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 diag- nosis 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, neurodegenera- tive disorders, psychiatric disorders, and may be the basis for the development of the interface “brain-computer”, on the basis of electroencephalography and magnetoen- cephalography. 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). Keywords:
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CITATION STYLE
Albertovich, T. D., & Aleksandrovna, R. I. (2017). The Fractal Analysis of the Images and Signals in Medical Diagnostics. In Fractal Analysis - Applications in Health Sciences and Social Sciences. InTech. https://doi.org/10.5772/intechopen.68167
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