• DocumentCode
    2099742
  • Title

    Detection of micro nucleus in human lymphocytes altered by Gaussian noise using convolution neural network

  • Author

    Paliy, Ihor ; Lamonaca, Francesco ; Turchenko, Volodymyr ; Grimaldi, Domenico ; Sachenko, Anatoly

  • Author_Institution
    Res. Inst. of Intell. Comput. Syst., Ternopil Nat. Economic Univ., Ternopil, Ukraine
  • fYear
    2011
  • fDate
    10-12 May 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    The application of convolution neural network for the detection of Micro Nucleuses (MNs) in human lymphocyte images acquired by an image flow cytometer is considered in this paper. The existing method of detection, IMAQ Match Pattern, is described. The training algorithm of the convolution neural network (CNN) and the detection procedure are presented. The performance of both detection methods are explored on the set of human lymphocyte images at the different intensities of Gaussian noise alteration. Our results show that the IMAQ Match Pattern method provides low detection rates of the MNs at the presence even of the small intensity of Gaussian noise alteration. Instead the CNN provides much higher detection rates at the different intensities of Gaussian noise alteration.
  • Keywords
    Gaussian noise; cellular biophysics; neural nets; Gaussian noise; convolution neural network; human lymphocytes; image flow cytometer; micro nucleus; Artificial neural networks; Convolution; Feature extraction; Gaussian noise; Humans; Pattern matching; Training; Convolutional neural network; Gaussian noise; Image processing; Micro nucleus detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Instrumentation and Measurement Technology Conference (I2MTC), 2011 IEEE
  • Conference_Location
    Binjiang
  • ISSN
    1091-5281
  • Print_ISBN
    978-1-4244-7933-7
  • Type

    conf

  • DOI
    10.1109/IMTC.2011.5944240
  • Filename
    5944240