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Label Free Cell-Tracking and Division Detection Based on 2D Time-Lapse Images For Lineage Analysis of Early Embryo Development

Computers in Biology and Medicine, 2014

In this paper we report a database and a series of techniques related to the problem of tracking cells, and detecting their divisions, in time-lapse movies of mammalian embryos. Our contributions are: (1) a method for counting embryos in a well, and cropping each individual embryo across frames, to create individual movies for cell tracking; (2) a semi-automated method for cell tracking that works up to the 8-cell stage, along with a software implementation available to the public (this software was used to build the reported database); (3) an algorithm for automatic tracking up to the 4-cell stage, based on histograms of mirror symmetry coecients captured using wavelets; (4) a cell-tracking database containing 100 annotated examples of mammalian embryos up to the 8-cell stage; (5) statistical analysis of various timing distributions obtained from those examples.

Links to paper: Science Direct, PubMed Central

BibTeX:

@article{Cicconet2014CBM,
  author        = {M. Cicconet and M. Gutwein and K. Gunsalus and D. Geiger},
  title         = {Label Free Cell-Tracking and Division Detection
                   Based on 2D Time-Lapse Images
                   For Lineage Analysis of Early Embryo Development},
  journal   	= {Computers in Biology and Medicine},
  year         	= {1 August 2014},
  volume 		= {51},
  pages        	= {24--34}
}

Link to Database Website.