[Retracted] Retinal Vessel Automatic Segmentation Using SegNet

Table 4

Compared with other methods on the DRIVE dataset.

Method	Year	Sensitivity	Specificity	score	MCC	Accuracy	AUC
Neto et al.	2015 [7]	0.7806	0.9629	/	/	0.8718	/
Bahadar et al. [27]	2016	0.7462	0.9801	/	/	0.96075	0.882
Khan et al. [27]	2016	0.746	0.980	/	/	0.961	0.863
Khan et al. [28]	2017	0.754	0.964	/	/	0.944	0.859
Cao et al.	2017	0.7663	0.9311	/	/	0.9174	/
Soomro et al.	2017	0.7523	0.976	/	/	0.9432	/
Cai et al.	2019	0.7787	0.9701	/	/	0.9520	/
Mehmood et al. [15]	2019	0.737	0.976	/	/	0.953	/
Khan et al.	2019	0.754	0.964	/	/	0.944	/
Lai et al.	2019	0.7843	0.9815	/	/	0.9457	/
Yang et al. [34]	2019	0.7560	0.9696	0.7673	0.7365	0.9421	/
Zhou et al.	2020	0.7262	0.9803	/	/	0.9475	/
Khan et al.	2020	0.797	0.973	/	0.739	0.958	0.885
Zhou et al.	2020	0.8432	0.9681	0.8163	0.7905	0.952	0.9754
Wu et al.	2020	0.7996	0.9813			0.9582	0.9830
Huang et al.	2021	0.8011	0.9849	0.8099	/	0.9701	0.8895
The proposed method	2022	0.7580	0.9804	0.7992	0.7749	0.9518	0.9750