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Relationship between Electrophysiological Activity and Dynamic Functional Connectivity of Large-scale Brain Networks in fMRI Data
Lamoš, Martin ; Hlinka, Jaroslav (referee) ; Kremláček, Jan (referee) ; Jan, Jiří (advisor)
Functional brain connectivity is a marker of the brain state. Growing interest in the examination of large-scale brain network functional connectivity dynamics is accompanied by an effort to find the electrophysiological correlates. The commonly used constraints applied to spatial and spectral domains during EEG data analysis may leave part of the neural activity unrecognized. A proposed approach blindly reveals multimodal EEG spectral patterns that are related to the dynamics of the BOLD functional network connectivity. The blind decomposition of EEG spectrogram by Parallel Factor Analysis has been shown to be a useful technique for uncovering patterns of neural activity where each pattern contains three signatures (spatial, temporal, and spectral). The decomposition takes into account the trilinear structure of EEG data, as compared to the standard approaches of electrode averaging, electrode subset selection or using standard frequency bands. The simultaneously acquired BOLD fMRI data were decomposed by Independent Component Analysis. Dynamic functional connectivity was computed on the component’s time series using a sliding window correlation, and functional connectivity network states were then defined based on the values of the correlation coefficients. ANOVA tests were performed to assess the relationships between the dynamics of functional connectivity network states and the fluctuations of EEG spectral patterns. Three patterns related to the dynamics of functional connectivity network states were found. Previous findings revealed a relationship between EEG spectral pattern fluctuations and the hemodynamics of large-scale brain networks. This work suggests that the relationship also exists at the level of functional connectivity dynamics among large-scale brain networks when no standard spatial and spectral constraints are applied on the EEG data.
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Segmentation of blood-vessel tree in whole-body MRI data
Guricová, Karolína ; Lamoš, Martin (referee) ; Kolář, Radim (advisor)
Práce popisuje anatomii a vlastnosti cévního eit s charakteristickými znaky, na kterých je zaloena jeho segmentace. Nejprve jsou uvedeny metody segmentace 3D CT a MRI sken. Více detailn jsou popsány základy segmentace zaloené na druhých derivacích a Hessov matici. K urení podobnosti cévám v pvodním obraze jsou spoítány vlastní ísla Hessovy matice kadého voxelu. K vytvoení výsledného segmentovaného obrazu je navreno více metod pro zpracování tchto vlastních ísel. Metoda je prakticky implementována v MATLABu. Vysegmentované arteriální eit je visualizováno pomoc í knihovny VTK kódované v Pythonu. Dále je navreno GUI, které umouje mení v zpracovaném objemu. Délky artérií jsou aproximovány lineárními úseky kopírujícími jejich cesty a výsledky tohoto mení jsou v práci prezentovány. Limitace této metody a návrh na poloautomatické mení jsou rozebrány na konci této práce.
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Service Messenger for Windows
Popelka, Petr ; Lamoš, Martin (referee) ; Sekora, Jiří (advisor)
This thesis describes the process of communication in Ethernet based on TCP/IP model. Client – server application was designed and realized using this model. This application can be used to send service messages between groups of doctors and workplace of OKB in FN Brno. This thesis also describes current laboratory equipment and communication between them laboratory information system using the protocol ASTM. This communication can be later used to develop other features of the designed application.
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Toolbox for neuronal datasets
Malý, Lukáš ; Harabiš, Vratislav (referee) ; Lamoš, Martin (advisor)
The aim of this bachelor's thesis was to create toolbox for functional magnetic resonance (fMRI) and electroencefalography (EEG) data processing in MATLAB enviroment using SPM software package. The first part describes the physiological origin of these data at neuronal level, basics of magnetic resonance imaging, principles of fMRI experiment, preprocessing and processing of fMRI data, their interpretation, then function and principles of EEG are described and at the end is simultaneous EEG-fMRI described. In the second part of the thesis features of each tool from Neural Data Toolbox (NDTb) are described.
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Manifestation of physiological noise in fMRI data
Skoupý, Radim ; Mareček, Radek (referee) ; Lamoš, Martin (advisor)
In this bachelor thesis I deal with the manifestations of physiological noise in fMRI data. The work includes the basic theory of BOLD signal - his character, dealing with the processing of measured data, the possibilities of their treatment, filtration and formation of the resulting statistical parametric maps. The key part is studing possibilities of physiological noise filtering method Retroicor that models physiological noise based on sine and cosine basis functions.
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Influence of the reaction time on neuronal response amplitude after the uncommon stimuli in fMRI images
Klimeš, Filip ; Bartoň, Marek (referee) ; Lamoš, Martin (advisor)
The goal of my bachelor’s thesis is to provide basic idea of the functional magnetic resonance imaging. The theoretical part deals with general principles, methods of measurement and analysis of fMRI data. The partial and also key objective is to design ways of modelling reaction time within the concept of general linear model. The goal of the practical part was to become familiar with SPM toolbox and then to implement designed ways on group data. The implementation was carried out at two levels: preprocessing and analysis of measured data. Preprocessed data were subjected to the first level analysis and second level analysis. Next aim is to evaluate the results of both analysis and thus different approaches to the modelling of reaction time and its influence on neuronal response amplitude after uncommon stimuli in functional magnetic resonance images.
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Hard and soft exudates detection in retinal images
Válková, Hana ; Lamoš, Martin (referee) ; Kolář, Radim (advisor)
The thesis deals with automatic detection of soft and hard exudates in retinal images of the human eye. In its introduction the thesis describes the issue of diabetes in relation to the damage to the retina of the eye. What is described in the first place is diabetic retinopathy, its symptoms and progression of the disease. Another section is devoted to describing DIARETDB1, the freely accessible database which besides other things contains a set of images showing various degrees of disease, evaluation of images from the experts and the evaluation protocol. The next section discusses several methods for automatic detection of hard and soft exudates. The practical part of the bachelor’s thesis is aimed at image pre-processing with respect to the normalization of retinal images, the selected method for adaptive transformation of contrast was implemented. This part also containts description of chosen methology of thresholding, feature extraction based on lesions intensity and its surroundings, use of Ho Kashyap classifier is described, classification of lesions in images is followed. In conclusion realized methods is evaluated.
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Tool for analysis of subject's movements in functional magnetic resonance measurements.
Šejnoha, Radim ; Lamoš, Martin (referee) ; Gajdoš, Martin (advisor)
This diploma thesis deals with an analysis of subject’s movement during measurements with funcional magnetic resonance imaging (fMRI). It focuses on methods of a movement artifacts detection and their removal in fMRI images. Thesis deals with metrics which are used for the movement rate of measured subjects evaluation. Metrics and a correction of movement are implemented into the programme in MATLAB. Comparison of subjects suffering from Parkinson’s disease with a group of healthy control was carried out. Tresholds of individual metrics were suggested and a criterion for the removal of subjects with high movement rate was determined.
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Hemodynamic model in effective brain connectivity analysis using fMRI
Holeček, Tomáš ; Harabiš, Vratislav (referee) ; Lamoš, Martin (advisor)
Modeling of hemodynamic response based on changes of synaptic activity is used for mapping active areas of the brain or functional organization of the brain using functional magnetic resonance imaging. Hemodynamic model is one of the methods for modeling hemodynamic response. Balloon model is the main part of the hemodynamic model. Hemodynamic model is used in the mapping active areas using general linear model and in the effective brain connectivity analysis using dynamic causal modelling. This bachelor´s thesis is focused on description of the hemodynamic model, its parameters and impact of every single parameter of the hemodynamic model on its response.
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MRI image segmantation based on edge detection
Simichanidis, Michail ; Lamoš, Martin (referee) ; Harabiš, Vratislav (advisor)
Cílem této práce je představit základní segmentační techniky používáné v oblasti medicínského zpracování obrazových dat a pomocí 3D prohlížeče schopného zobrazit 3D obrazy implementovat segmentační modul založený na hranové detekci a vyhodnotit výsledky. Navrhovaný prohlížeč je sestavený v prostředi Matlab GUI a je schopen načíst objem 3D snímků představující lidskou hlavu. Navrhovaný segmentační modul je založen na použití hranových detektorů, zejména Cannyho detektoru.
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