• DocumentCode
    3586776
  • Title

    A cell polar body positioning method based on SVM classification

  • Author

    Di Chen ; Mingzhu Sun ; Xin Zhao

  • Author_Institution
    Tianjin Key Lab. of Intell. Robotic (tjKLIR), Nankai Univ., Tianjin, China
  • fYear
    2014
  • Firstpage
    505
  • Lastpage
    509
  • Abstract
    Life science researches and clinical experiment involve the positioning of the polar body. The microinjection operation of mammalian oocytes has been more and more widely used. In many cell manipulation researches, researchers need to operate the polar body of an oocyte under optical microscopy to achieve the purpose of the study. Recently, the automatic detection technology develops rapidly. The orientation of the polar body has a low accuracy rate and poor applicability. This paper proposes a novel method of automatic positioning polar body, which tracks the cell and recognizes the polar body. We obtain the position of the polar body by using support vector machine (SVM). Then we report our automatic positioning system. Moreover, experimental results demonstrate the reliability and accuracy for the method. The method with a high accuracy rate of 97% can be used for positioning a variety of cells.
  • Keywords
    cellular biophysics; image classification; medical image processing; optical microscopy; support vector machines; SVM classification; accuracy rate; automatic detection technology; automatic positioning polar body; automatic positioning system; cell manipulation research; cell polar body positioning method; life science research; mammalian oocytes; microinjection operation; optical microscopy; reliability; support vector machine; Accuracy; Body regions; Feature extraction; Genetics; Microscopy; Sun; Support vector machines;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Robotics and Biomimetics (ROBIO), 2014 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/ROBIO.2014.7090381
  • Filename
    7090381