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.

Авторы
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
Журнал
Издательство
Springer New York LLC
Номер выпуска
5
Язык
Английский
Страницы
346-349
Статус
Опубликовано
Том
55
Год
2022
Организации
  • 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
Ключевые слова
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
Дата создания
06.07.2022
Дата изменения
06.07.2022
Постоянная ссылка
https://repository.rudn.ru/ru/records/article/record/84331/
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