Automated cell tracking and analysis in phase-contrast videos (iTrack4U): development of Java software based on combined mean-shift processes.
PLoS ONE. 2013-11-27; 8(11): e81266
DOI: 10.1371/journal.pone.0081266
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1. PLoS One. 2013 Nov 27;8(11):e81266. doi: 10.1371/journal.pone.0081266.
eCollection 2013.
Automated cell tracking and analysis in phase-contrast videos (iTrack4U):
development of Java software based on combined mean-shift processes.
Cordelières FP(1), Petit V, Kumasaka M, Debeir O, Letort V, Gallagher SJ, Larue
L.
Author information:
(1)Institut Curie, CNRS UMR3348, plate-forme IBISA d’imagerie cellulaire et
tissulaire, Orsay, France.
Cell migration is a key biological process with a role in both physiological and
pathological conditions. Locomotion of cells during embryonic development is
essential for their correct positioning in the organism; immune cells have to
migrate and circulate in response to injury. Failure of cells to migrate or an
inappropriate acquisition of migratory capacities can result in severe defects
such as altered pigmentation, skull and limb abnormalities during development,
and defective wound repair, immunosuppression or tumor dissemination. The ability
to accurately analyze and quantify cell migration is important for our
understanding of development, homeostasis and disease. In vitro cell tracking
experiments, using primary or established cell cultures, are often used to study
migration as cells can quickly and easily be genetically or chemically
manipulated. Images of the cells are acquired at regular time intervals over
several hours using microscopes equipped with CCD camera. The locations (x,y,t)
of each cell on the recorded sequence of frames then need to be tracked. Manual
computer-assisted tracking is the traditional method for analyzing the migratory
behavior of cells. However, this processing is extremely tedious and
time-consuming. Most existing tracking algorithms require experience in
programming languages that are unfamiliar to most biologists. We therefore
developed an automated cell tracking program, written in Java, which uses a
mean-shift algorithm and ImageJ as a library. iTrack4U is a user-friendly
software. Compared to manual tracking, it saves considerable amount of time to
generate and analyze the variables characterizing cell migration, since they are
automatically computed with iTrack4U. Another major interest of iTrack4U is the
standardization and the lack of inter-experimenter differences. Finally, iTrack4U
is adapted for phase contrast and fluorescent cells.
DOI: 10.1371/journal.pone.0081266
PMCID: PMC3842324
PMID: 24312283 [Indexed for MEDLINE]