• DocumentCode
    2594340
  • Title

    Detecting Virulent Cells of Cryptococcus Neoformans Yeast: Clustering Experiments

  • Author

    Jinshuo Liu ; Van Der Putten, Peter ; Hagen, F. ; Xinmeng Chen ; Boekhout, T. ; Verbeek, Fons J.

  • Author_Institution
    Comput. Sch., Wuhan Univ.
  • Volume
    1
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    1112
  • Lastpage
    1115
  • Abstract
    The yeast cryptococcus neoformans can cause dangerous infections such as meningitis. The presence of a thick capsule is shown to be correlated with virulence of a yeast cell. This paper reports on our approach towards developing a classifier for detecting virulent cells in images. We present our methods for creating samples, collecting images, preprocessing the images, identifying cells and creating features for each cell. Unsupervised clustering experiments have provided preliminary evidence that our methods results in features that can successfully be used to group and distinguish virulent from normal cells. In our future work we plan to use the same methods and feature set to build supervised classification models
  • Keywords
    biology computing; image classification; microorganisms; pattern clustering; dangerous infection; unsupervised clustering experiment; virulent cell detection; yeast cell virulence; yeast cryptococcus neoformans; Art; Capacitive sensors; Computer science; Cryptography; Data mining; Feature extraction; Fungi; Image analysis; Ink; Pathogens;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2006. ICPR 2006. 18th International Conference on
  • Conference_Location
    Hong Kong
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2521-0
  • Type

    conf

  • DOI
    10.1109/ICPR.2006.437
  • Filename
    1699084