idw – Informationsdienst Wissenschaft

Nachrichten, Termine, Experten

Grafik: idw-Logo
Grafik: idw-Logo

idw - Informationsdienst
Wissenschaft

Science Video Project
idw-Abo

idw-News App:

AppStore

Google Play Store



Instance:
Share on: 
03/25/2014 13:24

Automatic Tracking of Biological Particles in Cell Microscopy Images

Marietta Fuhrmann-Koch Kommunikation und Marketing
Ruprecht-Karls-Universität Heidelberg

    In order to track the movements of biological particles in a cell, scientists at Heidelberg University and the German Cancer Research Center have developed a powerful analysis method for live cell microscopy images. This so-called probabilistic particle tracking method is automatic, computer-based and can be used for time-resolved two- and three-dimensional microscopy image data. The Heidelberg method achieved the best overall result in an international competition that compared different methods for image analysis. The competition results were recently published in the journal “Nature Methods”.

    Press Release
    Heidelberg, 25 March 2014

    Automatic Tracking of Biological Particles in Cell Microscopy Images
    Heidelberg scientists develop powerful automatic method for image analysis

    In order to track the movements of biological particles in a cell, scientists at Heidelberg University and the German Cancer Research Center have developed a powerful analysis method for live cell microscopy images. This so-called probabilistic particle tracking method is automatic, computer-based and can be used for time-resolved two- and three-dimensional microscopy image data. The Heidelberg method achieved the best overall result in an international competition that compared different methods for image analysis. The competition results were recently published in the journal “Nature Methods”.

    The task of how to automatically track the movement of biological particles such as viruses, cell vesicles or cell receptors is of key importance in biomedical applications for the quantitative analysis of intracellular dynamic processes. Manually analysing time-resolved microscopy images with hundreds or thousands of moving objects is not feasible. In recent years, therefore, there has been increasing emphasis on the development of automatic image analysis methods for particle tracking. These methods are computer-based and determine the positions of particles over time. To objectively compare the performance of these methods, an international competition was organised in 2012 for the first time.

    A total of 14 research teams participated in the “Particle Tracking Challenge”, including Dr. William J. Godinez and Associate Professor Dr. Karl Rohr from Heidelberg University and the German Cancer Research Center (DKFZ). In the competition, the different image analysis methods were applied to a broad spectrum of two- and three-dimensional image data and their performance was quantified using different measures. The three best methods were determined for each category of data. With a total of 150 “Top 3 Rankings”, the Heidelberg scientists achieved the best overall result.

    The particle tracking method developed by Dr. Godinez and Dr. Rohr is based on a mathematically sound method from probability theory that takes into account uncertainties in the image data, e.g. due to noise, and exploits knowledge of the application domain. “Compared to deterministic methods, our probabilistic approach achieves high accuracy, especially for complicated image data with a large number of objects, high object density and a high level of noise,” says Dr. Rohr. The method enables determining the movement paths of objects and quantifies relevant parameters such as speed, path length, motion type or object size. In addition, important dynamic events such as virus-cell fusions are detected automatically.

    Karl Rohr heads the “Biomedical Computer Vision“ (BMCV) research group that develops computer science methods to automatically analyse cell microscopy images as well as radiological images. This group is located at the BioQuant Center of Heidelberg University. It is part of the department “Bioinformatics and Functional Genomics“ at Heidelberg University's Institute of Pharmacy and Molecular Biotechnology as well as the division “Theoretical Bioinformatics“ of the DKFZ, both of which are headed by Prof. Dr. Roland Eils. William J. Godinez is pursuing postdoctoral work in the BMCV group on the development of computer-based particle tracking methods.

    Internet information:
    http://www.bioquant.uni-heidelberg.de/bmcv

    Publication in Nature Methods:
    N. Chenouard, I. Smal, F. de Chaumont, M. Maška, I.F. Sbalzarini, Y. Gong, J. Cardinale, C. Carthel, S. Coraluppi, M. Winter, A.R. Cohen, W.J. Godinez, K. Rohr, Y. Kalaidzidis, L. Liang, J. Duncan, H. Shen, Y. Xu, K.E.G. Magnusson, J. Jaldén, H.M. Blau, P. Paul-Gilloteaux, P. Roudot, C. Kervrann, F. Waharte, J.Y. Tinevez, S.L. Shorte, J. Willemse, K. Celler, G.P. van Wezel, H.W. Dan, Y.S. Tsai, C. Ortiz de Solórzano, J.C. Olivo-Marin, E. Meijering: Objective comparison of particle tracking methods. Nature Methods (March 2014), Volume 11, Issue 3, 281-289, doi: 10.1038/nmeth.2808

    Captions:
    Particle_Tracking_1.jpg und Particle_Tracking_2.jpg
    Tracking result for virus particles. Microscopy image of time-resolved data overlaid with automatically determined movement paths of HIV-1 particles, shown in different colours. The small boxes indicate the positions found at the current time point. Image two shows an enlarged section of the area marked by the white rectangle in image one.
    Source: W.J. Godinez, K. Rohr

    Contact:
    Associate Professor Dr. Karl Rohr
    “Biomedical Computer Vision” research group
    Phone: +49 6221 51-298
    k.rohr@uni-hd.de, k.rohr@dkfz.de

    Communications and Marketing
    Press Office, phone: +49 6221 54-2311
    presse@rektorat.uni-heidelberg.de


    Images

    Tracking result for virus particles
    Tracking result for virus particles
    Source: W.J. Godinez, K. Rohr
    None

    Tracking result for virus particles – an enlarged section
    Tracking result for virus particles – an enlarged section
    Source: W.J. Godinez, K. Rohr
    None


    Criteria of this press release:
    Journalists
    Biology, Electrical engineering, Medicine
    transregional, national
    Research results
    English


     

    Help

    Search / advanced search of the idw archives
    Combination of search terms

    You can combine search terms with and, or and/or not, e.g. Philo not logy.

    Brackets

    You can use brackets to separate combinations from each other, e.g. (Philo not logy) or (Psycho and logy).

    Phrases

    Coherent groups of words will be located as complete phrases if you put them into quotation marks, e.g. “Federal Republic of Germany”.

    Selection criteria

    You can also use the advanced search without entering search terms. It will then follow the criteria you have selected (e.g. country or subject area).

    If you have not selected any criteria in a given category, the entire category will be searched (e.g. all subject areas or all countries).