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Proceedings of the Institute for System Programming of the RAS, 2022, Volume 34, Issue 4, Pages 241–250
DOI: https://doi.org/10.15514/ISPRAS-2022-34(4)-17
(Mi tisp717)
 

Review of methods for early melanoma computer vision detection

A. V. Kozachoka, A. A. Spirina, E. S. Kozachokb

a Ivannikov Institute for System Programming of the RAS
b Orel Regional Clinical Hospital
Abstract: Melanoma is one of the most aggressive forms of cancer, which can be treated only with early detection of the disease. The article discusses the existing algorithms and methods of visual diagnosis of melanoma. The systems of automatic diagnosis of dermatoscopic images and the methods used by them are also considered. The article considers the limitations hindering the development of automatic diagnosis systems: the lack of relevant domestic data sets that allow training artificial intelligence models, insufficient level of patient metadata accounting, low coverage of the population for the presence of melanoma during routine examinations. A variant of building a decision support system by general practitioners in the analysis of dermatoscopic images of the skin is proposed.
Keywords: early detection of melanoma, automatic diagnosis systems, artificial intelligence in medicine
Document Type: Article
Language: Russian
Citation: A. V. Kozachok, A. A. Spirin, E. S. Kozachok, “Review of methods for early melanoma computer vision detection”, Proceedings of ISP RAS, 34:4 (2022), 241–250
Citation in format AMSBIB
\Bibitem{KozSpiKoz22}
\by A.~V.~Kozachok, A.~A.~Spirin, E.~S.~Kozachok
\paper Review of methods for early melanoma computer vision detection
\jour Proceedings of ISP RAS
\yr 2022
\vol 34
\issue 4
\pages 241--250
\mathnet{http://mi.mathnet.ru/tisp717}
\crossref{https://doi.org/10.15514/ISPRAS-2022-34(4)-17}
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