Here you can find various information about the algorithm
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:
Available manuals / knowledge
Here you can find available documentation on how to use the plugins.
Matlab plugin userguide
CellProfiler plugin user guide
Here you can download an official user guide for CellProfiler plugin. It covers various aspects of CellStar algorithm usage within CellProfiler. Please download the entire plugin package for CellProfiler pipeline examples presented in the above guide.
Comparision of various algorithms using YIT
Before developing CellStar algorithm we spend some time in comparing existing solutions dedicated to segmentation and tracking budding yeast cells in brightfield images. It gave a rise to Yeast Image Toolkit (YIT) project. Please check out the YIT webpage for more information.
Take a look and enjoy!
Segmentation of a single frame
Illustration of brightfield to segmented image conversion with CellStar.
Segmentation and tracking of time-lapse movie
CellStar algorithm. The original images are displayed on the right, segmentation and tracking is overlaid on the images on the left.
Here you can find implementations of the algorithm
Stable version 1.2.3 for CellProfiler 2.2.0 is available to download here.
Stable version 1.3.1 for CellProfiler 3.1.8 is available to download here.
Stable version 2.0.2 for CellProfiler 4.2.4 is available to download here.
Those packages include not only CellStar plugin but also examples of its usage to guide users on how to achieve best segmentation on a given type of imagery.
How to acknowledge our work?
If you use our work, please use one of these citation in your manuscript to support us
If you used CellProfiler implementation
Mroz&Kaczmarek et al., in preparation
These organizations and people supported our development
University of Lile
Cristian VERSARI, Kiril BATMANOV, Cedric LHOUSSAINE
Szymon STOMA, Simon NOERRELYKKE, Gabor CSUCS
Pascal HERSEN, Artemis LLAMOSI, Matt DEYELL
University of Wroclaw
Filip MROZ, Adam KACZMAREK, Pawel RYCHLIKOWSKI
Anne CARPENTER, Lee KAMENTSKY, Mark BRAY
Please choose your contact person
INRIA / CNRS, France
Gregory Batt / Pascal Hersen
Please contact for the details of imaging expertise, biological datasets and microfluidics rutines.
Computer Science Laboratory of Lille, France
Please contact for the details of algorithm and Matlab GUI specific questions.
Image & Data Analysis Unit of Scientific Center for Optical and Electron Microscopy of ETH, Switzerland
Please contact for the details of CellProfiler implementation and integration with pipelines / tools.
Design: Szymon Stoma