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The cancer of liver, which is the leading cause of cancer death, is commonly diagnosed by comparing the changes of gray level of liver tissue in the different phases of the patient's CT images. To aid the doctor in reducing misdiagnosis or missed diagnosis, a fully automatic computer-aided diagnosis (CAD) system is proposed to diagnose hepatocellular carcinoma (HCC) using convolutional neural network (CNN) classifier. The automatic segmentation and classification are two core technologies of the proposed CAD system, which are both realized based on CNN. The segmentation of liver and tumor is implemented by a fully convolutional networks (FCN) based on a fine tuning VGG-16 model with two additional 'skip structures' using a weighted loss function which helps to solve the problem of inaccurate tumor segmentation caused by the inevitably unbalanced training data. HCC classification is implemented by a 9-layer CNN classifier, whose input is a 4-channel image data constructed by combining the segmentation result of FCN with the original CT image. A total of 165 venous phase CT images including 46 diffuse tumors, 43 nodular tumors, and 76 massive tumors are used to evaluate the performance of the proposed CAD system. The classification accuracy of CNN classifier for diffuse, nodular and massive tumors are 98.4%, 99.7% and 98.7% respectively, which are significantly improved in contrast with the traditional feature-based ANN and SVM classifiers. The proposed CAD system, which is unaffected by the difference of preprocessing method and feature type, is proved satisfactory and feasible by the test set.
Content available remote Software OCENS – a tool for outage costs and energy not supply calculation
This paper deals with description of Software OCENS. It is a software solution for Outage costs and Energy not Supply calculation. We describe a structure of software, input data and parameters and possibilities of presentation of results (Energy not supply, Damage function, Interrupted Energy Assessment Rate, Sensitivity analysis, etc.) in this paper. We use this software for reliability analysis in industry, but it can used as a background for distribution networks investment planning, for reconstruction of electrical networks in industrial enterprises.
Artykuł opisuje oprogramowanie OCENS. Oprogramowanie umożliwia wyliczenie kosztów utraty zasilania i niedostarczonej energii elektrycznej. Opisano strukturę programu, dane wejściowe i parametry oraz możliwości prezentacji wyników (niedostarczona energia, funkcja strat, analiza wrażliwości itp). Oprogramowanie zostało wykorzystane do analizy niezawodności w przemyśle, ale może być również użyte do planowania inwestycji w sieciach dystrybucyjnych oraz do rekonstrukcji sieci elektrycznych w zakładach przemysłowych.
Content available remote Bayes sharpening of imprecise information
A complete algorithm is presented for the sharpening of imprecise information, based on the methodology of kernel estimators and the Bayes decision rule, including conditioning factors. The use of the Bayes rule with a nonsymmetrical loss function enables the inclusion of different results of an under- and overestimation of a sharp value (real number), as well as minimizing potential losses. A conditional approach allows to obtain a more precise result thanks to using information entered as the assumed (e.g. current) values of conditioning factors of continuous and/or binary types. The nonparametric methodology of statistical kernel estimators freed the investigated procedure from arbitrary assumptions concerning the forms of distributions characterizing both imprecise information and conditioning random variables. The concept presented here is universal and can be applied in a wide range of tasks in contemporary engineering, economics, and medicine.
Paper presents theoretical fundamentals for process cost analysis as based on the loss functions proposed by Taguchi. The components of the loss function are taken into consideration as well as the cost of 100% quality inspection. The cost of the faulty products (predicted), products that were not accepted by customers, costs of selection and statistical monitoring are also estimated. An example to illustrate the problem has been provided.
W pracy przedstawiono teoretyczne podstawy analizy kosztów zapewniania jakości oparte na zaproponowanej przez Taguchiego funkcji strat. Rozpatrzono składniki kosztów sterowania statystycznego oraz 100% inspekcji wyrobów. Uwzględniono koszty określające prawdopodobną liczbę braków, koszty wyrobów nieakceptowalnych przez konsumentów, koszty selekcji oraz koszty nadzorowania statystycznego. Znaczenie metody zostało zilustrowane przykładem obliczeniowym.
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