A Model-Based Hematopoietic Stem Cell Tracker

  • Nezamoddin N. Kachouie
  • Paul Fieguth
  • John Ramunas
  • Eric Jervis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3656)


A better understanding of cell behavior is very important in drug and disease research. Cell size, shape, and motility may play a key role in stem-cell specialization or cancer development. However the traditional method of inferring these values manually is such an onerous task that automated methods of cell tracking and segmentation are in high demand. Image cytometry is a practical approach to measure and extract cell properties from large volumes of microscopic cell images. As an important application of image cytometry, this paper presents a probabilistic model based cell tracking method to locate and associate HSCs in phase contrast microscopic images. The proposed cell tracker has been successfully applied to track HSCs based on the most probable identified cell locations and probabilistic data association.


Mantle Cell Lymphoma Cell Boundary Cell Tracking Boundary Pixel Image Cytometry 
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 2005

Authors and Affiliations

  • Nezamoddin N. Kachouie
    • 1
  • Paul Fieguth
    • 1
  • John Ramunas
    • 2
  • Eric Jervis
    • 2
  1. 1.Department of Systems Design EngineeringUniversity of WaterlooWaterlooCanada
  2. 2.Department of Chemical EngineeringUniversity of WaterlooWaterlooCanada

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