Objective comparison of particle tracking methods

作者：Nicolas Chenouard, Ihor Smal, Fabrice de Chaumont, Martin Maška, Ivo F. Sbalzarini, Yuanhao Gong, Janick Cardinale, Craig Carthel, Stefano Coraluppi, Mark Winter, Andrew R. Cohen, William J. Godinez, Karl Rohr, Yannis Kalaidzidis, Liang Liang, James S. Duncan, Hongying Shen, Yingke Xu, Klas E. G. Magnusson, Joakim Jaldén, Helen M. Blau, Perrine Paul-Gilloteaux, Philippe Roudot, Charles Kervrann, François Waharte, Jean-Yves Tinévez, Spencer Shorte, Joost Willemse, Katherine Celler, Gilles P. van Wezel, Han-Wei Dan, Yuh‐Show Tsai, Carlos Ortíz-de-Solórzano, Jean‐Christophe Olivo‐Marín, Erik Meijering · 发表于：Nature Methods · 年份：2014 · DOI：10.1038/nmeth.2808 · 被引用次数：933 · 研究领域：Cell Image Analysis Techniques、Advanced Fluorescence Microscopy Techniques、Single-cell and spatial transcriptomics

The first community competition designed to objectively compare the performance of particle tracking algorithms provides valuable practical information for both users and developers. 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.