• DocumentCode
    3114316
  • Title

    Adaptive marker-based watershed segmentation approach for T cell fluorescence images

  • Author

    Ge Fan ; Jian-Wei Zhang ; Yong Wu ; Dong-Fa Gao

  • Author_Institution
    Sch. of Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
  • Volume
    02
  • fYear
    2013
  • fDate
    14-17 July 2013
  • Firstpage
    877
  • Lastpage
    883
  • Abstract
    It is intractable problem to segment the fluorescence image of T-cells with different sizes, irregular shape, and severe overlapping by conventional marker-based watershed segmentation. In this paper, Adaptive Marker-controlled Watershed method (AMWS) will be proposed. The Otsu strategy firstly is performed twice in a row to capture as many T-cells as possible. Then based on T-cells´ roundish shape, an improved strategy to obtain markers adaptively is present using the evaluation of the segmentation result. This strategy is able to mark the single cell and the overlapping cells accurately. It avoids the ineffectiveness of ultimate erosion which is due to different sizes of cells. The experimental results show that the proposed strategy in this paper can effectively avoid over-segmentation and under-segmentation thus improves both accuracy and robustness of the segmentation.
  • Keywords
    cellular biophysics; erosion; fluorescence; image segmentation; AMWS; Otsu strategy; T cell fluorescence images; T-cells roundish shape; adaptive marker-based watershed segmentation; adaptive marker-controlled watershed method; overlapping cells; single cell; ultimate erosion; Abstracts; Image reconstruction; Image segmentation; Distance reconstruction; Marker-based watershed; T cell fluorescence image;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Machine Learning and Cybernetics (ICMLC), 2013 International Conference on
  • Conference_Location
    Tianjin
  • Type

    conf

  • DOI
    10.1109/ICMLC.2013.6890407
  • Filename
    6890407