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Wavelet Based Filtering of Electrocardiograms
Smital, Lukáš ; Smékal, Zdeněk (referee) ; Halámek, Josef (referee) ; Kozumplík, Jiří (advisor)
This dissertation deals with possibilities of using wavelet transforms for elimination of broadband muscle noise in ECG signals. In this work, the characteristics of ECG signals and particularly the most frequently occurring type of interference are discussed firstly. The theory of wavelet transforms is also introduced and followed by design of the simple wavelet filter and the more sophisticated version with wiener filtering of wavelet coefficients. Next part is devoted to the design of our filter, which is based on wavelet wiener filtering and is complemented by algorithms that ensure full adaptability of its parameters when the properties of the input signal are changing. Suitable parameters of the proposed system are searched automatically and the algorithm is tested on the complete standard electrocardiograms database CSE, where it achieves significantly better results than other published methods.
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Retinal image processing using wavelet transform
Portyš, Jakub ; Kolář, Radim (referee) ; Taševský, Pavel (advisor)
Work is focused on usage wavelet transform in diagnostic of retinae illness. Wavelet transform enables decomposition of eye background pictures. With the following segmentation by force of thresholding it leads to lucidity of picture and simpler diagnostics of morphological and anatomical changes. Part of work is also familiarization with wavelet transform and mother's wavelet family. Marginally is in work analysed picture segmentation according to RGB coloured model, picture filtration and thresholding. In opening chapters are mentioned essential piece of knowledge from anatomy, physiology and pathology.
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Methods of noise suppression for speech recognition systems
Moldříková, Zuzana ; Smital, Lukáš (referee) ; Odstrčilík, Jan (advisor)
This diploma thesis deals with methods of noise suppression for speech recognition systems. In theoretical part are discussed basic terms of this topic and also methods for noise suppression. These are spectral subtraction, Wiener filtering, RASTA, mapping of spectrogram or algorithms based on noise estimation. In second part types of noise are analyzed, there is proposal and implementation of spectral subtraction method of noise suppression for speech recognition system. Also extensive testing of spectral subtractive algorithms in comparison with Wiener filter is conducted. Assessment of this testing is done with defined metrics, successfulness of recognition, recognition system score and signal to noise ratio.
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Wavelet Wiener filter of ECG signals
Janů, Joshua ; Kozumplík, Jiří (referee) ; Smital, Lukáš (advisor)
The thesis focuses on the use of wavelet wiener filtration to remove muscular interference from ECG signals. As part of it, a filter has been implemented in the MATLAB programming environment. The main part of the thesis deals with the optimization of numerical parameters of the proposed filter. The results of the filtration are compared with the results reported by other authors.
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Suppresion of distortion in iris images
Jalůvková, Lenka ; Štohanzlová, Petra (referee) ; Kolář, Radim (advisor)
This master`s thesis is focused on a suppression of a distorsion in iris images. The aim of this work is to study and describe existing degradation methods (1D motion blur, uniform 2D motion blur, Gaussian blur, atmospheric turbulence blur, and out of focus blur). Furthermore, these methods are implemented and tested on a set of images. Then, we designed methods for suppression of these distorsions - inverse filtration, Wiener filtration and iterative deconvolution. All of these methods were tested and evaluated. Based on the experimental results, we can conclude that the Wiener-filter restoration is the most accurate approach from our test set. It achieves the best results in both normal and iterative mode.
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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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Wavelet Filtering of ECG Signals
Handl, Marek ; Smital, Lukáš (referee) ; Kozumplík, Jiří (advisor)
The work deals with the wavelet transformation, focusing on wavelet transforms with discrete time (DTWT). The practical part is focused on the implementation of redundant packet DTWT and its use in the filtration of ECG signals. The main part of the work is to design wiener filter that uses redundant packet DTWT, designed to eliminate interference myopotentials of ECG signals. The actual solution is implemented in Matlab. Testing is performed on the library CSE using noise model myopotentials used to noising original signals. For optimum parameters designed filter is used the genetic algorithm (GA). The work is carried out comparing the proposed filter redundant packet DTWT a variant of redundant dyadic DTWT.
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Speckle noise suppression methods in ultrasound images
Teplý, Lukáš ; Harabiš, Vratislav (referee) ; Mézl, Martin (advisor)
Ultrasound investigation is one of meaningful imaging at present. Advantages of ultrasound are, that it hasn´t side effects as a rtg radiation and it is noninvasive. Ultrasound diagnostic is exploited in all branch of medicine (urology, cardiology, orthopeadist, gynecology etc.) to display organs, tissues and cavities of the human body. We use display in 2D, 3D and most modern display in 4D. We can encounter with many kinds of artifact. Artifacts are described more closely at 3rd chapter. Speckle noise deteriorates informative yiled of ultrasound picture. We try to remove speckle noise by simpler methods or more complex methods of filtration. These methods are described at 5th chapter. Programme for speckle filtering from pictures is part of this master´s thesis.
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Restoration of optical coherence tomography image data
Smékal, Ondřej ; Odstrčilík, Jan (referee) ; Jan, Jiří (advisor)
Restoration of image data has become an essential part of the processing of medical images obtained by any system. The same applies in the case of optical coherence tomography. The aim of this work is to study the first restoration methods. Second, the description of the data representation from optical coherence tomography and subsequent discussions that restoration methods based on deconvolution would potentially find application in processing of Optical coherence tomography. Finally, the third to create a program solution of the OCT data restoration process in MATLAB environment and followed by discussion of effectiveness of the presented solutions.
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Muscle Noise Filtering in ECG Signal
Novotný, J.
This work deals with muscle noise filtering in ECG signals using wiener filtration and optimization of Wiener filter numerical parameters. The optimization was performed by using the exhaustive search method, which belongs to the brute force methods and seeks the global solution. The Criterial function in the optimization process was the average SNR of filtered signals. The testing was performed on 20 random signals from the CSE database. The testing has shown that the greatest difference between the input SNR and the average output SNR was at the minimum input SNR.
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