CellStar. Segmentation & tracking.

Automatic tracking of cells in time-lapse microscopy is required to investigate a multitude of biological questions. To limit manipulations during cell line preparation and phototoxicity during imaging, brightfield imaging is often considered. Since the segmentation and tracking of cells in brightfield images is considered to be a difficult and complex task, a number of software solutions have been already developed.

CellStar is one of such algorithms. It is optimized to segment and track images of budding yeast cells growing in monolayer (e.g. images from microfluidic chambers), however the algorithm can be also used to track other round objects (in brightfield as well as fluorescent images).

CellStar is provided in two independent implementations:

• Matlab plugin - it is a version optimized for manual curation of  segmentation and tracking datasets. It contains GUI allowing to easily correct results of automatic tracking and segmentation. We recommend to use this implementation when you need very low error rates (e.g. in problems related to cell lineage analysis). To use this plugin you will need commercially available program Matlab together with image analysis and optionally optimization toolkits. 

• CellProfiler plugin - it is a version seamlessly integrated with CellProfiler, free open-source software designed to enable biologists without training in computer vision or programming to quantitatively measure phenotypes from thousands of images automatically. This version does not allow for manual correction of segmentation / trajectories. On the other hand, it does not require any commercial software and comes with all analytic power of CellProfiler. Furthermore it has autoadaptation of its parameters integrated with CellProfiler. We recommend to use this implementation if you would like to stay in the ecosystem of CellProfiler.

Here you can find available documentation on how to use the plugins.