. Author manuscript; available in PMC: 2016 Dec 1.

Published in final edited form as: Comput Med Imaging Graph. 2015 Sep 25;46(0 3):277–290. doi: 10.1016/j.compmedimag.2015.09.002

Table 1.

List of parameters used in the proposed landmark detection method. The same set of parameters was used in all experiments.

Parameters	Coarse resolution	Medium resolution	Fine resolution
K: number of trees	10
D_Tree: maximum tree depth	12
N_F: number of random features per tree	1,500
N_T: number of random thresholds per feature	1,000
N_Leaf: minimum number of data items in leaf node	10
R_s: maximum sampling radius in training image (mm)	160	80	40
\|P_Train\|: number of sampled points per training image	6,000
Size (B): size of sampling bounding box in testing image (mm)	200×200×200	100×100×100	50×50×50
\|P_Test\|: number of sampled points in testing image	125
Size(ρ): patch size (in voxels)	30×30×30
s: side length of cubic area within the patch (in voxels)	{3, 5}
Z: number of cubic functions per feature	{1, 2}
MAX_JUMP: maximum number of point jumping	10
T_Len: minimum length of point jumping (in voxels)	0.5
ε: minimum decrease in length of point jumping with tolerance (mm)	−2