delta2 2.0.2

Segments and tracks bacteria

DeLTA

NOTE This is version 2 of the DeLTA pipeline. For version 1, please check out branch 'version1'

DeLTA (Deep Learning for Time-lapse Analysis) is a deep learning-based image processing pipeline for segmenting and tracking single cells in time-lapse microscopy movies.

:scroll: To get started check out the documentation at delta.readthedocs.io

:bug: If you encounter bugs or have questions about the software, please use Gitlab's issue system

For the latest hotness check out the dev branch. You can also quickly test DeLTA on our data or your own with Google Colab for free here

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See also our papers and manuscript for more details:

Version 2 preprint: O’Connor, O. M., Alnahhas, R. N., Lugagne, J.-B., & Dunlop, M. J. (2021). DeLTA 2.0: A deep learning pipeline for quantifying single-cell spatial and temporal dynamics. BioRxiv, 2021.08.10.455795

Version 1 paper: Lugagne, J.-B., Lin, H., & Dunlop, M. J. (2020). DeLTA: Automated cell segmentation, tracking, and lineage reconstruction using deep learning. PLOS Computational Biology, 16(4), e1007673.