Cell lineage tracing is to track certain cell and all of its progeny. From the 20th century, lineage tracing has provided a predominant method to study organ development, tissue repairiaed cell fate-determination.
Enables cell lineage tracking. MicrobeTracker utilizes cell shape and timelapse information to achieve cell outlining. It can track fluorescently labeled molecules in cell lineages over several generations or in difficult-to-resolve samples, such as densely-packed or filamentous cells, from time-lapse sequences. This tool is delivered with an accessory tool, called SpotFinder, that detects small round spots, generating precise cell coordinates of fluorescently labeled foci inside cells.
Proposes a large collection of generic tools based on mathematical morphology to process binary and grey-level 2D and 3D images, integrated into user-friendly plugins. The library provides different categories of functions, corresponding to standard image processing workflows: (i) image processing and filtering; (ii) segmentation; (iii) post-processing; (iv) quantitative analysis; (v) library re-usability. The cell-resolved data provided by MorphoLibJ will be useful for the analysis of cell lineage, and the modelling of plant growth and morphogenesis in 3D.
Offers an ImageJ based framework which is easily extendible and has the capability to track cell lineages while being specifically designed to handle large cell displacements between frames. The methods are designed for fluorescent cells and have been used to analyse Schizosaccharomyces pombe (lower right), C2C12 mouse stem cells (upper right) or migrating RPE cells.
Allows exploration, analysis and interpretation of single-cell data. Vizardous’ core functionality is to visualize time-resolved, single-cell and population data. It can be used for the automated analysis of data as well. With Vizardous, lineage tree drawings can be upgraded with various, time-resolved cellular characteristics. Associated statistical moments link single cell and the population-average level.
Matches plant cell population and perform plant cell population tracking. This algorithm consists of an interacting multi-model (IMM) filter, based on 3D local graph matching method that exploits cells’ 3D neighborhood structure and spatiotemporal context. It aims to increase the stability of cell tracking by the use of a model allowing a simultaneous tracking of plants cells.
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