Table 1:

Evaluation indices for five calf muscle compartments from different segmentation methods and training datasets. * and ** denote results of paired t-tests vs. nnUNet_80, and nnUNet_350, respectively. See Section III.C. for details of the compared methods. Bolded values represent statistically significant improvements in comparison with the compared approaches.

	TransUNet_80		nnUNet_80	CoTr_80		FilterNet+_80		DeepLOGISMOS_80
	Mean±STD	p value*	Mean±STD	Mean±STD	p value*	Mean±STD	p value*	Mean±STD	p value*
DSC (%)	92.39±0.68	≪0.001	92.93±0.38	93.06±0.30	≪0.001	93.35±0.34	0.124	95.55±0.34	≪0.001
Jaccard (%)	86.75±0.96	≪0.001	87.01±0.62	87.1±0.69	≪0.001	87.71±0.56	0.115	91.66±0.57	≪0.001
ASSD (pixel)	1.50±1.38	≪0.001	1.18±0.78	1.15±1.36	≪0.001	1.15±0.77	0.579	0.80 ±0.75	≪0.001
ASSD Score	86.72±0.93	≪0.001	88.60±0.64	88.72±1.01	≪0.001	88.89±0.63	0.534	92.18±0.63	≪0.001
RSSD (pixel)	0.35±1.27	≪0.001	−0.09±0.78	0.16±0.79	≪0.001	−0.13±0.71	0.361	0.14±0.64	≪0.001
RSSD Score	94.63±0.81	0.02	94.74±0.53	94.93±0.53	0.008	95.28±0.49	0.135	96.83±0.50	≪0.001
ASSDmax95	6.87±5.33	≪0.001	5.23±3.87	4.94±4.32	≪0.001	4.92±3.87	0.244	4.25±4.33	≪0.001
Final Score	90.12±0.78	≪0.001	90.82±0.50	90.95±0.75	≪0.001	91.31±0.47	0.178	94.05±0.48	≪0.001
	TransUNet_350		nnUNet_350	CoTr_350		FilterNet+_350		DeepLOGISMOS_350
	Mean±STD	p value**	Mean±STD	Mean±STD	p value**	Mean±STD	p value*	*Mean±STD	p value**
DSC (%)	94.06±0.37	0.007	94.38±0.34	94.44±0.35	0.60	95.57±0.27	0.050	96.56±0.26	≪0.001
Jaccard (%)	88.99±0.58	0.003	89.52±0.51	89.64±0.55	0.48	90.81±0.44	0.051	93.45±0.43	≪0.001
ASSD (pixel)	1.02±0.75	0.006	0.95 ±0.78	0.96±0.63	0.61	0.94 ±0.64	0.708	0.63 ±0.62	≪0.001
ASSD Score	90.10±0.59	≪0.001	90.73±0.53	90.57±0.54	0.35	91.75±0.48	0.909	93.77±0.48	≪0.001
RSSD (pixel)	0.14±0.70	≪0.001	−0.13±0.81	0.16±0.60	≪0.001	−0.19±0.63	0.014	0.07±0.58	≪0.001
RSSD Score	96.32±0.52	0.017	95.92±0.52	96.49±0.47	≪0.001	97.22±0.43	0.051	97.71±0.42	≪0.001
ASSDmax95	5.50±5.46	≪0.001	4.39±3.57	4.81±3.42	≪0.001	4.18±3.15	0.049	3.50±3.46	≪0.001
Final Score	92.37±0.48	0.07	92.63±0.43	92.79±0.45	0.29	93.84±0.37	0.121	95.37±0.38	≪0.001