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Characteristics of the Structural Elements of the “Lines” in the Melanoma Recognition System

https://doi.org/10.56304/S2079562922030344

Abstract

The paper considers the problem of early diagnosis of one of the most dangerous malignant neoplasms of the skin – melanoma. A model of the allocation of structural elements (lines) on digital images of skin neoplasms in oncodermatology has been developed. The model is based on a combination of Otsu binarization and adaptive binarization of the original digital dermatoscopic image of skin neoplasms and subsequent skeletonization and filtration of false line fragments.

About the Authors

A. I. Otchenashenko
National Research Nuclear University MEPhI (Moscow Engineering Physics Institute)
Russian Federation

Moscow, 115409



V. G. Nikitaev
National Research Nuclear University MEPhI (Moscow Engineering Physics Institute)
Russian Federation

Moscow, 115409



A. N. Pronichev
National Research Nuclear University MEPhI (Moscow Engineering Physics Institute)
Russian Federation

Moscow, 115409



O. B. Tamrazova
Russian Peoples’ Friendship University (RUDN University)
Russian Federation

Moscow, 117198



V. Yu. Sergeev
Central State Medical Academy of the Presidential Administration of the Russian Federation
Russian Federation

Moscow, 121359



Yu. Yu. Sergeev
Central State Medical Academy of the Presidential Administration of the Russian Federation
Russian Federation

Moscow, 121359



References

1. Эберт М.А. и др. // Вопросы онкологии. 2019. Т. 65 (5). С. 638−644. https://doi.org/10.37469/0507-3758-2019-65-5-638-644

2. Zhuchkov M.V. et al. // Consil. Med. 2020. V. 22 (7). P. 38−41.

3. Kudrin K.G. et al. // Opt. Spectrosc. 2020. V. 128 (6). P. 820−831. https://doi.org/10.1134/S0030400X20060132

4. Kulik S., Shtanko A. // Proc. Comput. Sci. 2020. V. 169. P. 164–167. https://doi.org/10.1016/j.procs.2020.02.129

5. Prilipsky R.E., Zaeva M.A. // Proc. Comput. Sci. 2020. V. 169. P. 96–99. https://doi.org/10.1016/j.procs.2020.02.120.19

6. Marchetti M.A. et al. // J. Am. Acad. Dermatol. 2020. V. 82 (3). P. 622−627. https://doi.org/10.1016/j.jaad.2019.07.016

7. Amelard R. et al. // IIEEE Trans. Biomed. Eng. 2014. V. 62 (3). P. 820−831. https://doi.org/10.1109/TBME.2014.2365518

8. Oliveira R.B. et al. // Neural Comput. Appl. 2018. V. 29 (3). P. 613−636. https://doi.org/10.1007/s00521-016-2482-6

9. Munir K. et al. // Cancers. 2019. V. 11. (9). P. 1235. https://doi.org/10.3390/cancers11091235

10. Bazhenova N.V. // Sustain. Developm. Sci. Educ. 2018. V. 4. P. 218−221.

11. Ivanova I.V., Palmin P.A. // Proc. Scientific Research in the Modern World. Theory and Practice. 2021. P. 69−73.

12. Meng H. et al. // IEEE Trans. Med. Imaging. 2019. V. 38 (12). P. 2726−2734.

13. Mohammed Z.H.M.N. // Model. Optimiz. Inform. Technol. 2018. V. 6 (1). P. 99−107.

14. Hijazi M.H.A. et al. // Int. J. Artif. Intell. 2019. V. 8 (4). P. 429.

15. Speiser J.L. et al. // Expert Syst. Appl. 2019. V. 134. P. 93−101.


Review

For citations:


Otchenashenko A.I., Nikitaev V.G., Pronichev A.N., Tamrazova O.B., Sergeev V.Yu., Sergeev Yu.Yu. Characteristics of the Structural Elements of the “Lines” in the Melanoma Recognition System. Nuclear Physics and Engineering. 2023;14(2):185-188. (In Russ.) https://doi.org/10.56304/S2079562922030344

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ISSN 2079-5629 (Print)
ISSN 2079-5637 (Online)