Меланоцитарный невус как предшественник меланомы: клинические случаи и обзор литературы

Most cases of malignant melanoma develop de novo; in a third of cases, however, a tumor may arise on the background of a pre-existing melanocytic nevus. Nevus associated melanomas have some epidemiological features: they develop at a younger age, are more often are located on the trunk and have a lower Breslow thickness. The available literature data and own authors’experience indicate the absence of the need for “prophylactic" removal of melanocytic nevi as possible precursors of a malignant tumor. One of the methods for the early diagnosis of melanoma can be the introduction of digital dermatoscopy using automated processing of dermatoscopic images with artificial intelligence. The article describes the clinical cases of nevus-associated melanomas; litreture review and discussion of this problem are presented.Большинство случаев меланомы кожи развиваются de novo, однако в трети случаев возможно формирование опухоли на фоне существовавшего ранее меланоцитарного невуса. Ассоциированные с невусом опухоли имеют некоторые эпидемиологические особенности: они развиваются в более молодом возрасте, чаще располагаются на коже туловища и отличаются меньшей толщиной по Бреслоу. Имеющиеся литературные данные и собственный опыт свидетельствуют об отсутствии необходимости «профилактического» удаления отдельных меланоцитарных невусов как возможных предшественников злокачественной опухоли. Одним из способов ранней диагностики меланомы кожи может стать внедрение цифровой дерматоскопии с использованием автоматизированной обработки дерматоскопических изображений при помощи искусственного интеллекта. В статье приводятся описание клинических случаев МК, возникших на фоне меланоцитарных невусов, обзор литературы и обсуждение данной проблемы

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

Abstract In this study, the problem of early diagnosis of one of the most dangerous malignant neoplasms of the skin—melanoma—is considered. A model of distinguishing structural elements (lines) in 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 fragments of the lines

Model for Estimating the Morphological Characteristics of Structureless Areas of Pigmented Skin Neoplasms

Abstract The problem of early diagnosis of skin melanoma by dermatoscopic images of skin neoplasms is considered. A model for assessing the diagnostically significant morphological characteristics of neoplasm elements—structureless areas—is proposed. An experimental study has been conducted to determine the adequacy of the model. The most informative features for assessment of morphological characteristics have been identified. The best classification accuracy (94%) has been achieved for feature A1. The results of this study can be applied in the development of medical decision support systems for the diagnosis of skin melanoma

Color recognition of dermatoscopic images of skin neoplasms

The problem of determining the colors of dermatoscopic images of skin neoplasms using computer technologies is considered. Based on the proposed model, a program for recognizing the colors of the studied areas of neoplasm has been developed. The adequacy of this model was tested experimentally. This work is designed to increase the reliability of the diagnosis of skin neoplasms. © 2021 Institute of Physics Publishing. All rights reserved

Image Segmentation of Skin Neoplasms Using the Active Contour Method

Abstract Computer vision technologies are being actively introduced into modern life, including medical practice. The development of such technologies has led to the emergence of computer systems that allow the detection and classification of skin diseases with a quality comparable to and in some cases exceeding human capabilities. The article reveals the method of automatic segmentation on the basis of dermatoscopic images provided by doctors obtained using a digital optical device—a dermatoscope. The main goal of the model being developed is to identify the neoplasm zone and areas of hyperpigmentation on images of skin neoplasms for further integration into medical decision support systems for diagnosing of melanoma. As a result of the work carried out, a software package was created that allows segmentation of the neoplasm. As a demonstration of the method, experimental studies of the detection of melanoma boundaries and zones of areas of signs on images of skin neoplasms are presented. The developed system can be used for diagnostic research and educational purposes

Model for Assessing the Asymmetry of a Pigmented Neoplasm

Abstract The paper presents the results of the development of a method for recognizing skin neoplasms based on a model for assessing the asymmetry of the shape of the pigment area of the pathological growth of the epidermis and (or) dermis. Images of pigmented skin neoplasms obtained using a dermatoscope were considered as initial data. To analyze the images, a model was used to calculate the shape asymmetry coefficients obtained relative to the main axes of inertia of the neoplasm, which makes it possible to obtain values independent of the angle of rotation of the images