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MR image processing
Mrákava, Petr ; Smékal, Zdeněk (referee) ; Gescheidtová, Eva (advisor)
The subject of this bachelor's thesis is to become familiar with the methods of processing image acquired by techniques of nuclear magnetic resonance. It describes the gradual steps in the digitizing of the signal to the image data. But in the process a disturbing component is almost always created in the image, in particular noise, which causes image devaluation. Therefore, further work is focused mainly on eliminating present disturbing components. For the noise elimination, the widely used wavelet transformation is applied, which is implemented by banks of digital filters. The experimental part of this work deals with design of MR filtering method, optimal filtering parameters setting, decomposition of images into magnetic field map, and subsequent comparison of results obtained.
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Analysis of acoustic and electromagnetic emission signals
Boudný, Petr ; Káňa, Ladislav (referee) ; Sadovský, Petr (advisor)
Master´s thesis is focused to analyse the acoustic and electomagnetic emission signals. These signals generate external power applied on the material. This power put there plastic deformation and create cracks. Spectral analyse show that signals are non-stationary. Wavelet transformation was used to spectral analyse which informate about time-frequence vaules of the signal.
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Wavelet transform based object detector
Mikuš, Ondřej ; Průša, Zdeněk (referee) ; Rajmic, Pavel (advisor)
This thesis deals with applying methods on object detection in image. Separation of objects off the background is often needed during the image processing. It isolates the region of interest that can be worked with. The main purpose of this paper is the explanation of principles of pre-processing and segmentation of image, resulting in object detection using the wavelet transformation. This wavelet transformation is described more in detail, because it is the base of the primary used method. In the practical part of this thesis the main method was implemented to MATLAB environment and tested on set of images. The method was tested for robustness against noise and blur of image. It was compared with commonly used methods, using the edge detectors and thresholding. A simulation program was created for comparison of methods efficiency, including user interface.
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ECG quality estimation
Pospíšil, Jan ; Smíšek, Radovan (referee) ; Smital, Lukáš (advisor)
This bachelor thesis deals with the question of estimation of the quality of the ECG signals, which is a key parameter for determining the diagnosis. The theoretical part deals with the basic knowledge concerning cardiac physiology, electrocardiography and finally the types of interferences that can occur during the measurement. The following practical part will deal with the published methods and the proposal of methods for estimating signal quality and their testing on artificial and real data.
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Person Identification and Verification Using EEG
Žitný, Roland ; Orság, Filip (referee) ; Tinka, Jan (advisor)
The aim of this work was to create a brain-computer interface that reliably identifies and verifies a person using his electroencephalographic signals. Creating a user profile and verifying it is based on processing reactions to his own face, and the face of strangers or acquaintances. Algorithms such as bandpass and noise removal using wavelet transformation are user to filter signals. The classification of reactions is performed using a convolutional neural network or linear discriminant analysis. The average accuracy of the linear discriminant analysis is 66.2 % and of the convolutional neural network is 58.7 %. The maximum achieved accuracy was with linear discriminant analysis and at 93.7 %.
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Filtering methods for MR images processing
Pláněk, Jiří ; Smékal, Zdeněk (referee) ; Gescheidtová, Eva (advisor)
This master´s thesis deals with wavelet transformation and its signal and image noise reduction application method. Significant parameters problems as a wavelet type, a threshold technique selection, a threshold level and a level analysis selection for successful signal and noise image filtering are described. A relation between wavelet transformation and digital bank filter is used by anti-noise and sub-bandwidth filtration. A part of the master´s thesis is focused on nuclear magnetic resonation, where jaw-joint image is processed. Jaw joint image noise reduction filtration methods are used in experimental part of the master´s thesis. Consequently, filtration methods improve a jaw joint image quality, which helps a doctor with patient health state condition. Different types of wavelets were tested and in different application methods order. Filtration methods results were visually compared; therefore any conclusion comparison has subjective matter. Accordingly, only doctor is able to resolve which filtration method is convenient to use to determine patient health state.
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Fetal ECG records analysis
Hláčiková, Michaela ; Smíšek, Radovan (referee) ; Smital, Lukáš (advisor)
This thesis is focused on the analysis of fetal ECG records measured by indirect method from mother´s abdomen. The thesis consists of the theoretical part is focused on fetal, heart development and description of fetal ECG signal. This thesis also offers an overview of fECG signal processing methods used nowadays. The practical part of the thesis deals with the implementation of algorithms based on wavelet transformation and Least Mean Square LMS method in Matlab programming environment. The final part of the thesis consists of the analysis of achieved results.
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Wavelet Wiener filter of ECG signals
Sedláčková, Eva ; Odstrčilík, Jan (referee) ; Smital, Lukáš (advisor)
The aim of this work is introduction with method of filtering the ECG signals using wavelet transformation and use of this method for filtering of signal disturbed with myopotencials. The work deals with general properties and with genesis of ECG signals and describes ECG curve. Next part of work is focused on wavelet transformation, types of wavelet transformation and different methods calculation thresholds and thresholding. Design part of work is focused on design Wiener filter for remove myopotencials from ECG signals and finding optimal parameters of this filter using optimization algorithm. For optimization is used simplex method. Discovered optimal parameters are assessed on CSE and MIT-BIH Arrhythmia database and compared with results of other authors.
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Study of Biological Material Attributes by using Image Analysis Methods
Jeřábková, Petra ; Mikula, Milan (referee) ; Zmeškal, Oldřich (advisor)
Within the dissertation thesis “Study of Biological Material Attributes by Using Image Analysis Methods”, attention is focused on monitoring of the application of image analysis methods, mostly a fractal analysis, in studying the properties of various yeast species. The thesis includes determining the number of yeast cells and vegetative propagation of yeast using fractal parameters – fractal measure D and fractal dimension K. Attention is also paid not only to the application of the existing image analysis methods, but also to their renovation. The obtained images were evaluated using the box counting method specified by implementation of wavelet transformation. To monitor yeast cells for a longer time, it was first necessary to prepare a suitable microscopic preparation. To distinguish live and dead cells, the following fluorescent dyes were used: acridine orange, fluorescein diacetate, FUN-1, and Calcofluor White M2R. The images of yeast cells were recorded using a still camera or a CCD camera and microscope. Clips of the same size were obtained from the acquired digital photographs and processed by the HarFA program developed at the Faculty of Chemistry, Brno University of Technology. On the results it is possible to see a change in the fractal dimension depending on time, i.e. on the change of a budding cell structure, or to determine the number and radius of yeast cells upon predefined conditions.
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K-complex detection in sleep EEG
Bjelová, Martina ; Mézl, Martin (referee) ; Králík, Martin (advisor)
This paper addresses detecting of K-complexes in sleeping EEG records. Polysomnography is the method, which is used for diagnostic and following therapy of many sleep disorders. For identifnging of sleep stages it is fundamental to know graphoelements, in which they are situate. K-complex is important indicator of second sleep stange and hence is essencial to know to detect this pattern. In this paper we focus on design and implementation of more algorithms for detection of these patterns with various characteristics. Among the proposed methods, the wavelet transform method was best evaluated. Performance of this detection reached values the average senzitivity 63,83 % and average positive predictive value 44,07 %.
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