TABLE A2.

Multi-class medical image segmentation F-score evaluation index.

Model	F-score
	DSB2018	Lung	Eye blood vessels	ISBI2015	Liver cancer	Intestinal cancer
UNet (Ronneberger et al., 2015)	0.9502	0.9842	0.8872	0.8864	0.9926	0.9815
LinkNet (Chaurasia and Culurciello, 2018)	0.9446	0.9803	0.8379	0.8657	0.9900	0.9616
U2Net (Qin et al., 2020)	0.9527	0.9864	0.8846	0.8873	0.9926	0.9798
UNet++ (Zhou et al., 2018, 2020)	0.9519	0.9845	0.8855	0.8865	0.9923	0.9863
UNet+++ (Huang et al., 2020)	0.9532	0.9855	0.8851	0.8846	0.9928	0.9850
PraNet (Fan et al., 2020)	0.9732	0.9912	0.9213	0.9274	0.9912	0.9883
PspNet (Zhao et al., 2017)	0.8729	0.9778	0.6350	0.6223	0.9828	0.9712
Deeplabv3+ (Chen et al., 2018)	0.8714	0.9827	0.6337	0.6170	0.9857	0.9653
FCN8 (Long et al., 2015)	0.9478	0.9906	0.7722	0.8278	0.9925	0.9671
MBFFNet	0.9604	0.9839	0.8895	0.8928	0.9926	0.9851