Персона:
Козлов, Владимир Сергеевич

Организационные подразделения

Организационная единица

Инженерно-физический институт биомедицины

Цель ИФИБ и стратегия развития – это подготовка высококвалифицированных кадров на базе передовых исследований и разработок новых перспективных методов и материалов в области инженерно-физической биомедицины. Занятие лидерских позиций в биомедицинских технологиях XXI века и внедрение их в образовательный процесс, что отвечает решению практикоориентированной задачи мирового уровня – диагностике и терапии на клеточном уровне социально-значимых заболеваний человека.

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Козлов

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Владимир Сергеевич

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Теперь показываю 1 - 9 из 9

Только метаданные
A Model for Detecting Structural Elements – Lines – in Digital Images in Oncodermatology
(2021) Tamrazova, O. B.; Sergeev, V. Y.; Nikitaev, V. G.; Pronichev, A. N.; Otchenashenko, A. I.; Druzhinina, E. A.; Kozyreva, A. V.; Solomatin, M. A.; Kozlov, V. S.; Никитаев, Валентин Григорьевич; Проничев, Александр Николаевич; Отченашенко, Александр Иванович; Соломатин, Михаил Андреевич; Козлов, Владимир Сергеевич
© 2021, Springer Science+Business Media, LLC, part of Springer Nature.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.
Только метаданные
Detection of Circles as Structural Elements in Dermatoscopic Images of Skin Neoplasms in the Diagnosis of Melanoma
(2021) Tamrazova, O. B.; Sergeev, V. Y.; Nikitaev, V. G.; Pronichev, A. N.; Medvedeva, O. A.; Kozlov, V. S.; Solomatin, M. A.; Никитаев, Валентин Григорьевич; Проничев, Александр Николаевич; Козлов, Владимир Сергеевич; Соломатин, Михаил Андреевич
© 2021, Springer Science+Business Media, LLC, part of Springer Nature.A method for recognizing “circles”, significant structural elements of skin neoplasms, has been proposed. An RDS-2 dermatoscope has been used for imaging. Special software has been developed to implement the proposed method for circle recognition. The results of experimental detection of circles are presented. The developed method can be used in diagnostic systems for detecting skin melanoma, a dangerous form of cancer.
Только метаданные
Model for Estimating the Morphological Characteristics of Structureless Areas of Pigmented Skin Neoplasms
(2022) Nikitaev, V. G.; Pronichev, A. N.; Lim, A. O.; Kozlov, V. S.; Tamrazova, O. B.; Sergeev, Yu. Yu.; Никитаев, Валентин Григорьевич; Проничев, Александр Николаевич; Козлов, Владимир Сергеевич
Только метаданные
Model for Detecting Globules in Images of Skin Neoplasms
(2022) Tamrazova, O. B.; Sergeev, V. Y.; Nikitaev, V. G.; Pronichev, A. N.; Lim, A. O.; Kozlov, V. S.; Никитаев, Валентин Григорьевич; Проничев, Александр Николаевич; Козлов, Владимир Сергеевич
© 2022, Pleiades Publishing, Ltd.Abstract: 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.
Только метаданные
A Model for Recognizing Structureless Hyperpigmented Areas in Dermato-Oncology
(2022) Tamrazova, O. B.; Sergeev, V. Y.; Nikitaev, V. G.; Pronichev, A. N.; Solomatin, M. A.; Medvedeva, O. A.; Kozlov, V. S.; Никитаев, Валентин Григорьевич; Проничев, Александр Николаевич; Соломатин, Михаил Андреевич; Козлов, Владимир Сергеевич
© 2022, Springer Science+Business Media, LLC, part of Springer Nature.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.
Только метаданные
Color recognition of dermatoscopic images of skin neoplasms
(2021) Tamrazova, O. B.; Sergeev, V. Yu.; Sergeev, Yu. Yu.; Nikitaev, V. G.; Pronichev, A. N.; Medvedeva, O. A.; Solomatin, M. A.; Kozlov, V. S.; Никитаев, Валентин Григорьевич; Проничев, Александр Николаевич; Соломатин, Михаил Андреевич; Козлов, Владимир Сергеевич
© 2021 Institute of Physics Publishing. All rights reserved.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.
Только метаданные
Model for Estimating the Heterogeneity of the Distribution of Globule Characteristics in Images of Skin Neoplasms
(2021) Tamrazova, O. B.; Sergeev, V. Y.; Nikitaev, V. G.; Pronichev, A. N.; Selchuk, V. Y.; Kozlov, V. S.; Lim, A. O.; Никитаев, Валентин Григорьевич; Проничев, Александр Николаевич; Сельчук, Владимир Юрьевич; Козлов, Владимир Сергеевич
© 2022, Springer Science+Business Media, LLC, part of Springer Nature.The problem of diagnosing skin melanoma by digital imaging of the tumor is considered. Clinical algorithms for detecting skin melanoma are briefly described. A review of works devoted to the automated assessment of distribution asymmetry of the shape, color, and area of globules – important signs of melanoma, is given. A model for assessing the distribution heterogeneity of globule characteristics on digital images in the diagnosis of skin neoplasms has been developed, and models of distribution heterogeneity indicators have been proposed. An experimental comparative assessment of indicator models was carried out using a software system developed in the C++ language. The most informative indicators of globule characteristics distribution heterogeneity have been determined. The maximum (93%) accuracy in assessing the distribution heterogeneity of globule characteristics was obtained for the indicator “reduced reciprocal of the highest frequency of occurrence of the measured areas of globules.” The results of the study can be useful in the development of medical decision support systems for the diagnosis of melanoma.
Только метаданные
A Model for Recognition of Dermatoscopic Points in Images of Skin Neoplasms
(2021) Tamrazova, O. B.; Sergeev, V. Y.; Kruglova, L. S.; Nikitaev, V. G.; Pronichev, A. N.; Solomatin, M. A.; Kozlov, V. S.; Druzhinina, E. A.; Никитаев, Валентин Григорьевич; Проничев, Александр Николаевич; Соломатин, Михаил Андреевич; Козлов, Владимир Сергеевич
© 2021, Springer Science+Business Media, LLC, part of Springer Nature.The challenges of using computer diagnostics to seek structural elements of melanocytic neoplasms, including cutaneous melanomas at early stages of their development, are discussed. The characteristic features of the structural elements — dermatoscopic points — are also considered. A computer vision technique for recognizing these characteristic features is presented. The developed interdisciplinary approach can be used in the diagnosis of oncological diseases of the skin as a means of supporting decision making for the primary prevention of malignant neoplasms.
Только метаданные
Model of images of structureless areas for the analysis of pigment patterns using artificial intelligence in oncodermatology
(2025) Nikitaev, V. G.; Sergeev, V. Yu.; Kegelik, N. A.; Kozlov, V. S.; Никитаев, Валентин Григорьевич; Козлов, Владимир Сергеевич