Apoptosis Detection for Non-adherent Cells in Time-lapse Phase Contrast Microscopy

  • Seungil Huh
  • Takeo Kanade
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8150)


This paper proposes a vision-based method for detecting apoptosis (programmed cell death), which is essential for non-perturbative monitoring of cell expansion. Our method targets non-adherent cells, which float or are suspended freely in the culture medium—in contrast to adherent cells, which are attached to a petri dish. The method first detects cell regions and tracks them over time, resulting in the construction of cell tracklets. For each of the tracklets, visual properties of the cell are then examined to know whether and when the tracklet shows a transition from a live cell to a dead cell, in order to determine the occurrence and timing of a cell death event. For the validation, a transductive learning framework is adopted to utilize unlabeled data in addition to labeled data. Our method achieved promising performance in the experiments with hematopoietic stem cell (HSC) populations, which are currently in clinical use for rescuing hematopoietic function during bone marrow transplants.


Dead Cell Unlabeled Data Death Event Cell Death Event Slide Window Method 
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 2013

Authors and Affiliations

  • Seungil Huh
    • 1
  • Takeo Kanade
    • 1
  1. 1.Lane Center for Computational Biology and Robotics InstituteCarnegie Mellon UniversityUSA

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