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Proceedings Paper

Creating a classification model for diagnosis of joint lesions type
Author(s): M. V. Talakh; S. V. Holub; Yu. A. Ushenko; V. K. Gantiuk
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Paper Abstract

The work combines methods of multidimensional polarization microscopy, statistical processing of data and algorithms of machine learning with the purpose of constructing a methodology for creation of intelligent systems for multi-level medical monitoring of joint lesions . The task of classifying the results of the study of biological materials for obtaining a diagnosis was solved. To obtain informative features, a model of biological tissue was developed and the main diagnostic parameters were determined (statistical moments of 1-4 orders of coordinate distributions of the values of azimuths and the ellipticity of polarization and their autocorrelation functions, as well as wavelet coefficients of the corresponding distributions). The classification of these data was provided on the raw input data and on generated data with different degree of overlapping classes by machine learning algorithms and inductive modeling.

Paper Details

Date Published: 6 February 2020
PDF: 6 pages
Proc. SPIE 11369, Fourteenth International Conference on Correlation Optics, 1136922 (6 February 2020);
Show Author Affiliations
M. V. Talakh, Chernivtsi National Univ. (Ukraine)
S. V. Holub, Cherkasy State Technological Univ. (Ukraine)
Yu. A. Ushenko, Chernivtsi National Univ. (Ukraine)
V. K. Gantiuk, Chernivtsi National Univ. (Ukraine)


Published in SPIE Proceedings Vol. 11369:
Fourteenth International Conference on Correlation Optics
Oleg V. Angelsky, Editor(s)

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