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. Author manuscript; available in PMC: 2014 Jul 3.
Published in final edited form as: Proc IEEE Symp Biol Data Vis. 2012;2012:1–8. doi: 10.1109/BioVis.2012.6378577

Figure 9.

Figure 9

The influence of the stopping function parameters on segmentation results. A User wants to extract the eye muscle motor neurons from a zebrafish head dataset. The left column shows the selected results; the right column shows the extracted results. A: The default values give satisfactory results: completely selected fiber without much noise. B: Shifting the scalar falloff higher to 0.2 can barely select any fiber at its faintly stained regions. C: Decreasing the scalar falloff includes more noise to the selection. D: Increasing the gradient magnitude falloff includes more details. However further increasing the value does not make much difference, since higher gradient magnitude values become scarce in the data. E: Decreasing the gradient magnitude falloff results disconnected fiber.