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PhagoSight: An Open-Source MATLAB® Package for the Analysis of Fluorescent Neutrophil and Macrophage Migration in a Zebrafish Model

Figure 6

Validation of the algorithms with synthetic and real data sets.

In all cases the sets were automatically tracked with PhagoSight; input thresholds were automatically determined and then modified from 40% to 140% of the original values to test the robustness against variation of that input parameter. (a) Distance from the automatically generated tracks to the gold standard (DAG) for the synthetic data set, BD corresponds to the Bhattacharyya distance between background and neutrophils. (b) Distance from the gold standard to the automatically generated tracks (DGA) for the synthetic data set. (c) DAG for the real data set, (d) DGA for the real data set. High distances for the synthetic sets are due to low thresholds that interpret noise as neutrophils. The increase in DGA in (d) is caused by higher levels that do not detect faint neutrophils, this in turn will reduce DAG as with the higher threshold, the neutrophils which are detected are the brightest and thus the tracking is more precise.

Figure 6