Automated Tracking of Cell Movement in Microscopic Images
Posted December 12 2017
Researchers from Heidelberg developed high-performance image analysis method

To track cell movements automatically in microscopic images, researchers from Heidelberg University and the German Cancer Research Center (DKFZ) have developed a new computer-based image analysis method. With this analysis method, Privatdozent Dr. Karl Rohr and Dr. Nathalie Harder participated in an international benchmark test for various “Cell Tracking Challenges” and succeeded with the best results for the identification of the cell cycle, which is used to quantify cell growth, and were in total ranked among the “top 3 positions” for various image categories.


With the help of this method developed by Dr. Rohr and Dr. Harder, crucial biological processes such as cell migration and cell growth can be quantified. These processes play a central role in the development of diseases. The cell-tracking method combines methods for segmentation and spatio-temporal optimization for the analysis of microscopic images: Cells are identified automatically, correspondences within a sequence of images are determined and cell divisions get detected. Besides that, various information of cell movement such as the movement track, the velocity, and the covered distance of the cell can be determined.


The results of the international benchmark test with 21 methods from 11 countries have been published in the journal “Nature Methods”.


Based on the following article 11. December 2017 (German version only):



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Privatdozent Dr. Karl Rohr

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Abteilung Theoretische Bioinformatik

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Original Publication:

V. Ulman et al.: An Objective Comparison of Cell Tracking Algorithms. Nature Methods (published online 30 October 2017), doi:10.1038/nmeth.4473