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Measurement of biological signals with Bipack system
Brudík, Vladislav ; Hlaváček, Antonín (referee) ; Valla, Martin (advisor)
This bachelor's thesis deals with questions of sensing electrical brain activity by electroencephalograph, and the data processing. Theoretical part is focused on brain, it's anatomy and functions. It also deals with biological signals, types of curves and systems used for measuring EEG curves. For purpose of signal processing it's been designed application software with GUI interface. This application software displays EEG curves, significant frequency ranges, frequency spectrum and filtered areas of characteristic waves.
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Five in a Row
Vrtílek, Michal ; Zbořil, František (referee) ; Rozman, Jaroslav (advisor)
This Bachelor's Thesis describes the desing and implementation of artificial intelligence for the board game Five in a row. The main goal of this thesis is to create an application able to communicate with the Manager For Board Games with the use of network communication and being able to play the board game Five in a row on a suitable level. This work contains theoretical parts about the history and rules of Five in a row and it's variations, about the possibilities of use of artificial intelligence in this game and about the structure of aplications used for playing it. It's concern is about the actual desing and implementation of said application, including it's controls. In the end I evaluate achieved results and propose additional directions for the program development.
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Influence of PbO and CdO nanoparticles on particular physiological functions in mouse.
Svozilová, Eva ; Vrlíková, Lucie (referee) ; Večeřa, Zbyněk (advisor)
The aim of this bachelor´s thesis is to assess the long-term effects of inhalation of nanoparticles of lead oxide and cadmium oxide on the weight of selected organs of experimental white mice. The selected organs (spleen, liver, kidney, lungs, brain) were successively collected during a period of thirteen weeks. The effect of inhalation of both metal oxides was statistically evaluated. In both study groups of the experiment (PbO and CdO), the relation between organs weight and the length of inhalation and the relation between organs weight and inhalation of differing metal concentrations were evaluated, and results both of the study groups were compared to each other.
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Automatic 3D segmentation of brain images
Bafrnec, Matúš ; Dorazil, Jan (referee) ; Kolařík, Martin (advisor)
This bachelor thesis describes the design and implementation of the system for automatic 3D segmentation of a brain based on convolutional neural networks. The first part is dedicated to a brief history of neural networks and a theoretical description of the functionality of convolutional neural networks. It represents a fast introduction to the problematics and provides theoretical basics needed for the understanding and creation of the system. Individual layers of the neural network and principles of their functionality and mutual relations are also described in this part. The second part of the thesis is about problem analysis, designing of a solution and a comparison between neural networks and other solutions. The result of a magnetic resonance imaging of the head is a series of black-and-white images representing a 3D scan. The task is to tag a brain and to remove unnecessary information in the form of surrounding tissues. The final image of the brain can be utilized in a volumetry or during a diagnostic of neurodegenerative diseases. The advantage of neural networks in comparison with deterministic systems is their flexibility. They allow an adaptation to other segmentation problems just by changing the training dataset, without a need of changes in the architecture. One of the systems performing fully automatic 3D segmentation is called U-Net – its name comes from the similarity of the architecture with the letter U. Three real solutions, the first implementation of U-Net, extended U-Net and recurrent U-Net were presented. The first version of U-Net has been very memory-demanding, it required a training on a processor instead of a graphic card and has not allowed data processing in full resolution. The extended U-Net has resolved these problems by loading data in overlaying series of three images. In addition to the possibility of a training on a graphic card with related decrease in learning time, the accuracy was increased by adding interconnections to the internal architecture of the network. The last version, recurrent U-Net, aims for the optimization of extended U-Net based on the reusage of existing levels. This brings a decrease in a time and resource difficulty. The number of parameters of the network was lowered to less than 20%, without any increase in case of further level addition. This network is one of first recurrent networks used on the problem of 3D segmentation and provides a foundation to further research. The last part focuses on the evaluation of results and the comparison of accuracy, speed and requirements between particular networks. The accuracy of human and machine segmentation is also compared. The extended and recurrent U-Net have surpassed their human opponent, which in real case could save a lot of doctors time and prevent human mistakes. The result of this work is a theoretical basis providing an introduction to the problematics of convolutional neural networks and segmentation, fully working systems for automatic 3D segmentation and the foundation for further research in the field of recurrent networks.
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Segmentation of the basic parts of human brain in MR data
Klásek, Pavel ; Jiřík, Radovan (referee) ; Malínský, Miloš (advisor)
This work describes segmentation methods used in image data processing, from which there are selected and implemented suitable methods for solving the assignment of segmentation parts of human brain – region growing and watershed algorithm. Segmentation techniques are realized on real data sources. Final segmentation results are presented, compared and evaluated accordig to the advanced software FreeSurfer segmentation results. In addition there is a list of available software that can be applied for the purpose of neurological image segmentation.
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Determination of lead in lung and brain samples of experimental mice after the inhalation of nanoparticles
Demydenko, Yana ; Zlámalová Gargošová, Helena (referee) ; Vašinová Galiová, Michaela (advisor)
Lead is a heavy toxic metal whose nanoparticles are present in the air due to combustion processes. Data on the safe concentration of lead nanoparticles for human health have not been sufficiently investigated. Previous studies in experimental mice have shown that inhalation of lead nanoparticles first damages lungs and kidneys, then liver, spleen and brain. With prolonged exposure, lead accumulates in the teeth and bones. This bachelor thesis is focused on monitoring of the lead content in lung and brain samples of experimental mice after different periods of nanoparticle inhalation. The aim of this bachelor thesis was to develop an analytical method for the determination of lead in biological samples using atomic absorption spectrometry with electrothermal atomization (ET-AAS). In this work, a decomposition method for mineralization of the biological matrix in a microwave mineralizer was proposed, and a procedure for the determination of lead using ET-AAS was further developed. The determination of lead at 217 nm using the NH4H2PO4/Mg(NO3)2 matrix modifier was verified by analysis of certified reference materials. Analysis of organ samples from experimental mice confirmed the detoxification mechanism in exposed individuals with a dependence on the time since the end of inhalation of lead nanoparticles.
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Typing Using Brain Signals
Wagner, Lukáš ; Malinka, Kamil (referee) ; Tinka, Jan (advisor)
This bachelor thesis focusses on the implementation of a brain-computer interface, programmed in Python language, that would enable to communicate using EEG. The thesis investigates and evaluates existing brain-computer interface technologies for this purpose. The thesis also explores the use of machine learning applied to the technology, in particular neural networks, which have proven to be one of the most accurate methods of EEG signal processing. Following that, 3 different systems are proposed and implemented, each on different paradigm of visually evoking EEG potential changes. These systems were tested with different signal classification approaches. Unfortunately, none of the systems proved to be useful in communication.
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Segmentation and morphological analysis of mouse embryo choroid plexus
Parobková, Viktória ; Jakubíček, Roman (referee) ; Chmelík, Jiří (advisor)
Choroidálny plexus je regulovanou bránou medzi krvou a mozgovomiechovým mokom a má niekoľko funkcií spojených s nervovým systémom. Mnohé funkcie sú však stále neznáme, čo je spôsobené krehkosťou, umiestnením a tvarom plexu. Preto sa na prístup k tejto kľúčovej súčasti mozgu, ktorá sa nachádza v komorách, používajú neinvazívne techniky. Okrem toho existuje súvislosť medzi jeho tvarom a patologickými stavmi mozgu. Cieľom tohto projektu bolo extrahovať ChP 4. komory implementáciou segmentačných metód a následnou morfologickou analýzou s cieľom odhaliť zákonitosti medzi tvarom a ochorením.
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Computer Games and the Human Brain
Hanuš, Marek ; Šedrlová, Magdalena (referee) ; Ellederová, Eva (advisor)
Tato bakalářská práce se zabývá problematikou počítačových her a jejich vlivu na lidský mozek. Cílem první kapitoly je popsat základní vlastnostmi lidského mozku a jeho schopnosti, které developeři počítačových her využívají při vytváření her pro jejich cílovou skupinu zákazníků. Druhá kapitola se zaměřuje na lidské emoce a projevy, které developerům pomáhají, aby mohli vyhovět všem potencionálním uživatelům. Dále tato kapitola popisuje, jak mohou developeři prostřednictvím různých herních aspektů, jakými jsou hudba, narativ, grafický design a herní mód, v člověku evokovat určité emoce a donutit je podvědomě vnímat atmosféru hry. V práci je také popsán vliv těchto aspektů na lidské chování. Poslední kapitola teoretické části práce se zabývá závislostí na hrách a s tím spojenou problematikou. Praktická část práce se věnuje dotazníkovému průzkumu, jehož účelem bylo potvrdit nebo vyvrátit tvrzení v teoretické části. Dále poukazuje na genderové rozdíly v průmyslu počítačových her a ukazuje preference respondentů, které by mohly developerům umožnit zdokonalit kvalitu počítačových her.
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The influence of deep brain stimulation on the brain connectivity
Horváthová, Ľubica ; Výtvarová, Eva (referee) ; Klimeš, Petr (advisor)
Hĺbková mozgová stimulácia (DBS) predstavuje účinnú liečbu pre pacientov s Parkinsonovou chorobou (PD) alebo farmakorezistentnou epilepsiou. Avšak mechanizmy, ktorými znižuje počet záchvatov a zlepšuje pohyb, zostávajú ešte do značnej miery neznáme. Pre lepšie pochopenie a určenie, v ktorých frekvenčných pásmach je zmena najdôležitejšia, boli urobené porovnania medzi vypnutou a zapnutou DBS pomocou korelačnej metódy a indexu fázového posunu. Jedenásť pacientov s PD a naimplantovanými neurostimulátormi z firiem Medtronic a St.Jude Medical bolo predmetom nahraných dát použitých v tejto práci. Výsledky dokazujú, že zmena konektivity počas DBS nastane a zároveň, že najviac ovplyvňuje najvyššie frekvencie ako beta, nízka gama a vysoká gama. Zmeny v týchto frekvenciách, zodpovedné za motorickú aktivitu, sústredenie a spracovanie informácií, sú v súlade s klinickou teóriou o PD. Počas tejto choroby je patologická beta aktivita hypersynchronizovaná a gama aktivita je znížená práve v motorických oblastiach. Ak sa gama aktivita počas zapnutej stimulácie zvyšuje, fyziologický stav pacientov sa čiastočne znovuobnovuje a tým zlepšuje ich hybnosť. Metódy a výsledky tejto práce budú použité pre ďalší výskum pacientov s PD a epilepsiou.
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