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Nikitaev, V. G., Nagornov, O. V., Pronichev, A. N., Ovcharova, V. S., Polyakov, E. V., Zaytsev, S. M., & Dmitrieva, V. V. (2018). Research Neural Network to Recognize Blood Cells. KnE Energy, 3(2), 345–349. https://doi.org/10.18502/ken.v3i2.1834

https://doi.org/10.18502/ken.v3i2.1834

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authors

  • V G Nikitaev
    No author data available.
  • O V Nagornov
    No author data available.
  • A N Pronichev
    No author data available.
  • V S Ovcharova
    No author data available.
  • E V Polyakov
    No author data available.
  • S M Zaytsev
    No author data available.
  • V V Dmitrieva
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Published Date

  • Apr 17, 2018

Research Neural Network to Recognize Blood Cells

KnE Energy / The 2nd International Symposium "Physics, Engineering and Technologies for Biomedicine" / Pages 345–349

Abstract

The work investigates a neural network classifier for the differential diagnosis of acute lymphoblastic leukaemia and lymphomas. Specialized software was developed for research. The accuracy characteristics of the recognition of red blood cells were obtained in studies, it allows to judge about the possibility of using neural networks for classification of blood cells.


Keywords: neural network, digital image processing, blood cells detection, acute lymphoblastic leukemia.

References
[1] V.G. Nikitaev, A.N. Pronichev, E.V. Polyakov, V.V. Dmitrieva, N. N. Tupitsyn, M.A. Frenkel, A.V. Mozhenkova, “Application of texture analysis methods to computer microscopy in the visible range of electromagnetic radiation”, Bulletin of the Lebedev Physics Institute, vol. 43, no. 10, pp. 306-308, 2016.


[2] A.N. Pronichev, E.V. Polyakov, N.N. Tupitsyn, M.A. Frenkel, A.V. Mozhenkova, “The use of optical microscope equipped with multispectral detector to distinguish different types of acute lymphoblastic leukemia”, Journal of Physics: Conference Series, vol. 784, no. 1, p. 012003, 2017.


[3] G. Singh, G. Bathla, S. Kaur, “Design of New Architecture to detect leukemia cancer from medical images”, Int J Appl Eng Res, vol. 11, no. 10, pp. 7087-7094, 2016.


[4] A. V. Mozhenkova, N. N. Tupitsin, M. A. Frenkel, N. A. Falaleeva, V. G. Nikitaev and E. V. Polyakov “Computer microscopy in lymphoma diagnostics”, Journal of Physics: Conference Series. vol. 798, no. 1, p. 012126, 2017.


[5] Zakharenko Y. V., V. G. Nikitaev, E. V.Polyakov and S. O. Seldyukov “The method of selection of leukocytes in images of preparations of peripheral blood and bone marrow” //Journal of Physics: Conference Series, vol. 798, no. 1, p. 012127, 2017.


[6] E. V. Polyakov, V. G. Nikitaev, “A method for estimating the accuracy of measurements of optical characteristics of the nuclei of blood cells in the diagnosis of acute leukemia”, In Journal of Physics: Conference Series, vol. 798, no. 1, p. 012128, 2017.


[7] V.G. Nikitaev, O.V. Nagornov, A.N. Pronichev, E.V. Polyakov, V.Y. Sel’chuk, K.S. Chistov, V.N. Blindar’, V.V. Dmitrieva, V.V. Gordeev, “Model of description of leukocytes of peripheral blood based on the optical features of the structure of nuclei” Measurement Techniques, vol. 57, no. 5, pp. 560-563, 2014.


[8] V.G. Nikitaev, O.V. Nagornov, A.N. Pronichev, E.V. Polyakov, V.Y. Sel’chuk, K.S. Chistov, V.N. Blindar’, V.V. Dmitrieva, S.M Zaitsev, V.V. Gordeev, “Study of the Effectiveness of Using Wavelet Analysis in Data-Acquisition Systems for Diagnosis of Acute Leukemias” Measurement Techniques, vol. 57, no. 10, pp. 1203-1208, 2015.


[9] V.G. Nikitaev, O.V. Nagornov, A.N. Pronichev, E.V. Polyakov, V.V. Dmitrieva, “The use of the wavelet transform for the formation of the quantitative characteristics of the blood cells images for the automation of hematological diagnostics” WSEAS Transactions on Biology and Biomedicine, vol. 12, no. 3, pp. 16-19, 2015.


[10] Fast Artificial Neural Network Library[Электронный ресурс]. Дата обращения 24.10.17 URL: http://libfann.github.io/fann/docs/files/fann_cpp-h.html.