz, 12-20Hz a 20-30Hz) from the occipital electrodes (O1, O2 and Oz). Three types of test analyzes is performed. Data from three individuals is examined in the first. Accuracy of results is evaluated due to the possibilities of setting of calculation method of regressor. Group analysis of data from twenty-two healthy patients is performed in the second. Group EEG regressors analysis is realized in the third through the correlation matrix due to the specified type of power and frequency band outside of the general linear model.
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X-ray projection imaging- model of structural noise suppression
Lamoš, Martin ; Kolář, Radim (referee) ; Drastich, Aleš (advisor)
The aim of this task is to create a program that will simulate noise components and methods of their elimination for X-ray projection imaging with focus on structural noise. MATLAB has chosen as the environment for the implementation. Some of the toolboxes shipped with MATLAB has also been used, mainly the Image Processing Toolbox. The methods and elements are implemented as independent functions, which are highly configurable through the setting of the input parameters. All of functions are covered in a custom application. The model is become user friendly and it is suitable teaching support as a laboratory task. The methods it is possible to use for the structural noise suppression are: temporal image subtraction, temporal integration, matched filtration and recursive filtration. There are three methods of cumulation for physical noise suppression. With proper settings it is possible to suppress also the periodical motional noise suppression.
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Software for patients and brain regions selection suitable for analysis of connectivity in fMRI
Slavíček, Tomáš ; Lamoš, Martin (referee) ; Jan, Jiří (advisor)
The aim of this thesis is to create an exploratory tool for functional magnetic resonance imaging data, which allows quickly and easily making a selection of persons and areas suitable for group analysis of connectivity. In the first chapters of this work is mentioned history of brain research and comparison of methods used in functional imaging. Next they are discussed the theoretical basis of fMRI methods, such as the formation of BOLD signal, acquisition parameters of MRI images and methods for designing experiments. The following chapter describes in detail the analysis of recorded data from the pre-processing to the interpretation of results. The last chapter of the first part describes problems of group analysis in SPM8 software. The second half of this work is dedicated to the description of developed program from data input to saving the results, including detailed descriptions of key features. In conclusion, there is a chapter characterizing the application of developed program on real data from clinical studies, including the results and evaluation of the usability of program. The program will mainly be used in neuroscience research.
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Digital radiography- image processing simulation
Lamoš, Martin ; Kolář, Radim (referee) ; Drastich, Aleš (advisor)
This paper describes a MATLAB application with the main purpose of the simulation of noise components and noise elimination methods of Digital Radiography. The main parts of simulator are the model of a scene, procedures for loading the noise components to image data and methods for image processing. Various methods are employed depending on the type of noise. Subtraction techniques are used for the elimination of structural noise. The physical noise suppression is obtained using several methods of cumulation and Pixel Shift is used to reduce motion artifacts caused by the existence of moving noise. The techniques of superposition highlight the areas of interest in an image. Included are also auxiliary procedures for simulator running and presentation of final data. The model and the presented application can be used mainly for educational purposes as a powerful didactic tool.
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