A data driven and landmark-free image alignment approach to correct spatial shift in bacterial time series. This work was funded by the German-Canadian DFG International Research Training Group GRK 1906/1 and the “Phenotypic Heterogeneity and Sociobiology of Bacterial Populations” DFG SPP1617.
The employed datasets are 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.
For better reproducibility the versions that were used for development are mentioned in parentheses.
- Python (2.7.10)
- OpenCV (2.4.9)
- Image Processing SciKit (skimage 0.11dev)
- Python Imaging Library (PIL 1.1.7)
# Set file permissions
$ chmod +x main.py
# Run alignment on a folder containing all image files
# Formatted by channel : luminance, red, green, blue as c1, c2, c3, c4 respectively for every time point
$./main.py -i ../data/img_folder/ -p
# -h --help Prints this
# -i --input Supplies a directory containing the data
# -p --param Flag for treating imagesIf you use this software, please consider citing the following paper: Hattab, G., Schlüter, J.P., Becker, A. and Nattkemper, T.W., 2017. Vicar: an adaptive and landmark-free registration of time lapse image data from microfluidics experiments. Frontiers in genetics, 8, p.69.
@Article{hattab18vicar,
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"
}
The MIT License (MIT)
Copyright (c) Georges Hattab
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