Objective comparison of particle tracking methods

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

On the Fertilizer Three Element Treatments of Rice Crops Sampled for Leaf Analysis by Field

Rice crops field experiment grown on fertilizer three element treatments was carried out in 1952-54. at Fukigami, Takigun, Hyogo Pref. The effect of N element was most remarkable from 1st year in total yield, and that of P was not significant until 3rd year. K effect was not significant in 1st year, but gradually became significant since 2nd year. Details of growth and yield results are shown in the tables

Objective comparison of particle tracking methods

International audienceParticle 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