Objective comparison of particle tracking methods

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Chenouard, Nicolas | Smal, Ihor | de Chaumont, Fabrice | Maska, Martin | Sbalzarini, Ivo F. | Gon, Yuanhao | Cardinale, Janick | Carthel, Craig | Coraluppi, Stefano | Winter, Mark | Cohen, Andrew R. | Godinez, William J. | Rohr, Karl | Kalaidzidis, Yannis | Liang, Liang | Duncan, James | Shen, Hongying | Xu, Yingke | Magnusson, Klas | Jalden, Joakim | Blau, Hélène M. | Paul-Gilloteaux, Perrine | Roudot, Philippe | Kervrann, Charles | Waharte, François | Tinevez, Jean-Yves | Shorte, Spencer L. | Willemse, Joost | Celler, Katherine | van Wezel, Gilles P. | Dan, Han-Wei | Tsai, Yuh-Show | Ortiz de Solorzano, Carlos | Olivo-Marin, Jean-Christophe | Meijering, Erik

Edité par CCSD ; Nature Publishing Group -

International audience. Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy data. As detecting and following large numbers of individual particles by hand is not feasible, state-of-the-art computational methods for these tasks have been developed by many groups worldwide. Aspiring an objective comparison of methods, we gathered the community and organized, for the first time, an open competition, in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios, and performance was assessed using commonly defined measures. While no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to important practical conclusions for users and developers.

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