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Published in: Measurement Techniques 6/2021

26-11-2021 | MEDICAL AND BIOLOGICAL MEASUREMENTS

A Model for Detecting Structural Elements – Lines – in Digital Images in Oncodermatology

Authors: V. G. Nikitaev, A. N. Pronichev, O. B. Tamrazova, V. Yu. Sergeev, A. I. Otchenashenko, E. A. Druzhinina, A. V. Kozyreva, M. A. Solomatin, V. S. Kozlov

Published in: Measurement Techniques | Issue 6/2021

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Abstract

The problem of early diagnosis of one of the most dangerous malignant neoplasms of the skin, melanoma, is considered. A model for detecting structural elements (lines) in digital images of skin neoplasms in oncodermatology has been developed. The model is based on adaptive binarization of the initial digital dermatoscopy image of skin les neoplasms ions and subsequent operations of dilation, erosion, skeletonization, and filtration of false line fragments. Test dermatoscopy images of skin neoplasms were visually divided into four groups to conduct the experiment. Optimal parameters of image processing of four groups for the model of detecting structural elements – lines – have been experimentally established. The experimentally determined accuracy of line detection was 95%. This research is the result of interdisciplinary cooperation of dermatologists of the Central Medical Academy of the Administrative Department of the President of the Russian Federation, the Medical Institute of the Russian Peoples’ Friendship University and experts in the field of information and measurement systems of the Engineering and Physical Institute of Biomedicine of the National Research Nuclear University “MEPhI”. The proposed model can be used in the development of computer systems to support medical decision-making in the diagnosis of skin melanoma – a dangerous malignant neoplasm.

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Metadata
Title
A Model for Detecting Structural Elements – Lines – in Digital Images in Oncodermatology
Authors
V. G. Nikitaev
A. N. Pronichev
O. B. Tamrazova
V. Yu. Sergeev
A. I. Otchenashenko
E. A. Druzhinina
A. V. Kozyreva
M. A. Solomatin
V. S. Kozlov
Publication date
26-11-2021
Publisher
Springer US
Published in
Measurement Techniques / Issue 6/2021
Print ISSN: 0543-1972
Electronic ISSN: 1573-8906
DOI
https://doi.org/10.1007/s11018-021-01962-w

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