Перегляд за автором "Ryazantsev, O."

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  • Зображення мініатюри
    Публікація
    General Ideology of Analysis Digital Medical Images in RGB Format
    (WARSE, 2020) Lyashenko, V.; Kobylin, O.; Ryazantsev, O.; Ryazantsev, I.; Barbaruk, V.; Zhychenko, Y.
    Methods, technologies and various digital image processing procedures are one of the data analysis tools. At the same time, digital images can be considered as data that belong to the Big Data group. This fully applies to digital color images of cytological preparations. Thus, digital image processing techniques are one of the Big Data analysis tools. A feature of such a tool is the specificity of its use for various types of data, which are presented in the form of digital images. To do this, we examined the problematic aspects of the analysis of cytological specimens of images that are marked in the works of other authors. The paper also examined the issues of complex analysis of color images of cytological preparations. For this analysis, we used the decomposition of the original image into separate color channels, applied the ideology of wavelets to determine areas of interest and a set of morphological operations to specify such areas of interest. These methods are selected taking into account the peculiarities of images of cytological preparations. The results are shown on the example of images of cytological preparations, where megaloblastic anemia cells are also present.
  • Зображення мініатюри
    Публікація
    Influence of a signal description model on the calculations of the efficiency indicators of optoelectronic systems
    (НПП ЧП "Технологический Центр", 2020) Strelkova, T.; Lytuyga, A.; Kalmykov, A.; Khoroshun, G.; Riazantsev, A.; Ryazantsev, O.
    The work is aimed at establishing the boundaries of the use of models for describing signals in optoelectronic systems in calculating efficiency. A description of the signal formation process is proposed, taking into account the corpuscular and wave properties when registering signals in a wide range of intensities. A description of the statistical features of the output signals depending on the energy properties of the signal and noise components is proposed. It is shown that when describing the output signals of optoelectronic systems that register signals with different properties, Poisson and Gaussian distributions are used. The invariance of Poisson flows determines the description of an additive mixture of signal and background flows using Poisson flow. The efficiency of optoelectronic systems is calculated by the signal-to-noise ratio criterion based on the corpuscular and wave description of signals. Efficiency calculations have shown the expedience of using this criterion, provided that the statistical properties of signal and background flows are stabilized. It is shown that under the condition of changes in the energy characteristics of signals, from the point of view of the wave and corpuscular models, the statistical characteristics of the signals have different descriptions. The analysis of theoretical methods of signal analysis in optoelectronic systems is carried out, which is aimed at an adequate characteristic of the system operation, depending on the conditions of its operation. Taking into account the method of describing the process of receiving and processing signals will take into account additional statistical characteristics of signals, for example, an increase of the variance of the output signal. The use of adaptive methods for describing signals will make it possible to increase the efficiency of systems when receiving strong signals in a difficult interference environment, as well as when receiving weak signals
  • Зображення мініатюри
    Публікація
    Processing Technique for Biomedical Image Analysis
    (Severodonetsk, Ukraine, 2019) Lyashenko, V.; Kobylin, O.; Ryazantsev, O.; Ryazantsev, I.
    Image processing methods are used in all areas of research. These methods provide additional information, a better understanding of the object that is being studied. Among the areas of using image processing methods, medicine occupies a special place. Biomedical data allow us to assess human health, to identify diseases in the early stages. Images of cellular structures of cytological preparations are one of the examples of biomedical data. Based on image analysis methods, we can isolate various components of cellular structures of cytological preparations. To do this, we apply the methods of wavelet analysis for different color components of the input image. Applying morphological analysis, we can identify individual cellular structures. The results are shown on the example of images of cellular structures of cytological preparations.