A Model for Recognizing Structureless Hyperpigmented Areas in Dermato-Oncology

A model for recognizing structureless hyperpigmented areas in images of skin neoplasms has been developed. Recognition of hyperpigmented areas is important for the diagnosis of skin melanoma, a rapidly progressing skin cancer. A digital dermatoscope RDS-2 has been used to obtain images serving as the initial data for the model. Software for recognizing hyperpigmentation areas in images of skin neoplasms has been developed on the basis of the proposed model. Tests have shown the recognition accuracy to be 82%. The proposed model can be recommended for use in decision-making 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 , Solomatin M.A.1 , Medvedeva O.A.1 , Kozlov V.S.1
Journal
Biomedical Engineering
Publisher
Springer New York LLC
Number of issue
5
Language
English
Pages
346-349
Status
Published
Link
External link
DOI
10.1007/s10527-022-10133-2
Volume
55
Year
2022
Organizations
  • 1 National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), Moscow, Russian Federation
  • 2 Peoples’ Friendship University of Russia, Moscow, Russian Federation
  • 3 Central State Medical Academy of Department of Presidential Affairs, Moscow, Russian Federation
Keywords
Decision making; Oncology; Tumors; Decision-making support systems; Hyperpigmentation; Recognition accuracy; Skin cancers; Dermatology; Article; decision making; diagnostic accuracy; diagnostic test accuracy study; histogram; human; human cell; hyperpigmentation; image analysis; image quality; melanoma; neoplasm; skin cancer; skin pigmentation; telemedicine
Date of creation
06.07.2022
Date of change
06.07.2022
Short link
https://repository.rudn.ru/en/records/article/record/84331/
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