CYCASP employs two novel abstractions applied to the domain of microfluidics. It is a three steps framework comprising:
- preprocessing (denoising, contrast enhancement, etc)
- particle (finding, tracking, linking, etc)
- patch lineage graphs (finding, propogating, splitting, merging)
The real data is available under The Open Data Commons Attribution License (ODC-By) v1.0.
Schlueter, J. - P., McIntosh, M., Hattab, G., Nattkemper, T. W., and Becker, A. (2015). Phase Contrast and Fluorescence Bacterial Time-Lapse Microscopy Image Data. Bielefeld University. doi:10.4119/unibi/2777409.
The synthetic data is not yet published.
# Set file permissions
$ chmod +x cycasp.py
# Run CYCASP on a folder containing all image files
# Formatted by channel : red, green, blue as c2, c3, c4 respectively for every time point
$ ./cycasp.py -i img_directory/ -g 100
# Or on a CSV file containing particle positions and trajectory IDs
# with default thresholds for the fives metrics (euclidean distance, channel specifc differences and time window)
$ ./cycasp.py -f filename.csv -t 2
# -h, --help show this help message and exit
# -v, --version show program's version number and exit
# -i, --input run CYCASP on the supplied directory
# -f, --file run only step 3 of the method given as a CSV file
# -d diameter estimate (default 11)
# -e euclidean distance (default 10, cf. section above)
# -r -g -b channel specific differences (default 50 for each)
# -t time window for merges (default 10 time points)
For better reproducibility the versions that were used for development are mentioned in parentheses.
- Python (2.7.11)
- OpenCV (3.1.0-dev)
- pims (0.2.2)
- pyqtgraph (0.9.10)
- trackpy (u'0.3.0rc1')
- networkx (1.9.1)
- Scipy (0.16.0)
- pandas (0.16.2)
- json (2.0.9)
If you use this software, please consider citing the following paper: Hattab, G., Wiesmann, V., Becker, A., Munzner, T. and Nattkemper, T.W., 2018. a novel Methodology for characterizing cell subpopulations in automated Time-lapse Microscopy. Frontiers in bioengineering and biotechnology, 6, p.17.
@Article{hattab18cycasp,
Author="Hattab, G. and Wiesmann, V. and Becker, A. and Munzner, T. and Nattkemper, T. W. ",
Title="{{A} {N}ovel {M}ethodology for {C}haracterizing {C}ell {S}ubpopulations in {A}utomated {T}ime-lapse {M}icroscopy}",
Journal="Front Bioeng Biotechnol",
Year="2018",
Volume="6",
Pages="17"
}
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Copyright (c) Georges Hattab
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