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Документ Developing an informational model of instrumental examination(2019) Filatova, A. E.; Povoroznyuk, A. I.; Gavrylenko, Svitlana; Fahs, MohamadThis document presents the development of an informational model of instrumental examination of a patient using the data flow diagrams (DFD). The developed informational model of the instrumental examination is presented in the form of a context diagram, its decomposition, and the decomposition of the subsystems «Registration and analysis of biomedical signals and images with locally concentrated features» and «Diagnostics». Taking into account the proposed information model, UML diagrams of the activity of the biomedical decision support system based on morphological analysis of biomedical signals and images with locally concentrated features, of the module for morphological analysis of an electrocardiogram, and of the module for improving the quality of visualization of biological objects on radiological images based on the IMRI method are developed.Документ Development of method of matched morphological filtering of biomedical signals and images(Allerton Press, 2019) Povoroznyuk, A. I.; Filatova, A. E.; Zakovorotniy, A. Yu.; Shehna, Kh.Formalized approach to the analysis of biomedical signals and images with locally concentrated features is developed on the basis of matched morphological filtering taking into account the useful signal models that allowed generalizing the existing methods of digital processing and analysis of biomedical signals and images with locally concentrated features. The proposed matched morphological filter has been adapted to solve such problems as localization of the searched structural elements on biomedical signals with locally concentrated features, estimation of the irregular background aimed at the visualization quality improving of biological objects on X-ray biomedical images, pathologic structures selection on mammogram. The efficiency of the proposed methods of matched morphological filtration of biomedical signals and images with locally concentrated features is proved by experiments.