Model for Detecting Globules in Images of Skin Neoplasms

This article is devoted to the digital processing of images of skin neoplasms to detect significant structural elements in the diagnosis of melanoma–globules (clumps, lumps). A new processing model is proposed, which makes it possible to stably select globules in images of different contrasts withou...

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Published in:Mathematical models and computer simulations 2022, Vol.14 (3), p.411-418
Main Authors: Nikitaev, V. G., Pronichev, A. N., Tamrazova, O. B., Sergeev, V. Yu, Lim, A. O., Kozlov, V. S.
Format: Article
Language:English
Subjects:
Adequacy
Clumps
Digital imaging
Globules
Image contrast
Mathematical Modeling and Industrial Mathematics
Mathematics
Mathematics and Statistics
Neoplasms
Simulation and Modeling
Structural members
Tumors
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container_title Mathematical models and computer simulations
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creator Nikitaev, V. G.
Pronichev, A. N.
Tamrazova, O. B.
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Lim, A. O.
Kozlov, V. S.
description This article is devoted to the digital processing of images of skin neoplasms to detect significant structural elements in the diagnosis of melanoma–globules (clumps, lumps). A new processing model is proposed, which makes it possible to stably select globules in images of different contrasts without the need to manually adjust the parameters. The results of the experiment confirming the adequacy of the model are presented. The globule recognition accuracy ranged from 81 to 89%, depending on the contrast of the original images. The experimental sample of images contained 2868 globules.
doi_str_mv 10.1134/S2070048222030115
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subjects Adequacy
Clumps
Digital imaging
Globules
Image contrast
Mathematical Modeling and Industrial Mathematics
Mathematics
Mathematics and Statistics
Neoplasms
Simulation and Modeling
Structural members
Tumors
title Model for Detecting Globules in Images of Skin Neoplasms
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