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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.