Personalities of MEPhI
NRNU MEPhI National Research Nuclear University MEPhI
  1. Faculty and Staff
  2. Nikitaev V.G.
Nikitaev V.G.

Nikitaev Valentin G.

Degree: Doctor of Sciences in Technology

Head of Department

Department of Medical Computer Systems (46, ИФИБ КАФ.46)
Send message Spring 2024. Schedule
Works at MEPhI since 1973
Work Experience: 50 years

Courses

1. Approbation of scientific results
2. Image Processing Systems in Medicine
3. Introduction to the Profession
4. Pattern Recognition
5. Pedagogical practice
6. Post-graduate research and writing of scientific qualification work (dissertation) for seekers of “Candidate of Sciences” deegree
7. Practice on obtaining professional skills and experience of professional activity (pedagogical practice)
8. Research activities and thesis preparation
9. The Design of Medical Computer Systems: Problems and Solutions

Publication activity

4
h-index (Web of Science)
9
h-index (Scopus)
14
h-index (РИНЦ)

Showing publications for last 3 years

  1. Article
    Web of Science & Scopus
    Characteristics of the Structural Elements of the Lines in the Melanoma Recognition System // Physics of Atomic Nuclei, 2022 Vol. 85, No. 10, Q4 pp. 1789-1792 doi
  2. Article
    Web of Science & Scopus
    Image Segmentation of Skin Neoplasms Using the Active Contour Method // Physics of Atomic Nuclei, 2022 Vol. 85, No. 11, Q4 pp. 1956-1960 doi
  3. Article
    Web of Science & Scopus
    Model for Estimating the Morphological Characteristics of Structureless Areas of Pigmented Skin Neoplasms // Physics of Atomic Nuclei, 2022 Vol. 85, No. 11, Q4 pp. 1943-1947 doi
  4. Article
    Web of Science & Scopus
    Model for Assessing the Asymmetry of a Pigmented Neoplasm // Physics of Atomic Nuclei, 2022 Vol. 85, No. 11, Q4 pp. 1951-1955 doi
  5. Article
    Web of Science & Scopus
    Investigation of Textural Features for the Problems of Bone Marrow Cell Recognition in Information-Measuring Systems of Oncohematology // Measurement Techniques, 2022 Q4 doi
  6. Article
    Web of Science & Scopus
    A Model for Recognizing Structureless Hyperpigmented Areas in Dermato-Oncology // Biomedical Engineering, 2022 Vol. 55, No. 5, Q3 pp. 346-349 doi
  7. Article
    Web of Science & Scopus
    The Use of Laser Flow Cytometry and Light Microscopy for Assessing the Effect of Treatment of Acute Megakaryoblastic Leukemia // Biomedical Engineering, 2022 Q3 doi
  8. Article
    Web of Science & Scopus
    Model for Detecting Globules in Images of Skin Neoplasms // Mathematical Models and Computer Simulations, 2022 Vol. 14, No. 3, Q3 pp. 411-418 doi
  9. Article
    Web of Science & Scopus
    A Model for Recognition of Dermatoscopic Points in Images of Skin Neoplasms // Biomedical Engineering, 2021 Vol. 55, No. 2, Q3 pp. 112-115 doi
  10. Article
    Web of Science & Scopus
    Nevus spitz: A review of the literature and clinical cases from practice // Klinicheskaya Dermatologiya i Venerologiya, 2021 Vol. 20, No. 2, Q4 pp. 50-58 doi
  11. Article
    Web of Science & Scopus
    Detection of Influenza Virus Using a SOI-Nanoribbon Chip, Based on an N-Type Field-Effect Transistor // Biosensors, 2021 Vol. 11, No. 4, Q2 doi
  12. Article
    Web of Science & Scopus
    Detection and monitoring of minimal residual disease in acute megakaryoblastic leukemia in children // Journal of Modern Oncology, 2021 Vol. 23, No. 1, Q4 pp. 148-155 doi
  13. Article
    Web of Science & Scopus
    Algorithm for the Analysis of Pigment Network Characteristics in Diagnosing Melanoma // Mathematical Models and Computer Simulations, 2021 Vol. 13, No. 5, Q3 pp. 861-869 doi
  14. Article
    Web of Science & Scopus
    Detection of Circles as Structural Elements in Dermatoscopic Images of Skin Neoplasms in the Diagnosis of Melanoma // Biomedical Engineering, 2021 Q3 doi
  15. Article
    Web of Science & Scopus
    Application of atomic force microscopy in biology and medicine // Journal of Physics: Conference Series, 2021 Vol. 2058, No. 1, Q4 doi
  16. Article
    Web of Science & Scopus
    Integrated information and measurement system for the diagnosis of acute leukemia and minimal residual disease based on computer microscopy, flow laser cytofluorimetry and artificial intelligence // Journal of Physics: Conference Series, 2021 Vol. 2058, No. 1, Q4 doi
  17. Article
    Web of Science & Scopus
    Classification of bone marrow cells in the diagnosis of acute lymphoblastic leukemia // Journal of Physics: Conference Series, 2021 Vol. 2058, No. 1, Q4 doi
  18. Article
    Web of Science & Scopus
    ANALYSIS OF BIOLOGICAL OBJECTS BY DIGITAL OPTICAL MICROSCOPY USING NEURAL NETWORKS // Bulletin of the Lebedev Physics Institute, 2021 Vol. 48, No. 10, Q4 pp. 332-336 doi
  19. Article
    Web of Science & Scopus
    Model of a Decision-Making System for the Diagnosis of Melanoma Using Artificial Intelligence // Biomedical Engineering, 2021 Vol. 55, No. 3, Q3 pp. 215-218 doi
  20. Article
    Web of Science & Scopus
    Artificial Intelligence Technologies in the Diagnosis of Acute Lymphoblastic Leukemia and Minimal Residual Disease // Biomedical Engineering, 2021 Q3 doi
  21. Article
    Web of Science & Scopus
    Color recognition of dermatoscopic images of skin neoplasms // Journal of Physics: Conference Series, 2021 Vol. 2058, No. 1, Q4 doi
  22. Article
    Web of Science & Scopus
    SPITZ nevus (juvenile melanoma) in the pediatricians practice: Clinical picture, diagnosis, prognosis and treatment // Pediatriya - Zhurnal im G.N. Speranskogo, 2021 Vol. 100, No. 1, Q4 pp. 166-172 doi
  23. Article
    Web of Science & Scopus
    A Model for Detecting Structural Elements – Lines – in Digital Images in Oncodermatology // Measurement Techniques, 2021 Q4 doi
  24. Article
    Web of Science & Scopus
    Model for Estimating the Heterogeneity of the Distribution of Globule Characteristics in Images of Skin Neoplasms // Measurement Techniques, 2021 Q4 doi
  25. Article MODEL OF A DECISION-MAKING SYSTEM FOR THE DIAGNOSIS OF MELANOMA USING ARTIFICIAL INTELLIGENCE // 2021
  26. Article A MODEL FOR RECOGNITION OF DERMATOSCOPIC POINTS IN IMAGES OF SKIN NEOPLASMS // 2021
  27. Article ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN THE DIAGNOSIS OF ACUTE LYMPHOBLASTIC LEUKEMIA AND MINIMAL RESIDUAL DISEASE // 2021

Showing conferences for last 3 years

Conferences not found

Повышение квалификации

October 28, 2019 — October 30, 2019 Engineering and physical technologies of Biomedicine (in English) (18 hours) NRU MEPhI, Moscow

Grants

May 2019 — Dec 2021 Methods and models of digital image processing of skin neoplasms using artificial intelligence technologies for the diagnosis of melanoma Russian Science Foundation (RGNF)
Sep 2018 — Feb 2022 Methods and models of artificial intelligence for solving interdisciplinary fundamental problems of diagnosis of lymphoproliferative diseases and minimal residual disease in oncology. Russian Foundation for Basic Research (RFBR)

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