National Repository of Grey Literature 138 records found  beginprevious128 - 137next  jump to record: Search took 0.01 seconds. 
Machine learning for analysis of MR images of brain
Král, Jakub ; Říha, Ivo (referee) ; Provazník, Ivo (advisor)
The thesis is focused on methods of machine learning used for recognising the first stage of schizophrenia in images from nuclear-magnetic resonance. The introduction of this paper is focused primarily on physical principles. Further in this work, the attention is given to registration methods, reduction of data set and machine learning. In the classification part, simmilarity rates, support vectors´ method, K-nearest neighbour classification and K-means are described. The last stage of theoretical part is focused on evaluation of the clasification. In practical part the results of reduction data set by methods PCA, CRLS-PCA and subjects PCA are described. Furthermore, the practical part is focused on pattern recognition by methods K-NN, K-means and test K-NN method on real data. Abnormalities which are recognised by some classification methods can distinguish patients with schizophrenia from healthy controls.
Neuroinformatics and sharing data from medical imaging systems
Klimek, Martin ; Kubásek, Miroslav (referee) ; Provazník, Ivo (advisor)
The presented master's thesis deals with the issue of storing and sharing data from medical imaging systems. This thesis, inter alia, consists of organizational and informatics aspects of medical imaging systems data in multicentric studies containing MRI brain images. This thesis also includes technical design of a web-based application for image data sharing including a web interface suitable for manipulation with the image data stored in a database.
Monitoring Trends of Electrical Activity of the Heart Using Time-Frequency Decomposition
Čáp, Martin ; Kozumplík, Jiří (referee) ; Provazník, Ivo (advisor)
Work is aimed at the time-frequency decomposition of a signal application for monitoring the EKG trend progression. Goal is to create algorithm which would watch changes in the ST segment in EKG recording and its realization in the Matlab program. Analyzed is substance of the origin of EKG and its measuring. For trend calculations after reading the signal is necessary to preprocess the signal, it consists of filtration and detection of necessary points of EKG signal. For taking apart, also filtration and measuring the signal is used wavelet transformation. Source of the data is biomedicine database Physionet. As an outcome of the algorithm are drawn ST segment trends for three recordings from three different patients and its comparison with reference method of ST qualification. For qualification of the heart stability, as a system, where designed methods watching differences in position of the maximal value in two-zone spectrum and the Poincare mapping method. Realized method is attached to this thesis.
A Wavelet-Based QRS-Complex Detection
Kocian, Ondřej ; Provazník, Ivo (referee) ; Kozumplík, Jiří (advisor)
This project investigates methods of construction the wavelet-based QRS-complex detector. QRS-complex detection is very important, because it helps automatically calculate heart rate and in some cases it is used for compression ECG signal. The design of QRS detector can be made with many methods, in this project were mentioned and consequently tested only a few variants. The principle of designed detector used a wavelet-based decomposition of the original ECG signal to several frequency-coded bands. These bands are consequently transformed to absolute values and with the help of the threshold value are marked positions of assumed QRS complexes. Then are these assumed positions from all bands compared between themselves. If the position is confirmed at least at one nearby band, then is this position marked as true QRS complex. To increase efficiency of designed detector, two modifications were additionally mentioned. The first one, using the envelope of the signal, had rather negative effect on detectors efficiency. The second modification, using combined signal from three pseudoorthogonal leads, had reversely very good effect on detectors efficiency. In the end, the designed detector and all its modifications were tested on signals from CSE library (exactly on leads II, V2 and V6).
Advanced Data Mining in Cardiology
Mézl, Martin ; Provazník, Ivo (referee) ; Sekora, Jiří (advisor)
The aim of this master´s thesis is to analyse and search unusual dependencies in database of patients from Internal Cardiology Clinic Faculty Hospital Brno. The part of the work is theoretical overview of common data mining methods used in medicine, especially decision trees, naive Bayesian classifier, artificial neural networks and association rules. Looking for unusual dependencies between atributes is realized by association rules and naive Bayesian classifier. The output of this work is a complex system for Knowledge discovery in databases process for any data set. This work was realized with collaboration of Internal Cardiology Clinic Faculty Hospital Brno. All programs were made in Matlab 7.0.1.
Scoring Processing System for Protein Identification in Tandem Mass Spectrometry
Valla, Martin ; Svobodová-Vařeková, Radka (referee) ; Provazník, Ivo (advisor)
The goal of my diploma thesis was finding a suitable method for unifying score values from various protein identification search tools in MS/MS mass spectrometry into one single score value. Data coming from the output of mass spectrometer are processed in two independent search tools Mascot and X!Tandem. These were selected especially for their wide usage in proteomic labs. Both results are evaluated through newly designed function and unified by single valued score clearly identifying found proteins. Newly designed scoring value is called Matascore and function producing this score was implemented in MATLAB. Function and its results were successfully tested by real data available in public databases on the Internet.
Adaptive Filtering of Biological Signals
Šmíd, Karel ; Kozumplík, Jiří (referee) ; Provazník, Ivo (advisor)
Objective of this diploma work was to study methods of adaptive filtering and their use in suppression of noise in biological signals. Adaptive filtering represents effective means of suppression of parasitic nonstationary disturbances in a useful signal. The task was to design various types of adaptive filters and implement an adaptation algorithm in Matlab programming environment. It namely included suppression of powerline noise at 50 Hz and 100 Hz in ECG signals with minimization useful components disturbing. The realized filters were verified on real ECH signals and their efficiency was evaluated.
Analysis of Heart Rate Variability
Škrtel, Karol ; Kolářová, Jana (referee) ; Provazník, Ivo (advisor)
The project describes the methods useful for observe changes of heart rate in ECG signal. Heart rate variability become (HRV) the conventionally accepted term to describe variations of NN intervals between consecutive heart beats and generally it is function of instantaneous heart rate or NN interval on time. HRV may be evaluated by time domain or frequency domain measures. In Matlab was developed algorithm, realized like function, which counts HRV parameters from ECG signal series. Analysis in time domain adverts to high correlation between statistic and geometric parameters and similarly with signal HRV. Results of frequency domain analysis shows similarity of power spectral density, which was calculated by two different ways (from interpolated and no interpolated signal HRV). Functionality of developed algorithm was verified on each signal. Project results have signification in progress of analysis ECG signal methods with a view to observe pathological changes in heart rate.
Detection and filtering of ECG signals
Princ, Martin ; Kozumplík, Jiří (referee) ; Provazník, Ivo (advisor)
The aim of this thesis is to provide insight into certain elementary methods/ways of electrocardiographical signals filtration. Also, the thesis aims to introduce different techniques of detecting the EKG signal waves. The first part of the work analyses the theory of heart, electrical processes in heart, and the EKG signals systems. Further, the elementary methods of filtration and QRS detection are introduced.In the second part, the thesis analyses the BIOPAC student Lab system and presents simple methods of measuring the static EKG. The measure data results are then processed using the MATLAB program, and they are further used to demonstrate and practice the elementary methods of EKG filtration and QRS complex detection. Operation detectors QRS test on database EKG signal.
Electromyography, measurement of muscle electric activity
Kořínek, Peter ; Provazník, Ivo (referee) ; Kolářová, Jana (advisor)
The task of this thesis was to become acquainted with the issue of measuring of muscle electric activity.In the theoretical part we became familiar with the computer measuringsystem BIOPAC and its options to measure monitored magnitudes. This continue with practical part, in which we watch the problematic according to a theory in a group of people. We learned data with BIOPAC according to protocol of the result of physicaleffort influence on EMG. In the end the results were statistically analysed. The data as a product offallowing research were verified by hypothesis. In thelast step, the data are presented in graphical user interface development environment. After loading of the EMG of measured person, the process are displayed-without, with and after the power with onus. It is possible to choose from different analyses.

National Repository of Grey Literature : 138 records found   beginprevious128 - 137next  jump to record:
Interested in being notified about new results for this query?
Subscribe to the RSS feed.