Towards Fine Whole-Slide Skeletal Muscle Image Segmentation through Deep Hierarchically Connected Networks

Table 1

The segmentation results compared with state-of-the-art methods.

Method	-score ()		Precision ()		Recall ()
	FT	DT	FT	DT	FT	DT
DC [43]	48 ± 0.093	60 ± 0.138	41 ± 0.066	54 ± 0.164	67 ± 0.194	73 ± 0.148
MCG [44]	63 ± 0.201	71 ± 0.105	53 ± 0.136	64 ± 0.138	80 ± 0.303	82 ± 0.091
DNN-SNM [14]	76 ± 0.033	78 ± 0.080	83 ± 0.042	85 ± 0.089	70 ± 0.058	73 ± 0.087
U-Net [30]	80 ± 0.143	81 ± 0.054	87 ± 0.155	86 ± 0.076	74 ± 0.126	77 ± 0.055
Liu et al. [7]	82 ± 0.172	84 ± 0.061	81 ± 0.043	84 ± 0.071	85 ± 0.202	85 ± 0.068
Our approach	86 ± 0.184	89 ± 0.048	91 ± 0.174	93 ± 0.050	82 ± 0.176	86 ± 0.058

σ is the standard deviation.