Efficient BFCN for Automatic Retinal Vessel Segmentation

Table 4

Comparison between the results of the BFCN and other methods on the DRIVE dataset.

Method	Year	Sensitivity	Specificity	Accuracy	F-measure
Singh and Srivastava [8]	2016	0.7594	0.9723	0.947	—
Zhang et al. [10]	2015	0.7812	0.9668	0.9504	—
Lázár and Hajdu [38]	2015	0.7646	0.9723	0.9458	—
Zhao et al. [39]	2017	0.782	0.979	0.957	—
Zhang et al. [40]	2017	0.7861	0.9712	0.9527	0.7953
Yan et al. [41]	2018	0.8282	0.9738	0.9609	—
Alom [42]	2018	0.7792	0.9813	0.9556	0.8171
Zhuang [43]	2018	0.7856	0.9810	0.9560	0.8202
Wang et al. [44]	2019	0.7940	0.9816	0.9567	0.8270
Samuel and Veeramalai [21]	2019	0.8282	0.9738	0.9609	—
Ours	2019	0.8124	0.9822	0.9627	0.8294