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. Author manuscript; available in PMC: 2012 Sep 6.
Published in final edited form as: IEEE Trans Med Imaging. 2011 Aug 22;31(1):117–130. doi: 10.1109/TMI.2011.2165554

Fig. 7.

Fig. 7

Comparison of the tracking errors obtained using three different particle filtering algorithms. These data were obtained using the same moving neurofilament analyzed in Fig. 6 and shown in Fig. 5. The tracking error was defined as the ratio of the actual velocity (obtained by manual tracking) and the estimated velocity (obtained by automated tracking using particle filtering). The tracking procedure was repeated 100 times and then the mean and standard deviation of the tracking errors were calculated for each time interval in the image sequence. The vertical bars represent the standard deviation about the mean. (a) GPF with 200 particles, (b) OCPF with 50 particles, (c) OCPF with 100 particles, and (d) SCPF with 50 particles. Note that the tracking errors are greatest when the neurofilament moves abruptly, e.g., in frames 41, 47, 52, 53, 65, and 70. Nevertheless, SCPF generates small tracking errors compared to GPF and OCPF.