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Comparative analysis of selected classifiers in posterior cruciate ligaments computer aided diagnosis

Zarychta P., Badura P., Pietka E.

Bulletin of the Polish Academy of Sciences. Technical Sciences

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2017

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Vol. 65, nr 1

63--70

EN

A study on computer aided diagnosis of posterior cruciate ligaments is presented in this paper. The diagnosis relies on T1-weighted magnetic resonance imaging. During the image analysis stage, the ligament region is automatically detected, localized, and extracted using fuzzy segmentation methods. Eight geometric features are defined for the ligament object. With a clinical reference database containing 107 cases of both healthy and pathological cases, a Fisher linear discriminant is used to select 4 most distinctive features. At the classification stage we employ five different soft computing classifiers to evaluate the feature vector suitability for the computerized ligament diagnosis. Among the classifiers we introduce and specify the particle swarm optimization based Sugeno-type fuzzy inference system and compare its performance to other established classification systems. The classification accuracy metrics: sensitivity, specificity, and Dice index all exceed 90% for each classifier under consideration, indicating high level of the proposed feature vector relevance in the computer aided ligaments diagnosis.

2

Multi-step process in computer assisted diagnosis of posterior cruciate ligaments

Zarychta P.

Biocybernetics and Biomedical Engineering

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2016

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Vol. 36, no. 4

657--669

EN

A multi-step methodology resulting in a three-dimensional visualization and construction of feature vector of posterior cruciate ligament is presented. In the first step the location of the posterior cruciate ligament is established using the fuzzy image concept. The fuzzy image concept is based on the entropy measure of fuzziness extended to two dimensions. In order to reduce the area of analysis, the region of interest including the ligament structures is detected. In this case, the fuzzy C-means algorithm with median modification helping to reduce blurred edges was implemented. After finding the region of interest, the fuzzy connectedness procedure was performed. This procedure permitted to extract the ligament structures. On the basis of the extracted posterior cruciate ligament structures, the three-dimensional visualization of this ligament was built and, with the support of experts' knowledge, an appropriate feature vector was constructed and its values assigned for normal and pathological cases. Correct results were obtained for over 88% of 97 cases.

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Wyposażenie laboratoryjne Katedry Informatyki i Aparatury Medycznej Wydziału Inżynierii Biomedycznej w kontekście postaw i oczekiwań studentów

Zarychta P., Badura P., Piętka E.

Acta Bio-Optica et Informatica Medica. Inżynieria Biomedyczna

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2012

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Vol. 18, nr 2

102-106

PL

Latem 2012 roku mija sześć lat od uruchomienia w Polsce edukacji na kierunku Inżynieria Biomedyczna. Pierwsi absolwenci studiów II stopnia zasilają rynek pracy. Sytuacja ta może sprzyjać formułowaniu pierwszych poważnych wniosków na temat aspektów dydaktycznych prowadzonego procesu. Z drugiej strony, jednostki prowadzące studia mierzą się ciągle z wyzwaniami związanymi z zapewnieniem najwyższej jakości zarówno teoretycznej, jak i praktycznej oferty edukacyjnej. Oferta Wydziału Inżynierii Biomedycznej Politechniki Śląskiej z roku na rok jest coraz bardziej atrakcyjna, m.in. pod względem aparatury, oprogramowania i wyposażenia laboratoriów. Ten aspekt kształcenia – charakterystyka sprzętowa i informatyczna głównych laboratoriów prowadzonych przez Katedrę Informatyki i Aparatury Medycznej – stanowi treść niniejszego artykułu.

EN

Six years ago the faculty of Biomedical Engineering has been introduced in Poland, again. First graduates enter the labor market. It might be, a good opportunity to summarize first educational experiences. On the other hand, it is still a time for intensive development of educational offer. Academic institutions keep challenge to provide the professional studies and improve their quality. The Silesian University of Technology, Faculty of Biomedical Engineering develops not only the merits of education, but also the software and equipment of laboratories. The latter point of view - the high quality equipment and software of main laboratories - is the essence of the paper.

4

Analysis of influence of chemical composition of Al-Si-Cu casting alloy on formation of casting defects

Dobrzański L. A., Krupiński M., Zarychta P., Maniara R.

Journal of Achievements in Materials and Manufacturing Engineering

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2007

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Vol. 21, nr 2

53-56

EN

Purpose: A methodology of the computer-aided determining relationship between chemical composition of aluminium alloy and castings quality was presented in the paper. Design/methodology/approach: To resolve the problem artificial neural networks were used. Classification problems were evaluated by the consideration mainly the values of mistakes and correct answers of networks for test data. On the basis of data analyzed by the neural network, which has the best quality classification of chemical composition of tested material, the concentration of alloying elements range, which have an effect on formation casting defects, were developed to eliminate them in the future. Findings: Combining of all methods making use of chemical composition of aluminium alloy and neural networks will make it possible to achieve a better casting quality. Research limitations/implications: The presented issues may be use, among others, for manufacturers of car subassemblies from light alloys, where meeting the stringent quality requirements ensures the demanded service life of the manufactured products. Originality/value: The correctly specified number of chemical composition of aluminium alloy enables such technological process control where the number of castings defects can be reduced by means of the proper correction of the process.

5

Theory of fuzzy sets in edge location of the posterior cruciate ligament region

Zarychta P., Piętka E., Kiełtyka A., Zarychta-Bargieła A.

Journal of Medical Informatics & Technologies

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2006

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Vol. 10

199--203

EN

An approach to location of a region including the posterior and anterior cruciate ligament in the MR knee images has been developed. The proposed method of the PCL location in T1-weighted MR knee images is based on entropy (or energy) measure of fuzziness and fuzzy C-means (FCM) algorithm. Then, edges of a region of interest containing the ligament are found. The procedure has been tested on clinical T1- and T2- weighted MR knee images resulting in a 3D visualisation.

6

Methodology of analysis of casting defects

Dobrzański L. A., Krupiński M., Sokolowski J. H., Zarychta P., Włodarczyk-Fligier A.

Journal of Achievements in Materials and Manufacturing Engineering

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2006

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Vol. 18, nr 1-2

267--270

EN

Purpose: The goal of this publication is to present the methodology of the automatic supervision and control of the technological process of manufacturing the elements from aluminium alloys and of the methodology of the automatic quality assessment of these elements basing on analysis of images obtained with the X-ray defect detection, employing the artificial intelligence tools. The methodologies developed will make identification and classification of defects possible and the appropriate process control will make it possible to reduce them and to eliminate them - at least in part. Design/methodology/approach: The methodology is presented in the paper, making it possible to determine the types and classes of defects developed during casting the elements from aluminium alloys, making use photos obtained with the flaw detection method with the X-ray radiation. It is very important to prepare the neural network data in the appropriate way, including their standardization, carrying out the proper image analysis and correct selection and calculation of the geometrical coefficients of flaws in the X-ray images. The computer software was developed for this task. Findings: Combining of all methods making use of image analysis, geometrical shape coefficients, and neural networks will make it possible to achieve the better efficiency of class recognition of flaws developed in the material. Practical implications: The presented issues may be essential, among others, for manufacturers of car subassemblies from light alloys, where meeting the stringent quality requirements ensures the demanded service life of the manufactured products. Originality/value: The correctly specified number of products enables such technological process control that the number of castings defects can be reduced by means of the proper correction of the process.