Model for Estimating the Heterogeneity of the Distribution of Globule Characteristics in Images of Skin Neoplasms

The problem of diagnosing skin melanoma by digital imaging of the tumor is considered. Clinical algorithms for detecting skin melanoma are briefly described. A review of works devoted to the automated assessment of distribution asymmetry of the shape, color, and area of globules – important signs of melanoma, is given. A model for assessing the distribution heterogeneity of globule characteristics on digital images in the diagnosis of skin neoplasms has been developed, and models of distribution heterogeneity indicators have been proposed. An experimental comparative assessment of indicator models was carried out using a software system developed in the C++ language. The most informative indicators of globule characteristics distribution heterogeneity have been determined. The maximum (93%) accuracy in assessing the distribution heterogeneity of globule characteristics was obtained for the indicator “reduced reciprocal of the highest frequency of occurrence of the measured areas of globules.” The results of the study can be useful in the development of medical decision support systems for the diagnosis of melanoma. © 2022, Springer Science+Business Media, LLC, part of Springer Nature.

Authors
Nikitaev V.G.1 , Pronichev A.N.1 , Tamrazova O.B. 2 , Sergeev V.Y. 3 , Selchuk V.Y.1, 4 , Kozlov V.S.1 , Lim A.O.1
Number of issue
9
Language
English
Pages
778-783
Status
Published
Volume
64
Year
2021
Organizations
  • 1 National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), Moscow, Russian Federation
  • 2 Russian Peoples’ Friendship University, Moscow, Russian Federation
  • 3 Central State Medical Academy of the Administrative Department of the President of the Russian Federation, Moscow, Russian Federation
  • 4 Yevdokimov Moscow State University of Medicine and Dentistry, Moscow, Russian Federation
Keywords
digital image processing; globule characteristics; melanoma diagnostics; signs of heterogeneity; skin neoplasms
Date of creation
06.07.2022
Date of change
06.07.2022
Short link
https://repository.rudn.ru/en/records/article/record/84638/
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