About SuperSegger

Welcome to the SuperSegger wiki!

SuperSegger is a completely automated MATLAB-based image processing and analysis suite for time lapse bacterial fluorescence imaging.

Some of the basic uses of SuperSegger:

• Well suited for the high-throughput analysis of cell-cycle dynamics of proteins and complexes by time-lapse fluorescence microscopy in single bacterial cells.
• Highly reliable in segmenting cells in contact with other cells.
• Optimized for rod-like bacterial cells.
• Incorporates machine-learning algorithms, to optimize cellular boundaries for different cell shapes.
• Links cells from frame-to-frame in time-lapse imaging, during which it applies error correction to correct segmentation errors that may arise in segmentation.
• Identifies mothers, daughters and sisters. At any frame the cell lineage in the past and future of timelapse can be tracked.
• Identifies cells for which both birth and division were observed.
• Identifies cells in contact with a cell.
• Calculates fluorescence statistics and identifies foci in fluorescence images.
• Extracts a variety of information saved per individual cell, per frame and at a table of cells versus life pertaining information (clist).
• Includes post-processing tools at both the individual cell level and the population level, such as fluorescence kymographs, cell towers, plotting tools for a variety of fields, and consensus images.
• Allows the possibility of displaying information for subpopulations of the dataset, by gating on different variables.
• It is modular, allowing partial use according to the needs of the user
• It can either be run programmatically or through a graphical user interface.