Development of Method of Matched Morphological Filtering of Biomedical Signals and Images

Povoroznyuk, Anatoly; Filatova, Anna; Zakovorotniy, Alexander; Shehna, Kh.

doi:10.3103/s014641161903009x

Cited by 4 publications

(3 citation statements)

References 9 publications

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“…In [23], the authors proposed the method for morphological analysis of BMS with LCF based on matched morphological (MM) filtration. The main idea of the method is as follows.…”

Section: Literature Reviewmentioning

confidence: 99%

Method of Automatic Determination of the Heart’selectrical Axisin Cardiological Decision Support Systems

Filatova¹,

Fahs²

2021

AAIT

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The work is devoted to solving the scientific and practical problem of automating the heart’s electrical axis calculation to improve the quality of morphological analysis of biomedical signals with locally concentrated features in cardiological decision support systems, which in turn reduces the likelihood of medical errors. The work shows that existing methods for in the determining the electrical axis of the heart require morphological analysis of an electrocardiogram. The method is based on determining the integral signal in the frontal plane from all limb leads, taking into account the lead angle in the hexaxial reference system. In graphic form in polar coordinates, the integral electrocardiological signal is a figure, predominantly elongated along the axis, the direction’n of which corresponds to the heart’s electrical axis. The position of the heart’s electrical axis is calculated as the angle between the axis of standard lead I and the vector, the end of which is at the center of mass of the locus of the points the farthest away from the reference point. Cluster analysis is used to find the most distant points from the reference point. The proposed method for of calculating the heart’s electrical axis makes it possible not to carry out a preliminary morphological analysis of an electrocardiogram. To implement the method proposed in the article, a program was written in the Matlab language, which is connected as a dynamic link library to the cardiological decision support system “TREDEX telephone” operating as part of the medical diagnostic complex “TREDEX” manufactured by “Company TREDEX” LLC, Kharkiv. Verification of the results was carried out using a database of electrocardiograms, which were recorded using a transtelephone digital 12-channel electrocardiological complex “Telecard”, which is part of the medical diagnostic complex “TREDEX”, and deciphered by cardiologists of the communal non-profit enterprise of the Kharkiv Regional Council “Center for Emergency Medical aid and disaster medicine”. Comparison of the results of calculating the heart’s electrical axis according to electrocardiograms by a doctor and automatically using the proposed method showed that in the overwhelming majority of cases the decisions made coincide. At the same time, cardiologists make mistakes, and errors are made during automatic calculation using the proposed method. The paper explains the reasons for these errors.

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“…In [23], the authors proposed the method for morphological analysis of BMS with LCF based on matched morphological (MM) filtration. The main idea of the method is as follows.…”

Section: Literature Reviewmentioning

confidence: 99%

Method of Automatic Determination of the Heart’selectrical Axisin Cardiological Decision Support Systems

Filatova¹,

Fahs²

2021

AAIT

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“…In addition, the authors proposed a method for morphological filtration of BMS with LCF, which also solves the problem of the morphological analysis of the ECG [16].…”

Section: Literature Analysis and Problem Statementmentioning

confidence: 99%

Application of Probabilistic-Time Graphs for Evaluating the Effectiveness of the Electrocardiological Study Process

Povoroznyuk¹,

Filatova²,

Fahs³

2020

AAIT

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This work is devoted to the development of a structural model of the patient's electrocardiological study process based on graph theory, probability theory and the method of generating functions. The developed structural model is presented in the form of a probabilistic-time graph, in which nine main states and an uncertainty state (a set of states that do not lead to the goal) are identified, as well as the probabilistic-time characteristics of the arcs of transitions from one graph state to another. The following are identified as the main states characterizing the process to complete an electrocardiological study: the beginning of the study; indications were defined; morphological analysis of biomedical signals with locally concentrated features was performed; pathological changes were identified; comparison with previous electrocardiological studies was performed; dynamics evaluation was completed; evaluation of treatment effectiveness was completed; diagnostic decision was made; recommendations were issued (the end of the electrocardiological study). For the proposed model of the electrocardiological study process by the Mason method, there are obtained analytical expressions for the generating functions of the entire graph, as well as the part of the graph that characterizes the successful completion of the electrocardiological study. Using the indicated generating functions, analytical expressions were obtained to calculate the average transit time of an electrocardiological study and the probability of successful completion of this process. To get all analytic expressions, a program was written in the Matlab language. The developed structural model of an electrocardiological study in the form of a probabilistic-time graph made it possible to identify the main states and determine the criteria for the effectiveness of the process in terms of average time and the probability of a successful study.

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“…Morphological analysis of BMI with LLS is one of the crucial stages, since errors at this stage lead to the making of erroneous diagnostic decisions or to a refusal from making a decision at all. This stage requires the use of specialized methods of morphological data analysis, taking into account the features of BMI with LLS and methods of their transformation [6,7]. The theory of morphological analysis has been most fully developed for processing images and scenes of various types [8,9].…”

Section: Introductionmentioning

confidence: 99%

Application of Fractal Processing of Digital Mammograms in Designing Decision Support Systems in Medicine

Povoroznyuk

Шехна

2020

A.I.S.

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Development of Method of Matched Morphological Filtering of Biomedical Signals and Images

Cited by 4 publications

References 9 publications

Method of Automatic Determination of the Heart’selectrical Axisin Cardiological Decision Support Systems

Method of Automatic Determination of the Heart’selectrical Axisin Cardiological Decision Support Systems

Application of Probabilistic-Time Graphs for Evaluating the Effectiveness of the Electrocardiological Study Process

Application of Fractal Processing of Digital Mammograms in Designing Decision Support Systems in Medicine

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