Segmentation and Cell Tracking of Breast Cancer Cells

  • Adele P. Peskin
  • Daniel J. Hoeppner
  • Christina H. Stuelten
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6938)


We describe a new technique to automatically segment and track the cell images of a breast cancer cell line in order to study cell migration and metastasis. Within each image observable cell characteristics vary widely, ranging from very bright completely bounded cells to barely visible cells with little to no apparent boundaries. A set of different segmentation algorithms are used in series to segment each cell type. Cell segmentation and cell tracking are done simultaneously, and no user selected parameters are needed. A new method for background subtraction is described and a new method of selective dilation is used to segment the barely visible cells. We show results for initial cell growth.


Cell Boundary High Standard Deviation Bright Pixel Visible Cell Cell Segmentation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Adele P. Peskin
    • 1
  • Daniel J. Hoeppner
    • 2
  • Christina H. Stuelten
    • 2
  1. 1.NISTBoulderUSA
  2. 2.NIHBethesdaUSA

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