Objective Comparison of Particle Tracking Methods

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Authors

CHENOUARD Nicolas SMAL Ihor DE CHAUMONT Fabrice MAŠKA Martin SBALZARINI Ivo F GONG 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 E G JALDÉN Joakim BLAU Helen 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-SOLÓRZANO Carlos OLIVO-MARIN Jean-Christophe MEIJERING Erik

Year of publication 2014
Type Article in Periodical
Magazine / Source Nature Methods
MU Faculty or unit

Faculty of Informatics

Citation
Web http://dx.doi.org/10.1038/nmeth.2808
Doi http://dx.doi.org/10.1038/nmeth.2808
Field Informatics
Keywords Particle tracking;performance comparison;fluorescence microscopy
Description Particle tracking is of key importance for quantitative analysis of intracellular dynamic processes from time-lapse microscopy image data. Because manually detecting and following large numbers of individual particles is not feasible, automated computational methods have been developed for these tasks by many groups. Aiming to perform an objective comparison of methods, we gathered the community and organized an open competition in which participating teams applied their own methods independently to a commonly defined data set including diverse scenarios. Performance was assessed using commonly defined measures. Although no single method performed best across all scenarios, the results revealed clear differences between the various approaches, leading to notable practical conclusions for users and developers.
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