Table 5.

Results of BCR-UNet and other methods on DRIVE dataset.

Models	ACC	SEN	SPE	AUC	F1	IOU	MCC
M-Net (35)	0.9674	0.7680	0.9868	0.9829	-	0.6726	-
AG-UNet (16)	0.9692	0.8100	0.9848	0.9856	-	0.6965	-
RSAN (36)	0.9691	0.8149	0.9839	0.9855	0.8222	-	-
NFN+ (37)	0.9668	0.8002	0.9790	0.9832	-	-	-
Pyramid U-Net (21)	0.9615	0.8213	0.9807	0.9815	-	-	-
SCS-Net (38)	0.9697	0.8289	0.9838	0.9837	-	-	-
Deng et al. (39)	0.9683	0.8363	0.9811	-	0.8211	-	-
Xu et al. (40)	0.9689	0.8342	0.9821	0.9858	-	-	-
U-Net (5)	0.9690	0.7906	0.9861	0.9849	0.8170	0.6907	0.8007
Attention UNet (41)	0.9685	0.7663	0.9879	0.9834	0.8099	0.6805	0.7943
SD-UNet (24)	0.9695	0.7831	0.9874	0.9854	0.8182	0.6923	0.8025
MultiResUNet (27)	0.9697	0.7825	0.9876	0.9859	0.8188	0.6931	0.8033
DRNet (20)	0.9672	0.7967	0.9836	0.9815	0.8099	0.6804	0.7921
BCR-UNet	0.9695	0.8183	0.9840	0.9866	0.8246	0.7015	0.8075

Bold values is the highest scores for the metrics.