Creating a classification model for diagnosis of joint lesions type

M. V. Talakh; S. V. Holub; Yu. A. Ushenko; V. K. Gantiuk

doi:10.1117/12.2553971

6 February 2020 Creating a classification model for diagnosis of joint lesions type

M. V. Talakh, S. V. Holub, Yu. A. Ushenko, V. K. Gantiuk

Proceedings Volume 11369, Fourteenth International Conference on Correlation Optics; 1136922 (2020) https://doi.org/10.1117/12.2553971
Event: Fourteenth International Conference on Correlation Optics, 2019, Chernivtsi, Ukraine

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.

Citation Download Citation

M. V. Talakh, S. V. Holub, Yu. A. Ushenko, and V. K. Gantiuk "Creating a classification model for diagnosis of joint lesions type", Proc. SPIE 11369, Fourteenth International Conference on Correlation Optics, 1136922 (6 February 2020); https://doi.org/10.1117/12.2553971

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