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Wyświetlanie 1-7 z 7
Tytuł:
Accumulation methods in the processing of difficult images
Autorzy:
Chmielewski, L.J.
Powiązania:
https://bibliotekanauki.pl/articles/332880.pdf
Data publikacji:
2008
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
analiza obrazu
gromadzenie dowodów
metody rozmyte
histogram
transformata Hough'a
image analysis
evidence accumulation
fuzzy methods
Hough transform
Opis:
The accumulation methods emerged in close relation to the development of the Hough transform (HT). The application of some far reaching generalizations of the HT will be presented. The accumulation principle will be taken as a starting point: Accumulate the relevant data from possibly many, possibly competent sources. This principle is known and widely used in image processing, mainly in the methods related to the HT. The principle is in opposition to the tendency to compress the image data as early in the processing as possible. The accumulation principle is a recommendation to utilize the redundancy in the image data in a specific way and should be applied when the images are difficult to process due to their low quality. The basic data structure is the fuzzy histogram, which is in fact an experimentally obtained approximation of the probability density of the phenomenon of interest. The concepts of a degree of fuzzification and the weakly and strongly fuzzified histograms will be introduced. A number of solutions found with the use of the accumulation principle will be presented. In the examples and tests, biomedical images will be used. Such images are challenging because the objects imaged are irregular and the quality of the images is usually limited in a natural way by the imaging modalities used. The accumulation methods are a good solution to the problem of analysis of such images.
Źródło:
Journal of Medical Informatics & Technologies; 2008, 12; 11-21
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fuzzy clustering based methods for nystagmus movements detection in electronystagmography signal
Autorzy:
Czabański, R.
Pander, T.
Horoba, K.
Przybyła, T.
Powiązania:
https://bibliotekanauki.pl/articles/332952.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
saccade detection
optokinetic nystagmus
fuzzy clustering
detekcja ruchów sakadowych
oczopląs optokinetyczny
grupowanie rozmyte
sygnał ENG
Opis:
The analysis of optokinetic nystagmus (OKN) provides valuable information about the condition of human vision system. One of the phenomena that is used in the medical diagnosis is optokinetic nystagmus. Nystagmus are voluntary or involuntarily eye movements being a response to a stimuli which activate the optokinetic systems. The electronystagmography (ENG) signal corresponding to the nystagmus has a form of a saw tooth waveform with fast components related to saccades. The accurate detection of the saccades in the ENG signal is the base for the further estimation of the nystagmus characteristic. The proposed algorithm is based on the proper filtering of the ENG signal providing a waveform with amplitude peaks corresponding the fast eyes rotation. The correct recognition of the local maxima of the signal is obtained by the means of fuzzy c-means clustering (FCM). The paper presents three variants of saccades detection algorithm based on the FCM. The performance of the procedures was investigated using the artificial as well as the real optokinetic nystagmus cycles. The proposed method provides high detection sensitivity and allows for the automatic and precise determination of the saccades location in the preprocessed ENG signal.
Źródło:
Journal of Medical Informatics & Technologies; 2013, 22; 277-283
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Registration and fuzzy segmentation modules for SemiVis framework
Autorzy:
Denkowski, M.
Chlebiej, M.
Mikołajczak, P.
Powiązania:
https://bibliotekanauki.pl/articles/333861.pdf
Data publikacji:
2005
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
struktura przetwarzania obrazów
rejestracja
rozmyta metoda segmentacji
wizualizacja
przetwarzanie obrazu rezonansu magnetycznego mózgu
image processing framework
registration
fuzzy segmentation methods
visualization
MR brain image processing
Opis:
This paper presents the cross-platform framework for image processing with a focus on medical imaging. It allows a fast addition and testing of new algorithms using a modular structure. New modules can be created by using a platform-independent The C++ class library can be easily integrated with a whole system by a plug-in mechanisms. Together with the system core in the framework medical image processing modules are included. The plug-in mechanism allows to create a processing pipelines of this modules to achieve sophisticated processing functions such as registration or segmentation.
Źródło:
Journal of Medical Informatics & Technologies; 2005, 9; 65-74
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Granular representation of biomedical signals using numerical differentiation methods
Autorzy:
Momot, M.
Momot, A.
Gacek, A.
Powiązania:
https://bibliotekanauki.pl/articles/332925.pdf
Data publikacji:
2010
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
grupowanie
liczby rozmyte
granulacja informacji
interpolacja
kryterium odbudowy
clustering
fuzzy number
information granulation
interpolation
reconstruction criterion
Opis:
This work presents the general idea of granular description of temporal signal, particularly biomedical signal sampled with constant frequency. The main idea of presented method is based on using triangular fuzzy numbers as information granules in temporal and amplitude spaces. The amplitude space contains values of first few derivatives of underlying signal. The construction of data granules is performed using the optimization method according to some objective function, which balances the high coverage ability and the low support of fuzzy numbers. The granules (descriptors) undergo the clustering process, namely fuzzy c-means. The centroids of created clusters form a granular vocabulary and the quality of description is quantitatively assessed by reconstruction criterion. There are presented results of experiments with the electrocardiographic signal, digitally sampled and stored in MIT-BIH database. The method of numerical differentiation of function based on finite set of its values is employed, which incorporates polynomial interpolation. The paper presents results of numerical experiments which show the impact of method parameters, such as temporal window length, degree of polynomial, fuzzification parameter, on the reconstruction ability of presented method.
Źródło:
Journal of Medical Informatics & Technologies; 2010, 16; 43-49
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Improving the quality of the fetal state assessment with epsilon-insensitive learning methods
Autorzy:
Czabański, R.
Wróbel, J.
Jeżewski, J.
Łęski, J.
Powiązania:
https://bibliotekanauki.pl/articles/333468.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
fetal monitoring
fuzzy implication
epsilon-insensitive learning
monitorowanie płodu
implikacja rozmyta
Opis:
Recording and analysis of fetal heart rate (FHR) signal is nowadays the primary method for the biophysical assessment of the fetal state. Since the correct interpretation of crucial FHR characteristics is difficult, methods of automated quantitative signal evaluation are still the subject of the research studies. In the following paper we investigated the possibility of improvement of the fetal state evaluation on the basis of the epsilon-insensitive learning (eIL). We examined two eIL procedures integrated with fuzzy clustering algorithms as well as different methods of logical interpretation of the fuzzy conditional statements. The quality of the FHR signal classification was evaluated using the data collected with the computerized fetal surveillance system. The learning performance was measured with the number of correct classification (CC) and overall quality index (QI) defined as a geometric mean of sensitivity and specificity. The obtained results (CC = 88 % and QI = 87 %) show a high efficiency of the fetal state assessment using the epsilon-insensitive learning based methods.
Źródło:
Journal of Medical Informatics & Technologies; 2014, 23; 19-26
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Using artificial immune and case-based reasoning methods in classification of treatment effectiveness
Autorzy:
Badura, D.
Ferdynus, D.
Powiązania:
https://bibliotekanauki.pl/articles/333874.pdf
Data publikacji:
2007
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
wnioskowanie bazujące na przykładach
sztuczne systemy immunologiczne
sieci neuronowe rozmyte
case-based reasoning
artificial immune system
fuzzy neural nets
Opis:
The article concerns the analysis of classification of medical data by use of selected method of artificial intelligence: case-based reasoning. The subject of the research is the assessment of effective treatment, being one of the most important medical problems. The basis work of the assessment system should be one of the classification methods. The aim of the attempted research is to study which of the enumerated method will be able to group data containing incomplete information in the best way. The classified data are descended from the patients with nephroblastoma and patients with backbone pain. The final aim of the research is to work out the functioning method of the learning system, assisting the doctor with making a decision during working out on patient's treatment therapy, and making analyses of the treatment effectiveness. On the basis of the medical tests, the system will classify the data assigning them to the appropriate therapy groups. Moreover, in the system will be used artificial immunology as the method of generalizing or extrapolating of the gathering and considering so far cases.
Źródło:
Journal of Medical Informatics & Technologies; 2007, 11; 221-226
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Segmentation and visualisation MR images of the human brain
Autorzy:
Denkowski, M.
Chlebiej, M.
Mikołajczak, P.
Powiązania:
https://bibliotekanauki.pl/articles/333556.pdf
Data publikacji:
2004
Wydawca:
Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:
metody segmentacji
wizualizacja
przetwarzanie obrazu rezonansu magnetycznego mózgu
logika rozmyta
powierzchnia
interpretacja objętościowa
segmentation methods
visualization
MR brain image processing
thresholding
fuzzy logic
surface
volumetric rendering
Opis:
Segmentation and visualisation of anatomical regions of the brain are fundamental problems in medical image analysis. In this paper, we present a fuzzy-logic segmentation system that is capable of segmenting magnetic resonance (MR) images of a human brain. The presented method consists of two main stages: histogram thresholding and pixel classification using a rule-based fuzzy logic inference. After the segmentation is complete, attributes of different tissue classes may be determined (e.g., volumes), or the classes may be visualised as spatial objects. The implemented system provides many advanced 3D imaging tools.
Źródło:
Journal of Medical Informatics & Technologies; 2004, 7; MIP59-68
1642-6037
Pojawia się w:
Journal of Medical Informatics & Technologies
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-7 z 7

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