Персона: Никитаев, Валентин Григорьевич
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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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Руководитель научной группы "Прикладные технологии искусственного интеллекта в онкодиагностике и промышленном контроле"
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Никитаев
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Валентин Григорьевич
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- ПубликацияТолько метаданныеSPITZ nevus (juvenile melanoma) in the pediatricians practice: Clinical picture, diagnosis, prognosis and treatment(2021) Tamrazova, O. B.; Sergeev, V. Yu.; Taganov, A. V.; Glukhova, E. A.; Nikitaev, V. G.; Pronichev, A. N.; Никитаев, Валентин Григорьевич; Проничев, Александр Николаевич© 2021, Pediatria Ltd.. All rights reserved.Spitz nevi (epithelioid and spindle-cell nevi) are a special group of melanocytic neoplasms with a specific clinical, dermatoscopic and histological picture. There are typical and atypical Spitz nevus. The typical Spitz nevus is more common in pediatric practice and has a benign course. Of particular interest are atypical forms that combine the characteristics of a typical Spitz nevus and melanoma. The article presents an analysis of the clinical picture, dermatoscopic, immunohistochemical, histological and genetic characteristics in various forms of Spitz nevus. The existing classification according to the metastasis risk degree is presented. The last recommendations on the tactics of managing patients with this nosology are discussed with examples of original observations.
- ПубликацияТолько метаданныеDetection 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.
- ПубликацияТолько метаданныеModel 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.
- ПубликацияТолько метаданныеAFM-MS for Protein Analysis of Plasma Samples of Patients with Ovarian Cancer(2019) Kaysheva, A. L.; Pleshakova, T. O.; Malsagova, K. A.; Chingin, K.; Pronichev, A. N.; Nikitaev, V. G.; Ivanov, E. O.; Проничев, Александр Николаевич; Никитаев, Валентин ГригорьевичAn atomic force microscope (AFM) is a molecular detector that allows the recording of individual proteins and protein complexes on the surface of an atomically flat substrate, the AFM chip. Registration of target proteins is carried out after the fishing procedure - catching out of proteins from the volume of the analyzed solution to a surface of a small area (sensory zone of the chip) modified by affinity reagents against the target protein. The use of the procedure of biospecific enrichment makes it possible to effectively concentrate the molecules of the target proteins in an amount sufficient for the subsequent mass spectrometric analysis for early diagnosis of ovarian cancer in blood samples.
- ПубликацияТолько метаданныеImage Segmentation of Skin Neoplasms Using the Active Contour Method(2022) Voronin, A. E.; Pronichev, A. N.; Nikitaev, V. G.; Solomatin, M. A.; Zanegina, T. P.; Arkhangelskaya, I. V.; Petukhova, A. I.; Bagnova, P. Yu.; Soshnina, A. V.; Проничев, Александр Николаевич; Никитаев, Валентин Григорьевич; Соломатин, Михаил Андреевич; Архангельская, Ирина Владимировна; Петухова, Александра Ильинична
- ПубликацияТолько метаданныеNevi in children: Organoid epidermal nevi: Clinical picture, diagnosis, treatment (Part 2)(2020) Tamrazova, O. B.; Sergeev, V. Y.; Sergeev, Y. Y.; Nikitaev, V. G.; Pronichev, A. N.; Никитаев, Валентин Григорьевич; Проничев, Александр Николаевич© 2020, Pediatria Ltd.. All rights reserved.Nevi are congenital formations that appear on the skin from birth or in early childhood, are very common in healthy children and, as a rule, are harmless. The article deals with epidermal nevi formed from epidermal cells and skin appendages (sebaceous and sweat glands, hair follicles). Particular attention is paid to the syndromes of epidermal nevi, which are characterized by a combination of skin rashes with systemic manifestations. Correct diagnosis of different subtypes of nevi, their differential diagnosis with other pigment formations (including melanomas) and non- melanoma skin cancer, as well as the recognition of non-uniform syndromes will help to determine the pediatrician correct tactics of management of patients, further counseling and assess the prognosis of the disease. Early diagnosis using dermatoscopy and modern techniques based on artificial intelligence is most significant in children before the development of progressive symptoms or neurological disorders. In the detection of epidermal nevus syndromes, consultations of related specialists (neurologists, traumatologists, cardiologists, etc.) are recommended.
- ПубликацияОткрытый доступSystem for constructing virtual slides for cytological diagnostics(2019) Shabalova, I. P.; Djangirova, T. V.; Ivanov, Y. D.; Nikitaev, V. G.; Pronichev, A. N.; Polyakov, E. V.; Zaitsev, S. M.; Никитаев, Валентин Григорьевич; Проничев, Александр Николаевич; Поляков, Евгений Валерьевич© 2019 Published under licence by IOP Publishing Ltd. A system of virtual cytological slides formation using a robotic scanning microscope with X40 lens are discussed in the paper. Series of digital images with different focus are provided in each of the positions of the object table. Panorama is formed by the frames which are combined by reference points allocated as a result of digital processing. A software module has been developed to adjust the results of the program combination. The proposed solution is used in practice.
- ПубликацияОткрытый доступClinical intelligent system for the diagnosis of prostate cancer(2019) Pushkar, D. Y.; Govorov, A. V.; Prilepskaya, E. A.; Kovilina, M. V.; Nikitaev, V. G.; Pronichev, A. N.; Selchuk, V. Yu.; Onykiy, B. N.; Zaytsev, S. M.; Polyakov, E. V.; Kurdin, A. A.; Levadnaya, M. G.; Никитаев, Валентин Григорьевич; Проничев, Александр Николаевич; Сельчук, Владимир Юрьевич; Поляков, Евгений Валерьевич© 2019 Published under licence by IOP Publishing Ltd. A software clinical intelligent system for the diagnosis of prostate cancer is discussed. The system provides assistance to the doctor in the histological diagnosis. The system has the mode of operation of an expert doctor to fill the knowledge base of the system, the mode of assistance to the diagnostician (pathologist) in the formation of requests to the system, the mode of support in decision-making based on the formation of a rating list of possible diagnoses for the case under study, the training mode.
- ПубликацияТолько метаданныеArtificial intelligence in oncourology: integrated deep learning technologies in the tasks of segmentation of three-dimensional images of kidney tumors(2025) Nikitaev, V. G.; Pushkar, D. Yu.; Matveev, V. B.; Pronichev, A. N.; Nagornov, O. V.; Otchenashenko, A. I.; Kleyman, A. I.; Никитаев, Валентин Григорьевич; Проничев, Александр Николаевич; Нагорнов, Олег Викторович; Отченашенко, Александр Иванович
- ПубликацияОткрытый доступМодель оценки асимметрии пигментного новообразования(2023) Занегина, Т. П.; Никитаев, В. Г.; Проничев, А. Н.; Соломатин, М. А.; Воронин, А. Е.; Архангельская, И. В.; Сошнина, А. В.; Петухова, А. И.; Багнова, П. Ю.; Тамразова, О. Б.; Сергеев, В. Ю.; Сергеев, Ю. Ю.; Архангельская, Ирина Владимировна; Никитаев, Валентин Григорьевич; Проничев, Александр Николаевич; Петухова, Александра Ильинична; Соломатин, Михаил АндреевичВ работе представлены результаты разработки наглядного способа распознавания новообразований кожи на основе модели оценки асимметрии формы пигментного участка патологического разрастания эпидермиса и (или) дермы. В качестве исходных данных рассматривались изображения пигментных новообразований кожи, полученные с помощью дерматоскопа. Для анализа изображений применялась модель расчета коэффициентов асимметрии формы, полученных относительно главных осей инерции новообразования, что позволяет получать независящие от угла поворота изображений значения.