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The Fractal Analysis of the Images and Signals in Medical Diagnostics

In: Fractal Analysis - Applications in Health Sciences and Social Sciences

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  • Dmitrii Tayurskii
  • Inna Rusanova

Abstract

In the present chapter, we summarize our results concerning fractal analysis of some medical data. The aim of this study is to identify the inherent human body "chaotic" dynamics and insufficient disclosure of the physical essence of the processes observed, depending on the extent of developing a pathology that is characterized by a decrease or increase in the degree of complexity and as a consequence--randomness, for which, in some cases, hidden fractal. The proposed approach based on identifying the presence of the properties of self-similarity can be useful in preliminary clinical trials for the diagnosis of cancerous epithelial diseases, blood, and liver in the initial stage, the analysis of digital images, the structure of correlations biomedical parameters, as well as in the study of pathologies of the central nervous system--the neurological, neurodegenerative disorders, psychiatric disorders, and may be the basis for the development of the interface "brain-computer", on the basis of electroencephalography and magnetoencephalography. Additional measures are proposed to study the presence of self-similar properties in the form of self-similarity and magnitude SRGB ratio (area of a triangle in the coordinate system of the properties).

Suggested Citation

  • Dmitrii Tayurskii & Inna Rusanova, 2017. "The Fractal Analysis of the Images and Signals in Medical Diagnostics," Chapters, in: Fernando Brambila (ed.), Fractal Analysis - Applications in Health Sciences and Social Sciences, IntechOpen.
  • Handle: RePEc:ito:pchaps:115089
    DOI: 10.5772/intechopen.68167
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    Keywords

    fractal dimension; EEG signals; magnetoencephalography signals; photosensitive epilepsy; malignant tissue; leukemia; brain-computer;
    All these keywords.

    JEL classification:

    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets

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