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Table 1 Parameter selection

From: Neuron anatomy structure reconstruction based on a sliding filter

Parameter Value/range Notes
Sliding filter rad 20–30 (voxel) This parameter determines the size of the support region of SVF and SBF. Too large or too small of a region will lead to computation-intensive processes or a reduction in the quality of seeding point selection and radius estimation.
d 8 (voxel) This parameter is the width of the sliding volume and sliding band, and it remains constant in the following experiments.
L 20 This parameter remains constant in the following experiments. Too large of an L value will lead to computationally intensive processes.
R max rad-d/2 This parameter is same in seeding and radius estimation.
R min (d/2, rad-d/2) This parameter is same in seeding and radius estimation. If the datasets are generated from bright field microscopy, a larger R min should be set. Otherwise, a smaller R min should be set.
n 8–32 The larger the n value, the better the radius estimation and the lower the computation efficiency.
T 0.7 This parameter is the threshold used to select the coarse seeding points, and it remains constant in the following experiments.
SEF-Open curve snake t 10–25 In most experiments, 10 is sufficient for the curve evolution in the GVF field of volume after SVF enhancement.
γ 2 This parameter controls the steps of evolution, and it is a fixed constant in following experiments.
ɑ 0.8 This parameter representing the elasticity coefficient remains constant in the following experiments. A larger ɑ value makes the open snake smoother.
β β(s) = 0.2, 0 < s < 1 This parameter of the stiffness coefficient remains constant in the following experiments. A larger β value makes the snake stiffer.
β(s) = 0, s = 0 or s = 1